From da3d012b66796ed59ce3d5f1240e53856ca56a42 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 22 Aug 2023 08:24:43 -0500 Subject: [PATCH 001/268] Adds `ALCF/*` --- ALCF/args.sh | 647 +++++++++++++++++++++++++++++ ALCF/benchmark_train.sh | 82 ++++ ALCF/launch.sh | 151 +++++++ ALCF/model.sh | 264 ++++++++++++ ALCF/mpi_wrapper | 27 ++ ALCF/setup.sh | 228 ++++++++++ ALCF/submit-pbs.sh | 263 ++++++++++++ ALCF/submit.sh | 66 +++ ALCF/sweep_args_theta_multinode.sh | 164 ++++++++ ALCF/train-gpt3.sh | 71 ++++ 10 files changed, 1963 insertions(+) create mode 100755 ALCF/args.sh create mode 100755 ALCF/benchmark_train.sh create mode 100755 ALCF/launch.sh create mode 100755 ALCF/model.sh create mode 100755 ALCF/mpi_wrapper create mode 100755 ALCF/setup.sh create mode 100755 ALCF/submit-pbs.sh create mode 100755 ALCF/submit.sh create mode 100755 ALCF/sweep_args_theta_multinode.sh create mode 100755 ALCF/train-gpt3.sh diff --git a/ALCF/args.sh b/ALCF/args.sh new file mode 100755 index 0000000000..f452d3b7aa --- /dev/null +++ b/ALCF/args.sh @@ -0,0 +1,647 @@ +#!/bin/bash -login + +# SCRIPT_PATH="${BASH_SOURCE[0]}" +# while [ -L "$SCRIPT_PATH" ]; do +# SCRIPT_DIR="$(cd -P "$(dirname "$SCRIPT_PATH")" >/dev/null 2>&1 && pwd)" +# SCRIPT_PATH="$(readlink "$SCRIPT_PATH")" +# [[ ${SCRIPT_PATH} != /* ]] && SCRIPT_PATH="${SCRIPT_DIR}/${SCRIPT_PATH}" +# done +# SCRIPT_PATH="$(readlink -f "$SCRIPT_PATH")" +# SCRIPT_DIR="$(cd -P "$(dirname -- "$SCRIPT_PATH")" >/dev/null 2>&1 && pwd)" +# +# SOURCE=${BASH_SOURCE[0]} +# while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink +# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +# SOURCE=$(readlink "$SOURCE") +# [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located +# done +# DIR="$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd )" + +function FindMegatron() { + MEGATRON_INSTALL=$(python3 -c 'import megatron; print(megatron.__file__)' | tail -1) + MEGATRON_DIR=$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1))) +} + +function WhereAmI() { + python3 -c 'import os; print(os.getcwd())' +} + +HERE=$(WhereAmI) +ALCF_DIR=$(find "${HERE}" -name "ALCF") + +# [ "${MEGATRON_DIR}" ] && echo "Caught ${MEGATRON_DIR} from env" || FindMegatron +# ALCF_DIR="${MEGATRON_DIR}/ALCF" +# ALCF_DIR="$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1)))/ALCF" +PARENT=$(dirname "${ALCF_DIR}") +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" +echo "ALCF_DIR: ${ALCF_DIR}" +echo "PARENT: ${PARENT}" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source="${FILE}" + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi +} + +USER=$(whoami) + +# # DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd -LP) +# PARENT=$(dirname "$DIR") +# +# HERE=$(python3 -c 'import os; print(os.getcwd())') + +# echo "------------------------" +# echo "SCRIPT_DIR=$SCRIPT_DIR" +# echo "SCRIPT_PATH=$SCRIPT_PATH" +# echo "------------------------" +# echo "SOURCE=$SOURCE" +# echo "DIR=$DIR" +# echo "PARENT: ${PARENT}" +# echo "HERE: ${HERE}" +# echo "------------------------" + +if [[ $(hostname) == theta* ]]; then + echo "Setting up ThetaGPU from $(hostname)" + HOSTFILE="${COBALT_NODEFILE}" +elif [[ $(hostname) == x* ]]; then + echo "Setting up Polaris from $(hostname)" + HOSTFILE="${PBS_NODEFILE}" +else + echo "Unexpected hostname $(hostname)" +fi + +NHOSTS=$(wc -l < "${HOSTFILE}") +NGPU_PER_HOST=$(nvidia-smi -L | wc -l) +NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" +WORLD_SIZE="${NGPUS}" +PARALLEL_SIZE="${WORLD_SIZE}" +# # NGPUS="$((${NHOSTS}*${NGPU_PER_HOST}))" +echo "NHOSTS * (NGPU / HOST) = $NHOSTS * $NGPU_PER_HOST = $NGPUS" + + +export MODEL_SIZE_KEY="${MODEL_SIZE_KEY:-GPT13B}" +echo "==========================+" +echo "Using ${MODEL_SIZE_KEY}" +echo "==========================+" + +sourceFile "${ALCF_DIR}/model.sh" + +MODEL_TYPE=${MODEL_TYPE:-gpt} + +# ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ Model Parallel / Pipeline Parallel ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +# ---------- +# Originals +# MPSIZE=8 +# PPSIZE=16 +# ---------- +# NHOSTS=$(wc -l < "${PBS_NODEFILE}") +export DDP_IMPL="local" # FSDP | local | torch +export USE_FLASH_ATTN=${USE_FLASH_ATTN:-0} # 1 | 0 +export USE_ACTIVATION_CHECKPOINTING=1 # 1 | 0 +export SEQ_LEN=${SEQ_LEN:-2048} +export PPSIZE=${PPSIZE:-1} +# export MPSIZE=${MPSIZE:-1} +# export SPSIZE=${SPSIZE:-1} +export MICRO_BATCH=${MICRO_BATCH:-1} +# export ZERO_STAGE=${ZERO_STAGE:-1} # 0 | 1 | 2 | 3 +export GRADIENT_ACCUMULATION_STEPS=${GAS:-1} +# export NHOSTS="$NHOSTS" +# export USE_SEQUENCE_PARALLEL=${USE_SEQUENCE_PARALLEL:-0} # 1 | 0 + +# NHOSTS=$(wc -l < "${COBALT_NODEFILE}") +# # NGPU_PER_HOST=8 +# NGPU_PER_HOST=$(nvidia-smi -L | wc -l) +# PARALLEL_SIZE=$((${NHOSTS}*${NGPU_PER_HOST})) + +export MODEL_TYPE=${MODEL_TYPE:-"gpt"} # set bert or gpt +export SP_TYPE=${SP_TYPE:-"megatron"} # set ds or megatron + + +# Deal with Sequence Parallel implementation --------------------------------------- +# ---------------------------------------------------------------------------------- +if [[ ${SP_TYPE} == "ds" ]]; then + # NOTE: -------------------------------------------------------------------------- + # SP_TYPE="ds" has NO effect, essentially running with no Seq. || + # -------------------------------------------------------------------------------- + USE_SEQUENCE_PARALLEL=0 + if [[ "$MPSIZE" == "${WORLD_SIZE}" ]]; then + echo "Caught MPSIZE: $MPSIZE from env. Setting SPSIZE=1" + SPSIZE=1 + MPSIZE="${MPSIZE}" + else + echo "Didn't catch MPSIZE from env. Setting SPSIZE=${WORLD_SIZE}, MPSIZE=1" + MPSIZE=1 + SPSIZE="${WORLD_SIZE}" + fi + # if [[ "$MPSIZE" != 0 ]]; then + # SPSIZE=$(( WORLD_SIZE - MPSIZE )) + # echo "############################################################" + # echo "Caught MPSIZE: $MPSIZE from env!" + # echo "Setting SPSIZE: (${WORLD_SIZE} - ${MPSIZE}) = ${SPSIZE}" + # echo "############################################################" + # else + # MPSIZE=1 + # SPSIZE="$WORLD_SIZE" + # echo "############################################################" + # echo "Setting MPSIZE: $SPSIZE, SPSIZE: $WORLD_SIZE = $SPSIZE" + # echo "############################################################" + # fi + # [ "$MPSIZE" ] && SPSIZE=1 || SPSIZE="${WORLD_SIZE}" + # [ "$SPSIZE" ] && MPSIZE=1 || MPSIZE="${}" + # [ "$MPSIZE" = "$WORLD_SIZE" ] && SPSIZE=1 || SPSIZE="$WORLD_SIZE" + # [ "$SPSIZE" = "$WORLD_SIZE" ] && MPSIZE=1 || MPSIZE="${WORLD_SIZE}" + # export SPSIZE="${WORLD_SIZE}" + export SPSIZE="${SPSIZE:-$WORLD_SIZE}" + export MPSIZE="${MPSIZE:-1}" + export USE_SEQUENCE_PARALLEL=0 + if [ -z "${ZERO_STAGE}" ]; then + echo "ZERO_STAGE not set, setting to 3 for ${SP_TYPE}" + ZERO_STAGE=3 + else + echo "Caught ZERO_STAGE=${ZERO_STAGE} with ${SP_TYPE}" + fi + export ZERO_STAGE="${ZERO_STAGE}" +elif [[ ${SP_TYPE} == "megatron" ]]; then + # NOTE: -------------------------------------------------------------------------- + # SP_TYPE="megatron" will use Megatron's Seq. || implementation with ZERO_STAGE=0 + # -------------------------------------------------------------------------------- + # export SPSIZE=1 + # export MPSIZE="${WORLD_SIZE}" + [ "$SPSIZE" ] && echo "Caught SPSIZE: ${SPSIZE} from env" || SPSIZE=1 + [ "$MPSIZE" ] && echo "Caught MPSIZE: ${MPSIZE} from env" || MPSIZE="${WORLD_SIZE}" + [ "$ZERO_STAGE" ] && echo "Caught ${ZERO_STAGE} from env" || ZERO_STAGE=0 + # [ "$USE_SEQUENCE_PARALLEL" = 0 ] && export USE_SEQUENCE_PARALLEL=0 || export USE_SEQUENCE_PARALLEL=1 + # if [[ "$SPSIZE" == 0 ]]; then + # echo "Caught SPSIZE=$SPSIZE from env!!" + # USE_SEQUENCE_PARALLEL=0 + # else + # USE_SEQUENCE_PARALLEL=1 + # fi + # if [[ "$USE_SEQUENCE_PARALLEL" ]]; then + # echo "Caught USE_SEQUENCE_PARALLEL=${USE_SEQUENCE_PARALLEL} from env!!" + # [ "${SPSIZE}" != 0 ] && USE_SEQUENCE_PARALLEL=1 || USE_SEQUENCE_PARALLEL=0 + # [ "$USE_SEQUENCE_PARALLEL" = 0 ] && echo "Not using sequence parallelism" || USE_SEQUENCE_PARALLEL=1 + export SPSIZE="${SPSIZE}" + export MPSIZE="${MPSIZE}" + export ZERO_STAGE="${ZERO_STAGE}" + export USE_SEQUENCE_PARALLEL="${USE_SEQUENCE_PARALLEL:-1}" + # if [[ "${SPSIZE}" == 0 ]]; then + # [ "$SPSIZE" ] && USE_SEQUENCE_PARALLEL=1 || USE_SEQUENCE_PARALLEL=0 + # echo "Caught SPSIZE=${SPSIZE} from env, with ${SP_TYPE} sequence parallelism" + # export SPSIZE="${SPSIZE}" + # export USE_SEQUENCE_PARALLEL=0 + # else + # export SPSIZE=1 + # export USE_SEQUENCE_PARALLEL=1 + # fi + # if [ -z "${ZERO_STAGE}" ]; then + # echo "ZERO_STAGE not set, setting to 0 for ${SP_TYPE}" + # ZERO_STAGE=0 + # else + # echo "Caught ZERO_STAGE=${ZERO_STAGE} with ${SP_TYPE}" + # fi +else + echo "Unexpected SP_TYPE: ${SP_TYPE}" + exit 1 +fi +# ------------------------------------------------------------------------ + +echo "####################################################" +echo "# USING: ${SP_TYPE}" +echo "# SPSIZE: ${SPSIZE}" +echo "# PPSIZE: ${SPSIZE}" +echo "# MPSIZE: ${MPSIZE}" +echo "# ZERO_STAGE: ${ZERO_STAGE}" +echo "# WORLD_SIZE: ${WORLD_SIZE}" +echo "# USE_SEQUENCE_PARALLEL: ${USE_SEQUENCE_PARALLEL}" +echo "####################################################" + +echo "########################################################" +echo "| ${SP_TYPE} sequence parallelism, with: " +echo "| {MPSIZE: ${MPSIZE}, SPSIZE: ${SPSIZE}, USE_SEQUENCE_PARALLEL: ${USE_SEQUENCE_PARALLEL}} !!" +echo "########################################################" + +# GLOBAL_BATCH=1 +# GLOBAL_BATCH=$(( $GLOBAL_BATCH / $MPSIZE / $PPSIZE / $SPSIZE )) +# GLOBAL_BATCH=$(( $NGPUS * $MICRO_BATCH * $GRADIENT_ACCUMULATION_STEPS )) +GLOBAL_BATCH=$(( NGPUS * MICRO_BATCH * GRADIENT_ACCUMULATION_STEPS )) +echo "GB = NGPUS * MB * GAS = ${NGPUS} * ${MICRO_BATCH} * ${GRADIENT_ACCUMULATION_STEPS} = ${GLOBAL_BATCH}" + +GLOBAL_BATCH=$(( GLOBAL_BATCH / MPSIZE / PPSIZE / SPSIZE)) +echo "GB = (NGPUS * MB * GAS) / (MP * PP * SP) = (${NGPUS} * ${MICRO_BATCH} * ${GRADIENT_ACCUMULATION_STEPS}) / (${MPSIZE} * ${PPSIZE} * ${SPSIZE}) = ${GLOBAL_BATCH}" +export GLOBAL_BATCH="$GLOBAL_BATCH" + +echo "--------------------------------" +echo "GLOBAL_BATCH=${GLOBAL_BATCH}" +echo "--------------------------------" + +# ┏━━━━━━━━━━━━┓ +# ┃ Data paths ┃ +# ┗━━━━━━━━━━━━┛ +# DATA_PATH=/lus/grand/projects/datascience/vsastry/genslm_subsample_200k_sequence_document/genslm_subsample_200k_sequence_document +DATA_DIR="${PARENT}/dataset" +DATA_PATH="${DATA_DIR}/BookCorpusDataset_text_document" +VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" +MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" + +# DATA_PATH="/home/czh5/genome/Megatron-DeepSpeed/dataset/BookCorpusDataset_text_document" +# VOCAB_FILE="/home/czh5/genome/Megatron-DeepSpeed/dataset/gpt2-vocab.json" +# MERGE_FILE="/home/czh5/genome/Megatron-DeepSpeed/dataset/gpt2-merges.txt" +# DATA_PATH="/lus/eagle/projects/MDClimSim/chengming/gpt_datasets1/BookCorpusDataset_text_document" +# VOCAB_FILE="/lus/eagle/projects/MDClimSim/chengming/gpt_datasets1/gpt2-vocab.json" +# MERGE_FILE="/lus/eagle/projects/MDClimSim/chengming/gpt_datasets1/gpt2-merges.txt" + +# ┏━━━━━━━━━━━━━━━━━━━┓ +# ┃ FILE I/O SETTINGS ┃ +# ┗━━━━━━━━━━━━━━━━━━━┛ +RUN_STR="gb${GLOBAL_BATCH}_mb${MICRO_BATCH}" +RUN_STR="nl${NLAYERS}_hs${HIDDEN}_${RUN_STR}" +RUN_STR="mp${MPSIZE}_pp${PPSIZE}_sp${SPSIZE}_${RUN_STR}" +RUN_STR="z${ZERO_STAGE}_seqlen${SEQ_LEN}_${RUN_STR}" +RUN_STR="${MODEL_SIZE}_${RUN_STR}" + +if [[ $USE_FLASH_ATTN == 1 ]] ; then + RUN_STR="flashAttn_${RUN_STR}" +fi +if [[ $DDP_IMPL == 'FSDP' ]]; then + RUN_STR="FSDP_${RUN_STR}" +fi +if [[ $USE_ACTIVATION_CHECKPOINTING == 1 ]] ;then + RUN_STR="actCkpt_${RUN_STR}" +fi +if [[ $USE_SEQUENCE_PARALLEL == 1 ]] ; then + RUN_STR="SP_${RUN_STR}" +fi + +RUN_STR="${MODEL_TYPE}_${RUN_STR}" + +OUTPUT_DIR="${PARENT}/outputs/${RUN_STR}" +CHECKPOINT_DIR="${PARENT}/checkpoints/$RUN_STR" +TENSORBOARD_DIR="${PARENT}/outputs/${RUN_STR}/tensorboard" + +export MODEL_SIZE="$MODEL_SIZE" +export TENSORBOARD_DIR=$TENSORBOARD_DIR +export OUTPUT_DIR=$OUTPUT_DIR +mkdir -p "$OUTPUT_DIR/tensorboard/wandb" +mkdir -p "$CHECKPOINT_DIR" +mkdir -p "$TENSORBOARD_DIR" +mkdir -p "$OUTPUT_DIR" +echo "OUTPUT TO: ${OUTPUT_DIR}" + +# if [[ -z "${NVME_PATH}" ]]; then +# echo "NVME_PATH: $NVME_PATH" +# else +# if [[ $(hostname) == x* ]]; then +# export NVME_PATH="/local/scratch/" +# elif [[ $(hostname) == theta* ]]; then +# export NVME_PATH="/raid/scratch/" +# else +# export NVME_PATH="/tmp/" +# fi +# fi + +# echo "NVME_PATH: ${NVME_PATH}" + +if [[ $MODEL_TYPE == "gpt" ]] ; then + DATA_LOAD_ARGS="--data-path $DATA_PATH --vocab-file $VOCAB_FILE --merge-file $MERGE_FILE" +else + DATA_LOAD_ARGS="" +fi + +# Set to cpu for offloading to cpu for larger models +OFFLOAD_DEVICE="${OFFLOAD_DEVICE:-cpu}" +CPU_OPTIM=" --cpu-optimizer" + +# # Set to none and empty string for no cpu offloading +# OFFLOAD_DEVICE="none" +# CPU_OPTIM=" " + +# ┏━━━━━━━━━━━━━━━━━━┓ +# ┃ DeepSpeed Config ┃ +# ┗━━━━━━━━━━━━━━━━━━┛ +DS_CONFIG=${PARENT}/ds_config-gpt.json +echo "!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~!" +echo "! DS_CONFIG: ${DS_CONFIG}" +echo "!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~!" +# "optimizer": { +# "type": "Adam", +# "params": { +# "lr": 0.001, +# "betas": [0.8, 0.999], +# "eps": 1e-8, +# "weight_decay": 3e-7 +# } +# }, + +# "zero_allow_untested_optimizer": false, +# "train_batch_size" : $GLOBAL_BATCH, +# "zero_force_ds_cpu_optimizer": false, +if [[ $ZERO_STAGE == "3" ]] ; then +cat < "$DS_CONFIG" +{ + "train_micro_batch_size_per_gpu": $MICRO_BATCH, + "steps_per_print": 1, + "wall_clock_breakdown" : true, + "gradient_accumulation_steps": $GRADIENT_ACCUMULATION_STEPS, + "gradient_clipping": 1.0, + "zero_optimization": { + "stage": 3, + "stage3_max_live_parameters": 3e9, + "stage3_max_reuse_distance": 3e9, + "stage3_param_persistence_threshold": 1e5, + "stage3_prefetch_bucket_size": 1e9, + "contiguous_gradients": true, + "overlap_comm": true, + "reduce_bucket_size": 90000000, + "sub_group_size": 5e7, + "offload_param": { + "device": "cpu", + "pin_memory": true + }, + "offload_optimizer": { + "device": "cpu", + "buffer_count": 4, + "pipeline_read": false, + "pipeline_write": false, + "pin_memory": true + } + }, + "fp16": { + "enabled": true, + "initial_scale_power" : 12, + "loss_scale_window": 1000, + "hysteresis": 2, + "min_loss_scale": 1 + }, + "aio": { + "block_size": 1048576, + "queue_depth": 16, + "single_submit": false, + "overlap_events": true, + "thread_count": 2 + }, + "flops_profiler": { + "enabled": true, + "profile_step": 1, + "module_depth": -1, + "top_modules": 3, + "detailed": true, + "output_file": null + }, + "comms_logger": { + "enabled": true, + "verbose": false, + "prof_all": false, + "debug": false + }, + "wandb": { + "enabled": true, + "project": "Megatron-DS-Benchmarking" + } +} +EOT +else +cat < "$DS_CONFIG" +{ + "train_micro_batch_size_per_gpu": $MICRO_BATCH, + "gradient_accumulation_steps": $GRADIENT_ACCUMULATION_STEPS, + "steps_per_print": 1, + "wall_clock_breakdown" : true, + "zero_force_ds_cpu_optimizer": false, + "zero_optimization": { + "stage": $ZERO_STAGE, + "allgather_partitions": true, + "reduce_scatter": true, + "allgather_bucket_size": 5e8, + "overlap_comm": true, + "contiguous_gradients": true, + "offload_optimizer": { + "device": "cpu" + } + }, + "optimizer": { + "type": "OneBitAdam" + }, + "scheduler": { + "type": "WarmupLR", + "params": { + "warmup_min_lr": 0, + "warmup_max_lr": 0.001, + "warmup_num_steps": 1000 + } + }, + "fp16": { + "enabled": true, + "initial_scale_power": 12 + }, + "flops_profiler": { + "enabled": true, + "profile_step": 1, + "module_depth": -1, + "top_modules": 3, + "detailed": true, + "output_file": null + }, + "comms_logger": { + "enabled": true, + "verbose": false, + "prof_all": false, + "debug": false + }, + "wandb": { + "enabled": true, + "project": "Megatron-DS-Benchmarking" + } +} +EOT +fi +# "optimizer": { +# "type": "Adam", +# "params": { +# "lr": 0.001, +# "betas": [0.8, 0.999], +# "eps": 1e-8, +# "weight_decay": 3e-7 +# } +# }, +# +# "offload_optimizer": { +# "device": "$OFFLOAD_DEVICE", +# "buffer_count": 4, +# "pipeline_read": false, +# "pipeline_write": false, +# "pin_memory": true +# } +# "train_batch_size" : $GLOBAL_BATCH, +# 'offload_optimizer': 'cpu' + # "train_batch_size" : $GLOBAL_BATCH, +# "offload_optimizer": { +# "device": "cpu", +# "nvme_path": "/raid/scratch/" +# } +# +# "optimizer": { +# "type": "AdamW", +# "params": { +# "lr": 0.001, +# "betas": [0.8, 0.999], +# "eps": 1e-8, +# "weight_decay": 3e-7 +# } +# }, +# "optimizer": { +# "type": "OneBitAdam", +# "params": { +# "lr": 0.001, +# "betas": [ +# 0.8, +# 0.999 +# ], +# "eps": 1e-8, +# "weight_decay": 3e-7, +# "freeze_step": 400, +# "cuda_aware": false, +# "comm_backend_name": "nccl" +# } +# }, +# +# "optimizer": "Adam", +# "optimizer": { +# "type": "OneBitAdam", +# "params": { +# "lr": 0.001, +# "betas": [ +# 0.8, +# 0.999 +# ], +# "eps": 1e-8, +# "weight_decay": 3e-7, +# "freeze_step": 400, +# "cuda_aware": true, +# "comm_backend_name": "nccl" +# } +# }, +# +# +# 'deepspeed_mpi': True, +# 'ds_pipeline_enabled': False, +# 'rank': 0, +# 'world_size': 1, +# 'transformer_pipeline_model_parallel_size': 1, +# 'data_parallel_size': 1, +# 'virtual_pipeline_model_parallel_ size': None, + + +# ┏━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ DeepSpeed Arguments ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━┛ +if [[ "$DDP_IMPL" != "FSDP" ]] ; then + ds_args="" + ds_args=" --deepspeed ${ds_args}" + ds_args=" --deepspeed_mpi ${ds_args}" + ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" + ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" + if [[ "$PPSIZE" == 1 ]]; then + ds_args="--no-pipeline-parallel ${ds_args}" + else + ds_args=" --pipeline-model-parallel-size ${PPSIZE} ${ds_args}" + fi + if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + ds_args=" --deepspeed-activation-checkpointing ${ds_args}" + fi +fi + +# ┏━━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ MEGATRON-LM SETTINGS ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━━┛ +# "--sequence-parallel-size ${SPSIZE}" +gpt_args=( + "--seed ${RANDOM}" + "--DDP-impl ${DDP_IMPL}" + "--pipeline-model-parallel-size ${PPSIZE}" + "--tensor-model-parallel-size ${MPSIZE}" + "--num-layers ${NLAYERS}" + "--hidden-size ${HIDDEN}" + "--num-attention-heads ${ATEN_HEADS}" + "--micro-batch-size ${MICRO_BATCH}" + "--global-batch-size ${GLOBAL_BATCH}" + "--seq-length ${SEQ_LEN}" + "--max-position-embeddings ${SEQ_LEN}" + "--train-iters 10" + "--lr-decay-iters 320000" + "--num-workers 1" + "$DATA_LOAD_ARGS" + "--data-impl mmap" + "--split 949,50,1" + "--distributed-backend nccl" + "--lr 0.00015" + "--lr-decay-style cosine" + "--min-lr 1.0e-5" + "--weight-decay 1e-2" + "--clip-grad 1.0" + "--lr-warmup-fraction .01" + "--log-interval 1" + "--save-interval 1000" + "--eval-interval 1000" + "--eval-iters 10" + "--override-opt_param-scheduler" + "--tensorboard-dir ${TENSORBOARD_DIR}" + "--log-timers-to-tensorboard" + "--tensorboard-log-interval 1" +) + +# --recompute-activations \ +# --recompute-granularity full \ +# --recompute-method uniform \ +# --recompute-num-layers 1 \ +if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + gpt_args+=( + "--checkpoint-activations" + "--checkpoint-num-layers 1" + ) +fi + +if [[ "$DDP_IMPL" != "FSDP" ]] ; then + gpt_args+=( + # "${gpt_args[*]}" + "--fp16" + ) +else + gpt_args+=( + "--bf16" + ) +fi + +if [[ "$USE_FLASH_ATTN" == 1 ]] ; then + gpt_args+=( + "--use-flash-attn" + ) +fi + +# if [[ "$USE_SEQUENCE_PARALLEL" == 1 ]]; then +# gpt_args+=( +# "--sequence-parallel" +# ) +# fi + +if [[ "${SP_TYPE}" == "ds" ]]; then + gpt_args+=( + "--cpu-optimizer" + ) +fi + +export gpt_args=( + "${gpt_args[*]}" + "${ds_args[*]}" +) +echo "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" +echo "gpt_args: ${gpt_args[*]}" +echo "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" diff --git a/ALCF/benchmark_train.sh b/ALCF/benchmark_train.sh new file mode 100755 index 0000000000..94eb94e116 --- /dev/null +++ b/ALCF/benchmark_train.sh @@ -0,0 +1,82 @@ +#!/bin/bash --login + +TSTAMP=$(date "+%Y-%m-%d-%H%M%S") +# DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd -LP) +# + +#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +#┃ Make sure we're not already running; if so, exit here ┃ +#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +PIDS=$(ps aux | grep pretrain_gpt.py | grep -v grep | awk '{print $2}') +if [ -n "${PIDS}" ]; then + echo "Already running! Exiting!" + exit 1 +fi + + +SOURCE=${BASH_SOURCE[0]} +while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink + DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) + SOURCE=$(readlink "$SOURCE") + [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located +done +DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) + + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source="${FILE}" + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi +} + +SETUP_FILE="${DIR}/setup.sh" +MODEL_FILE="${DIR}/model.sh" +ARGS_FILE="${DIR}/args.sh" +LAUNCH_FILE="${DIR}/launch.sh" + + +sourceFile "${SETUP_FILE}" +sourceFile "${MODEL_FILE}" +sourceFile "${ARGS_FILE}" +sourceFile "${LAUNCH_FILE}" + + +SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) +echo "My current script is: ${SCRIPT_DIR[0]}" + +NHOSTS=$(wc -l < "${COBALT_NODEFILE}") +# NGPU_PER_HOST=8 +NGPU_PER_HOST=$(nvidia-smi -L | wc -l) +PARALLEL_SIZE=$(( NHOSTS * NGPU_PER_HOST )) + +export MODEL_TYPE=${MODEL_TYPE:-"gpt"} # set bert or gpt +export SP_TYPE=${SP_TYPE:-"megatron"} # set ds or megatron + +echo "+-----------------------------+" +echo "| MODEL TYPE: ${MODEL_TYPE}" +echo "| SP TYPE: ${SP_TYPE}" +echo "+-----------------------------+" + +#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +#┃ source ./launch.sh ┃ +#┃ which then sources ./{args.sh,setup.sh} ┃ +#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ + +export MODEL_TYPE=${MODEL_TYPE:-gpt} + +setup +# singleGPU "$@" 2>&1 & +# fullNode "$@" 2>&1 & +TORCH_VERSION=$(python3 -c 'import torch; print(torch.__version__)') +export TORCH_VERSION=$TORCH_VERSION +export CUDA_DEVICE_MAX_CONNECTIONS=1 +# fullNode "$@" +# elasticDistributed "$@" 2>&1 & +# elasticDistributed "$@" +PID=$! +wait $PID diff --git a/ALCF/launch.sh b/ALCF/launch.sh new file mode 100755 index 0000000000..7604098667 --- /dev/null +++ b/ALCF/launch.sh @@ -0,0 +1,151 @@ +#!/bin/bash --login + +HOST=$(hostname) + +# # DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd -LP) +# SOURCE=${BASH_SOURCE[0]} +# while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink +# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +# SOURCE=$(readlink "$SOURCE") +# [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located +# done + +# HERE=$(python3 -c 'import os; print(os.getcwd())') +# ALCF_DIR="${HERE}/ALCF" +# +ALCF_DIR="$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1)))/ALCF" +PARENT=$(dirname "${ALCF_DIR}") + +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" +echo "ALCF_DIR: ${ALCF_DIR}" +echo "PARENT: ${PARENT}" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" + + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source=./setup.sh + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi +} + +# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +# PARENT=$(dirname "${DIR}") + +MASTER_ADDR=$(uname -n) +MASTER_PORT=20010 +SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )" +MPI_WRAPPER="${SCRIPT_DIR}/mpi_wrapper" + +sourceFile "${ALCF_DIR}/args.sh" + +MAIN="${PARENT}/pretrain_${MODEL_TYPE}.py" + +printJobInfo() { + echo "Job started at: ${TSTAMP} on $(hostname)" + echo "Job running in: ${DIR}" + echo "Training GPT-3 with ${MODEL_SIZE} parameters" + echo "Writing logs to: ${OUTPUT_DIR}" + echo 'to view output: tail -f $(tail -1 logfiles)' + echo "i.e. tail -f $(tail -1 "${PARENT}"/logfiles)" +} + +launchJob() { + echo "using: $(which python3)" | tee -a "${OUTPUT_LOG}" + printJobInfo | tee -a "${OUTPUT_LOG}" + echo EXEC="${EXEC}" | tee -a "${OUTPUT_LOG}" + echo "Writing logs to: ${OUTPUT_LOG}" | tee -a "${OUTPUT_LOG}" + ${EXEC} "$@" # >> "${OUTPUT_LOG}" 2>&1 & +} + +singleGPU() { + echo "\ + Running on 1 host \ + with 1 GPUs each \ + for a total of 1 GPUs" + EXEC="\ + $(which python3) \ + ${MAIN} \ + ${gpt_args} \ + ${ds_args}" + OUTPUT_LOG="${OUTPUT_DIR}/logs/$USER-$HOST-nhosts1-ngpu1-$TSTAMP.log" + mkdir -p "$(dirname "${OUTPUT_LOG}")" + echo "${OUTPUT_LOG}" >> "${PARENT}/logfiles" + printJobInfo | tee -a "${OUTPUT_LOG}" + launchJob "$@" >> "${OUTPUT_LOG}" 2>&1 & +} + +# ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ Use all available GPUs a single nodes ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +fullNode() { + echo "fullNode started" + echo "MPI_COMMAND ${MPI_COMMAND}" + echo "MPI_DEFAULTS ${MPI_DEFAULTS}" + echo "NGPUS ${NGPUS}" + echo "hostfile ${DIR}/hostfile" + echo "MAIN ${MAIN}" + echo "gpt_args ${gpt_args}" + NHOSTS=$(wc -l < "${HOSTFILE}") + NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + # NGPU_PER_HOST=1 + NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) + # hostname > $DIR/hostfile + echo "\ + Running on $NHOSTS hosts \ + with $NGPU_PER_HOST GPUs each \ + for a total of $NGPUS GPUs" + EXEC="\ + ${MPI_COMMAND} \ + ${MPI_DEFAULTS} \ + "${MPI_ELASTIC}" + ${MPI_WRAPPER} ${MASTER_ADDR} ${MASTER_PORT} \ + ${MAIN} \ + ${gpt_args} \ + ${ds_args}" + OUTPUT_LOG="${OUTPUT_DIR}/logs/$USER-$HOST-nhosts${NHOSTS}-ngpu${NGPUS}-$TSTAMP.log" + mkdir -p "$(dirname "${OUTPUT_LOG}")" + echo "${OUTPUT_LOG}" >> "${PARENT}/logfiles" + printJobInfo | tee -a "${OUTPUT_LOG}" + launchJob "$@" 2>&1 | tee "${OUTPUT_LOG}" +} + +# ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ Use all available GPUs on all available nodes ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +elasticDistributed() { + NHOSTS=$(wc -l < "${HOSTFILE}") + NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) + export WORLD_SIZE="${NGPUS}" + echo "\ + Running on ${NHOSTS} hosts \ + with ${NGPU_PER_HOST} GPUs each \ + for a total of ${NGPUS} GPUs" + EXEC_STR=( + "${MPI_COMMAND}" + "${MPI_DEFAULTS}" + "${MPI_ELASTIC}" + "$(which python3)" + "${MAIN}" + "${gpt_args}" + "${ds_args}" + ) + EXEC="${EXEC_STR[*]}" + OUTPUT_LOG="${OUTPUT_DIR}/logs/$USER-$HOST-nhosts${NHOSTS}-ngpu${NGPUS}-$TSTAMP.log" + echo "Writing logs to: ${OUTPUT_LOG}" + mkdir -p "$(dirname "${OUTPUT_LOG}")" + echo "${OUTPUT_LOG}" >> "${PARENT}/logfiles" + printJobInfo | tee -a "${OUTPUT_LOG}" + # launchJob "$@" >> "${OUTPUT_LOG}" 2>&1 & + # launchJob "$@" + # printJobInfo | tee -a "${OUTPUT_LOG}" + # launchJob "$@" >> "${OUTPUT_LOG}" 2>&1 & + launchJob "$@" >> "${OUTPUT_LOG}" 2>&1 & + PID=$! + wait $PID +} diff --git a/ALCF/model.sh b/ALCF/model.sh new file mode 100755 index 0000000000..2427893e9b --- /dev/null +++ b/ALCF/model.sh @@ -0,0 +1,264 @@ +#!/bin/bash --login +#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +#┃ GPT MODEL SETTINGS ┃ +#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +# ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ Model / Architecture settings ┃ +# ┃ ---------------------------------------------------- ┃ +# ┃ GPT-3 models use 2K sequence length/context window ┃ +# ┃ The "GPT-3 XXX" below are configs from GPT-3 paper ┃ +# ┃ https://arxiv.org/abs/2005.14165, choose based on ┃ +# ┃ your desired model size or build your own configs ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ + +declare -A A_NLAYERS +declare -A A_HIDDEN +declare -A A_ATEN_HEADS + +# ┏━━━━━━━━━━━━━━━━━━━━┓ +# ┃ GPT-3 Small: 125M ┃ +# ┗━━━━━━━━━━━━━━━━━━━━┛ +MODEL_125M_KEY="GPT125M" +A_NLAYERS[$MODEL_125M_KEY]=12 +A_HIDDEN[$MODEL_125M_KEY]=768 +A_ATEN_HEADS[$MODEL_125M_KEY]=16 + +# ┏━━━━━━━━━━━━━━━━━━━━┓ +# ┃ BERT: 1.2B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="BERT1.2B" +# NLAYERS=24 +# HIDDEN=2048 +# ATEN_HEADS=128 + +BERT_1_2B_KEY="BERT1.2B" +A_NLAYERS[$BERT_1_2B_KEY]=24 +A_HIDDEN[$BERT_1_2B_KEY]=2048 +A_ATEN_HEADS[$BERT_1_2B_KEY]=128 + +# ┏━━━━━━━━━━━━━━━━━━━━┓ +# ┃ GPT-3: 1.5B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="1.5B" +# NLAYERS=48 +# HIDDEN=1536 +# ATEN_HEADS=24 + +MODEL_1_5B_KEY="GPT1_5B" +A_NLAYERS[$MODEL_1_5B_KEY]=48 +A_HIDDEN[$MODEL_1_5B_KEY]=1536 +A_ATEN_HEADS[$MODEL_1_5B_KEY]=24 + +# ┏━━━━━━━━━━━━━━━━━━━━┓ +# ┃ GPT-3: 1.5B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="1.5B" +# NLAYERS=48 +# HIDDEN=1600 +# ATEN_HEADS=25 + +# ┏━━━━━━━━━━━━━━━━━━━━┓ +# ┃ GPT-3: 2.7B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="2.7B" +# NLAYERS=32 +# HIDDEN=2560 +# ATEN_HEADS=32 + +MODEL_2_7B_KEY="GPT2_7B" +A_NLAYERS[$MODEL_2_7B_KEY]=32 +A_HIDDEN[$MODEL_2_7B_KEY]=2560 +A_ATEN_HEADS[$MODEL_2_7B_KEY]=32 + +# ┏━━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ ✓ GPT-3: 6.7B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="6.7B" +# NLAYERS=32 +# HIDDEN=4096 +# ATEN_HEADS=32 + +MODEL_6_7B_KEY="GPT6_7B" +A_NLAYERS[$MODEL_6_7B_KEY]=32 +A_HIDDEN[$MODEL_6_7B_KEY]=4096 +A_ATEN_HEADS[$MODEL_6_7B_KEY]=32 + +# ┏━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ ✓ GPT-3: 13B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="13B" +# NLAYERS=40 +# HIDDEN=5120 +# ATEN_HEADS=40 + +MODEL_13B_KEY="GPT13B" +A_NLAYERS[$MODEL_13B_KEY]=40 +A_HIDDEN[$MODEL_13B_KEY]=5120 +A_ATEN_HEADS[$MODEL_13B_KEY]=64 + +# ┏━━━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ ✓ GPT-3: 18.4B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="18.4B" +# NLAYERS=40 +# HIDDEN=6144 +# ATEN_HEADS=48 + +# ┏━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ ✓ GPT-3: 20B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="20B" +# NLAYERS=44 +# HIDDEN=6144 +# ATEN_HEADS=64 + +# ┏━━━━━━━━━━━━━━━━━━━┓ +# ┃ GPT-3: 25B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="25B" +# NLAYERS=64 +# ------------ +# HIDDEN=5760 # DEFAULT (no flash attn) +# ATEN_HEADS=64 +# ------------ +# HIDDEN=5888 # headdim = 5888 / 46 = 128 +# ATEN_HEADS=46 +# ----------------- +# -- FLASH ATTN -- +# headdim = 5760 / 80 = 72 +# HIDDEN=5760 +# ATEN_HEADS=80 +# ------------ + +MODEL_25B_KEY="GPT25B" +A_NLAYERS[$MODEL_25B_KEY]=64 +A_HIDDEN[$MODEL_25B_KEY]=6144 +A_ATEN_HEADS[$MODEL_25B_KEY]=64 + +# ┏━━━━━━━━━━━━━━━━━━━┓ +# ┃ GPT-3: 30B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="30B" +# NLAYERS=64 +# HIDDEN=6144 +# ATEN_HEADS=64 + +# head size must be divisible by 8 (requirements of flash attention) +# head num must be divisible by sequence/tensor parallel size +MODEL_30B_KEY="GPT30B" +A_NLAYERS[$MODEL_30B_KEY]=64 +A_HIDDEN[$MODEL_30B_KEY]=6144 +A_ATEN_HEADS[$MODEL_30B_KEY]=64 + +# ┏━━━━━━━━━━━━━━━━━━━┓ +# ┃ GPT-3: 33B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="33B" +# NLAYERS=80 +# HIDDEN=5760 +# ATEN_HEADS=80 + +# MODEL_33B_KEY="GPT33B" +# A_NLAYERS[$MODEL_33B_KEY]=80 +# A_HIDDEN[$MODEL_33B_KEY]=5760 +# A_ATEN_HEADS[$MODEL_33B_KEY]=80 + +MODEL_33B_KEY="GPT33B" +A_NLAYERS[$MODEL_33B_KEY]=80 +A_HIDDEN[$MODEL_33B_KEY]=6144 +A_ATEN_HEADS[$MODEL_33B_KEY]=64 + +# ┏━━━━━━━━━━━━━━━━━━━━┓ +# ┃ GPT-3: 145B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="145B" +# NLAYERS=80 +# HIDDEN=12288 +# ATEN_HEADS=96 +# +GPT145B_HIDDEN=12288 +GPT145B_ATEN_HEADS=96 + +MODEL_145B_2L_KEY="GPT145B_2L" +A_NLAYERS[$MODEL_145B_2L_KEY]=2 +A_HIDDEN[$MODEL_145B_2L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_2L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_4L_KEY="GPT145B_4L" +A_NLAYERS[$MODEL_145B_4L_KEY]=4 +A_HIDDEN[$MODEL_145B_4L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_4L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_5L_KEY="GPT145B_5L" +A_NLAYERS[$MODEL_145B_5L_KEY]=5 +A_HIDDEN[$MODEL_145B_5L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_5L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_6L_KEY="GPT145B_6L" +A_NLAYERS[$MODEL_145B_6L_KEY]=6 +A_HIDDEN[$MODEL_145B_6L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_6L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_8L_KEY="GPT145B_8L" +A_NLAYERS[$MODEL_145B_8L_KEY]=8 +A_HIDDEN[$MODEL_145B_8L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_8L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_10L_KEY="GPT145B_10L" +A_NLAYERS[$MODEL_145B_10L_KEY]=10 +A_HIDDEN[$MODEL_145B_10L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_10L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_12L_KEY="GPT145B_12L" +A_NLAYERS[$MODEL_145B_12L_KEY]=12 +A_HIDDEN[$MODEL_145B_12L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_12L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_16L_KEY="GPT145B_16L" +A_NLAYERS[$MODEL_145B_16L_KEY]=16 +A_HIDDEN[$MODEL_145B_16L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_16L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_24L_KEY="GPT145B_24L" +A_NLAYERS[$MODEL_145B_24L_KEY]=24 +A_HIDDEN[$MODEL_145B_24L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_24L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_32L_KEY="GPT145B_32L" +A_NLAYERS[$MODEL_145B_32L_KEY]=32 +A_HIDDEN[$MODEL_145B_32L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_32L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_48L_KEY="GPT145B_48L" +A_NLAYERS[$MODEL_145B_48L_KEY]=48 +A_HIDDEN[$MODEL_145B_48L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_48L_KEY]="${GPT145B_ATEN_HEADS}" + +MODEL_145B_64L_KEY="GPT145B_64L" +A_NLAYERS[$MODEL_145B_64L_KEY]=64 +A_HIDDEN[$MODEL_145B_64L_KEY]="${GPT145B_HIDDEN}" +A_ATEN_HEADS[$MODEL_145B_64L_KEY]="${GPT145B_ATEN_HEADS}" + +# ┏━━━━━━━━━━━━━━━━━━━━┓ +# ┃ GPT-3: 175B Params ┃ +# ┗━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE="175B" +# NLAYERS=96 +# HIDDEN=12288 +# ATEN_HEADS=96 +# if [ -z "$NLAYERS" ]; then +# A_NLAYERS[$MODEL_145B_KEY]="${NLAYERS}" +# echo "Caught NLAYERS=${NLAYERS} from env, using this value!" +# else +# A_NLAYERS[$MODEL_145B_KEY]=80 +# echo "Using default NLAYERS=80" +# fi +MODEL_145B_KEY="GPT145B" +A_NLAYERS[$MODEL_145B_KEY]=80 +A_HIDDEN[$MODEL_145B_KEY]=12288 +A_ATEN_HEADS[$MODEL_145B_KEY]=96 + +export MODEL_SIZE="${MODEL_SIZE_KEY}" +export NLAYERS="${A_NLAYERS[$MODEL_SIZE_KEY]}" +export HIDDEN="${A_HIDDEN[$MODEL_SIZE_KEY]}" +export ATEN_HEADS="${A_ATEN_HEADS[$MODEL_SIZE_KEY]}" diff --git a/ALCF/mpi_wrapper b/ALCF/mpi_wrapper new file mode 100755 index 0000000000..770f950e1d --- /dev/null +++ b/ALCF/mpi_wrapper @@ -0,0 +1,27 @@ +#!/usr/bin/env bash + +set -e + +PYTHON=${PYTHON:-python3} + +MASTER_ADDR="$1" +MASTER_PORT="$2" +TRAINING_SCRIPT="$3" + +shift 3 + +test -n "${MASTER_ADDR}" -a -n "${MASTER_PORT}" -a -n "${OMPI_COMM_WORLD_RANK}" -a -n "${OMPI_COMM_WORLD_SIZE}" -a -n "${OMPI_COMM_WORLD_LOCAL_RANK}" +test -f "${TRAINING_SCRIPT}" + +set -x + +LOCAL_RANK=$((OMPI_COMM_WORLD_RANK % 8)) + +exec env \ + MASTER_ADDR="${MASTER_ADDR}" \ + MASTER_PORT="${MASTER_PORT}" \ + RANK="${OMPI_COMM_WORLD_RANK}" \ + WORLD_SIZE="${OMPI_COMM_WORLD_SIZE}" \ + ${PYTHON} -u "${TRAINING_SCRIPT}" "--local_rank=${LOCAL_RANK}" "$@" + +exit 1 diff --git a/ALCF/setup.sh b/ALCF/setup.sh new file mode 100755 index 0000000000..0b90daf02e --- /dev/null +++ b/ALCF/setup.sh @@ -0,0 +1,228 @@ +#!/bin/bash --login +# +# DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd -LP) +SOURCE=${BASH_SOURCE[0]} +while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink + DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) + SOURCE=$(readlink "$SOURCE") + [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located +done +DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +PARENT=$(dirname "${DIR}") + +export CUDA_DEVICE_MAX_CONNECTIONS=1 + +thetagpuMPI() { + NHOSTS=$(wc -l < "${COBALT_NODEFILE}") + NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) + NVME_PATH="/raid/scratch/" + MPI_COMMAND=$(which mpirun) + # export PATH="${CONDA_PREFIX}/bin:${PATH}" + MPI_DEFAULTS="\ + --hostfile ${HOSTFILE} \ + -x CFLAGS \ + -x LDFLAGS \ + -x http_proxy \ + -x PYTHONUSERBASE \ + -x https_proxy \ + -x PATH \ + -x CUDA_DEVICE_MAX_CONNECTIONS \ + -x LD_LIBRARY_PATH" + MPI_ELASTIC="\ + -n ${NGPUS} \ + -npernode ${NGPU_PER_HOST}" +} + +polarisMPI() { + NHOSTS=$(wc -l < "${PBS_NODEFILE}") + NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) + MPI_COMMAND=$(which mpiexec) + NVME_PATH="/local/scratch/" + MPI_DEFAULTS="\ + --envall \ + --verbose \ + --hostfile ${HOSTFILE}" + MPI_ELASTIC="\ + -n ${NGPUS} \ + --ppn ${NGPU_PER_HOST}" +} + +setupMPI() { + if [[ $(hostname) == theta* ]]; then + echo "Setting up MPI on ThetaGPU from $(hostname)" + thetagpuMPI + elif [[ $(hostname) == x* ]]; then + echo "Setting up MPI on Polaris from $(hostname)" + polarisMPI + else + echo "Unexpected hostname $(hostname)" + fi +} + +condaThetaGPU220701() { + module load conda/2022-07-01 ; conda activate base + conda activate \ + /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2022-07-01 + # if [[ -f "${PARENT}/.venvs/thetaGPU/2022-07-01-deepspeed/bin/activate" ]]; then + # echo "Found virtual environment!" + # source "${PARENT}/.venvs/thetaGPU/2022-07-01-deepspeed/bin/activate" + # fi +} + +condaThetaGPU230111() { + module load conda/2023-01-11 ; conda activate base +# conda activate \ +# /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2023-01-11-deepspeed + VENV_DIR="${PARENT}/venvs/thetaGPU/2023-01-11-deepspeed" + if [[ -d "${VENV_DIR}" ]] ; then + echo "Found venv at: ${VENV_DIR}" + # shellcheck source='../venvs/thetaGPU/2023-01-10/bin/activate' + source "${VENV_DIR}/bin/activate" + fi +} + +condaThetaGPU() { + module load conda/2022-07-01 ; conda activate base + conda activate \ + /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2022-07-01 + echo "USING PYTHON: $(which python3)" +} + +condaThetaGPU_mtanaka() { + # module load conda/2023-01-11 ; conda activate base + # conda activate \ + # /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2023-01-11-deepspeed + VENV_DIR="/lus/grand/projects/datascience/mtanaka/dsseq/venv/dsseq" + if [[ -d "${VENV_DIR}" ]] ; then + echo "Found venv at: ${VENV_DIR}" + # shellcheck source='../venvs/thetaGPU/2023-01-10/bin/activate' + source "${VENV_DIR}/bin/activate" + fi +} + +condaPolaris220908() { + echo "Loading: 'module load conda 2022-09-08 ; conda activate base'" + module load conda/2022-09-08 ; conda activate base + conda activate /lus/grand/projects/datascience/foremans/locations/polaris/miniconda3/envs/2022-09-08-deepspeed + export CFLAGS="-I${CONDA_PREFIX}/include" + export LDFLAGS="-L${CONDA_PREFIX}/lib" + VENV_DIR="${PARENT}/venvs/polaris/2022-09-08" + if [[ -d "${VENV_DIR}" ]]; then + echo "Found venv at: ${VENV_DIR}" + source "${VENV_DIR}/bin/activate" + fi +} + +condaPolaris230110() { + echo "Loading: 'module load conda 2023-01-10-unstable ; conda activate base'" + module load conda/2023-01-10-unstable ; conda activate base + export CFLAGS="-I${CONDA_PREFIX}/include" + export LDFLAGS="-L${CONDA_PREFIX}/lib" + # conda activate \ + # /lus/grand/projects/datascience/foremans/locations/polaris/miniconda3/envs/2023-01-10 + VENV_DIR="${PARENT}/venvs/polaris/2023-01-10/" + if [[ -d "${VENV_DIR}" ]]; then + echo "Found venv at: ${VENV_DIR}" + # shellcheck source=../venvs/polaris/2023-01-10/bin/activate + source "${VENV_DIR}/bin/activate" + fi +} + +condaThetaGPU230426() { + echo "Loading: 'module load conda 2023-01-10-unstable ; conda activate base'" + module load conda/2023-01-11 + conda activate base + conda activate /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2023-04-26 + VENV_DIR="${PARENT}/venvs/thetaGPU/2023-04-26/" + if [[ -d "${VENV_DIR}" ]]; then + echo "Found venv at: ${VENV_DIR}" + # shellcheck source=../venvs/thetaGPU/2023-04-26/ + source "${VENV_DIR}/bin/activate" + fi + thetagpuMPI + export CFLAGS="-I${CONDA_PREFIX}/include" + export LDFLAGS="-L${CONDA_PREFIX}/lib" +} + +condaPolaris() { + condaPolaris230110 + echo "USING PYTHON: $(which python3)" +} + +# ┏━━━━━━━━━━┓ +# ┃ ThetaGPU ┃ +# ┗━━━━━━━━━━┛ +setupThetaGPU() { + if [[ $(hostname) == theta* ]]; then + export MACHINE="ThetaGPU" + HOSTFILE="${COBALT_NODEFILE}" + # -- Python / Conda setup ------------------------------------------------- + thetagpuMPI + condaThetaGPU230426 + else + echo "Unexpected hostname: $(hostname)" + fi +} + +# ┏━━━━━━━━━┓ +# ┃ Polaris ┃ +# ┗━━━━━━━━━┛ +setupPolaris() { + if [[ $(hostname) == x* ]]; then + export MACHINE="Polaris" + HOSTFILE="${PBS_NODEFILE}" + # -- MPI / Comms Setup ---------------------------------------------------- + condaPolaris + polarisMPI + # export IBV_FORK_SAFE=1 + else + echo "Unexpected hostname: $(hostname)" + fi +} + +# ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +# ┃ SETUP CONDA + MPI ENVIRONMENT @ ALCF ┃ +# ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +setup() { + # unset PYTHONUSERBASE + export NCCL_DEBUG=warn + export WANDB_CACHE_DIR="./cache/wandb" + CFLAGS="-I${CONDA_PREFIX}/include/" + LDFLAGS="-L${CONDA_PREFIX}/lib/" + # export CFLAGS="${CFLAGS}" + # export LDFLAGS="${LDFLAGS}" + # export PATH="${CONDA_PREFIX}/bin:${PATH}" + + export NVME_PATH="${NVME_PATH}" + export MPI_DEFAULTS="${MPI_DEFAULTS}" + export MPI_ELASTIC="${MPI_ELASTIC}" + export MPI_COMMAND="${MPI_COMMAND}" + + PYTHON_EXECUTABLE="$(which python3)" + export PYTHON_EXECUTABLE="${PYTHON_EXECUTABLE}" + echo "USING PYTHON: $(which python3)" + echo "CFLAGS: ${CFLAGS}" + echo "LDFLAGS: ${LDFLAGS}" + # source "${DIR}/args.sh" + + if [[ $(hostname) == theta* ]]; then + echo "Setting up ThetaGPU from $(hostname)" + setupThetaGPU + elif [[ $(hostname) == x* ]]; then + echo "Setting up Polaris from $(hostname)" + setupPolaris + else + echo "Unexpected hostname $(hostname)" + fi + export NODE_RANK=0 + # export RANK=0 + export NNODES=$NHOSTS + export GPUS_PER_NODE=$NGPU_PER_HOST + export WORLD_SIZE=$NGPUS + export NGPUS="${NGPUS}" + export NHOSTS="${NHOSTS}" + export NGPU_PER_HOST="${NGPU_PER_HOST}" + export CUDA_DEVICE_MAX_CONNECTIONS=1 +} diff --git a/ALCF/submit-pbs.sh b/ALCF/submit-pbs.sh new file mode 100755 index 0000000000..712a932656 --- /dev/null +++ b/ALCF/submit-pbs.sh @@ -0,0 +1,263 @@ +#!/bin/bash --login +# + +cd "${PBS_O_WORKDIR}" || exit + +# cd "${PBS_O_WORKDIR}" +# +# echo "PBS_O_WORKDIR: ${PBS_O_WORKDIR}" +# +# echo "__________________________________________________________________________________" +# cd ~/datascience/foremans/locations/polaris/projects/saforem2/Megatron-DS-Benchmarking/ +# echo "pwd: $(pwd)" +# echo "__________________________________________________________________________________" + +# SOURCE=${BASH_SOURCE[0]} +# while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink +# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +# SOURCE=$(readlink "$SOURCE") +# [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located +# done +# DIR="$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd )" + +# HERE=$(python3 -c 'import os; print(os.getcwd())') +# ALCF_DIR="${HERE}/ALCF" + +ALCF_DIR="$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1)))/ALCF" +PARENT=$(dirname "${ALCF_DIR}") +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" +echo "ALCF_DIR: ${ALCF_DIR}" +echo "PARENT: ${PARENT}" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" + + +TSTAMP=$(tstamp) +echo "┌──────────────────────────────────────────────────────────────────┐" +#####"│ Job Started at 2023-08-04-121535 on polaris-login-04 by foremans │" +echo "│ Job Started at ${TSTAMP} on $(hostname) by $USER │" +echo "│ in: ${PARENT}" +echo "└──────────────────────────────────────────────────────────────────┘" +# echo "------------------------------------------------------------------------" + +getValFromFile() { + FILE=$1 + KEY=$2 + echo "getting ${KEY} from ${FILE}" + if [[ -f "${FILE}" ]]; then + VAL="$(cat "${FILE}" | grep -E "^${KEY}=" | sed "s/${KEY}=//g" | sed 's/\"//g')" + echo "setting ${KEY}: ${VAL}" + export "${KEY}"="${VAL}" + fi +} + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source="${FILE}" + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi +} +# +# sourceFile "${DIR}/setup.sh" +# sourceFile "${DIR}/model.sh" +# sourceFile "${DIR}/args.sh" +# sourceFile "${DIR}/launch.sh" +# +# export USE_ACTIVATION_CHECKPOINTING=1 # 1 | 0 +# export SEQ_LEN=${SEQ_LEN:-1024} +# export MPSIZE=${MPSIZE:-1} +# export PPSIZE=${PPSIZE:-1} +# export SPSIZE=${SPSIZE:-1} +# export MICRO_BATCH=${MICRO_BATCH:-1} +# export ZERO_STAGE=${ZERO_STAGE:-1} # 0 | 1 | 2 | 3 +# export NHOSTS="$NHOSTS" +# export GRADIENT_ACCUMULATION_STEPS=${GAS:-1} +# export USE_SEQUENCE_PARALLEL=${USE_SEQUENCE_PARALLEL:-0} # 1 | 0 +# +# +# export MODEL_SIZE_KEY="GPT1_5B" +# export SEQ_LEN=1024 +# export USE_FLASH_ATTN=1 +# export MICRO_BATCH=4 +# export WORLD_SIZE=8 +# export SP_TYPE="ds" +# export SPSIZE=8 +# export PPSIZE=1 +# export MPSIZE=1 +# export ZERO_STAGE=3 +# export USE_SEQUENCE_PARALLEL=0 + + +# getValFromFile "${DIR}/model.sh" MODEL_SIZE +# getValFromFile "${DIR}/args.sh" PPSIZE +# getValFromFile "${DIR}/args.sh" MPSIZE +# getValFromFile "${DIR}/args.sh" MICRO_BATCH +# getValFromFile "${DIR}/args.sh" GRADIENT_ACCUMULATION_STEPS +# +# MODEL_SIZE="${MODEL_SIZE}" +# PPSIZE="${PPSIZE}" +# MPSIZE="${MPSIZE}" +# MICRO_BATCH="${MICRO_BATCH}" +# GRADIENT_ACCUMULATION_STEPS="${GRADIENT_ACCUMULATION_STEPS}" + +QUEUE=$1 +NUM_NODES=$2 +DURATION=$3 +PROJECT=$4 + +# MODEL_SIZE_KEY=$5 +# SEQ_LEN=$6 +# USE_FLASH_ATTN=$7 +# MICRO_BATCH=$8 +# GAS=$9 +# SP_TYPE=$10 + +# MODEL_SIZE_KEY="GPT6_7B" SEQ_LEN=2048 USE_FLASH_ATTN=0 MICRO_BATCH=1 GAS=1 SP_TYPE="deepspeed" ./ALCF/submit-pbs.sh debug-scaling 4 00:30:00 datascience + +# export MICRO_BATCH=${MICRO_BATCH:-1} +# export MICRO_BATCH="${MICRO_BATCH}" +# export MODEL_SIZE="${MODEL_SIZE}" +# # export GAS="${GRADIENT_ACCUMULATION_STEPS}" +# export GRADIENT_ACCUMULATION_STEPS=${GAS:-1} +# +# export DDP_IMPL="local" # FSDP | local | torch +# # export USE_FLASH_ATTN=${USE_FLASH_ATTN:-0} # 1 | 0 +# # export USE_ACTIVATION_CHECKPOINTING=1 # 1 | 0 +# export SEQ_LEN=${SEQ_LEN:-1024} +# # export MPSIZE=${MPSIZE:-1} +# export PPSIZE=${PPSIZE:-1} +# export SPSIZE=${SPSIZE:-1} +# export MICRO_BATCH=${MICRO_BATCH:-1} +# export ZERO_STAGE=${ZERO_STAGE:-1} # 0 | 1 | 2 | 3 +# # export NHOSTS="$NHOSTS" +# export GRADIENT_ACCUMULATION_STEPS=${GAS:-1} +# export USE_SEQUENCE_PARALLEL=${USE_SEQUENCE_PARALLEL:-0} # 1 | 0 +# + +if [ -z "${MODEL_SIZE_KEY}" ]; then + echo "ERROR: MODEL_SIZE_KEY not set" + exit 1 +fi + +if [ -z "${SEQ_LEN}" ]; then + echo "ERROR: SEQ_LEN not set" + echo "Using default SEQ_LEN=2048" + echo "Set SEQ_LEN=XXXX to change" + SEQ_LEN=2048 +fi + +if [ -z "${USE_FLASH_ATTN}" ]; then + echo "ERROR: USE_FLASH_ATTN not set" + echo "Not using flash attn! Set USE_FLASH_ATTN=1 to use" + USE_FLASH_ATTN=0 +fi + +if [ -z "${MICRO_BATCH}" ]; then + echo "ERROR: MICRO_BATCH not set" + echo "Using MICRO_BATCH=1" + MICRO_BATCH=1 +fi + +if [ -z "${GAS}" ]; then + echo "ERROR: GAS not set" + echo "Using GAS=1" + GAS=1 +fi + +if [ -z "${SP_TYPE}" ]; then + echo "ERROR: SP_TYPE not set" + echo "Using SP_TYPE=megatron" + SP_TYPE="megatron" +fi + +export GAS="${GAS}" +export SEQ_LEN="${SEQ_LEN}" +export SP_TYPE="${SP_TYPE}" +export MICRO_BATCH="${MICRO_BATCH}" +export MODEL_SIZE_KEY="${MODEL_SIZE_KEY}" +export USE_FLASH_ATTN="${USE_FLASH_ATTN}" + +echo "-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-" +echo "| MODEL_SIZE_KEY: ${MODEL_SIZE_KEY}" +echo "| SEQ_LEN: ${SEQ_LEN}" +echo "| USE_FLASH_ATTN: ${USE_FLASH_ATTN}" +echo "| MICRO_BATCH: ${MICRO_BATCH}" +echo "| GAS: ${GAS}" +echo "| SP_TYPE: ${SP_TYPE}" +echo "-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-" + +export QUEUE="${QUEUE}" +export DURATION="${DURATION}" +export TSTAMP="${TSTAMP}" +export NUM_NODES="${NUM_NODES}" +export PROJECT="${PROJECT}" + +RUN_NAME="N${NUM_NODES}-${TSTAMP}" +# RUN_NAME="mb${MICRO_BATCH}-gas${GAS}-${RUN_NAME}" +# RUN_NAME="GPT3-${MODEL_SIZE}-${RUN_NAME}" +RUN_NAME="${MODEL_SIZE_KEY}-${SP_TYPE}-mb${MICRO_BATCH}-gas${GAS}-seqlen${SEQ_LEN}-${RUN_NAME}" +export RUN_NAME="${RUN_NAME}" + +echo "QUEUE=$QUEUE" +echo "PROJECT=$PROJECT" +echo "DURATION=$DURATION" +echo "TSTAMP=$TSTAMP" +echo "NUM_NODES=$NUM_NODES" +echo "RUN_NAME: ${RUN_NAME}" +# echo "MODEL_SIZE=$MODEL_SIZE" +# echo "GAS=$GRADIENT_ACCUMULATION_STEPS" + +# QSUB_ARGS=( +# "-q ${QUEUE}" +# "-A ${PROJECT}" +# "-N ${RUN_NAME}" +# "-l select=${NUM_NODES}" +# "-l walltime=${DURATION}" +# "-l filesystems=eagle:home:grand" +# "${DIR}/submit.sh" +# ) + +OUTPUT=$(qsub \ + -q "${QUEUE}" \ + -A "${PROJECT}" \ + -N "${RUN_NAME}" \ + -l select="${NUM_NODES}" \ + -l walltime="${DURATION}" \ + -l filesystems=eagle:home:grand \ + "${ALCF_DIR}/submit.sh") + +# OUTPUT=$(qsub "${QSUB_ARGS[@]}") + +PBS_JOBID=$(echo "${OUTPUT}" | cut --delimiter="." --fields=1) +export PBS_JOBID="${PBS_JOBID}" +# echo "${TSTAMP} ${PBS_JOBID} " + +PBS_JOBSTR=( + "PBS_JOBID=${PBS_JOBID}" + "QUEUE=$QUEUE" + "PROJECT=$PROJECT" + "DURATION=$DURATION" + "TSTAMP=$TSTAMP" + "NUM_NODES=$NUM_NODES" + # "MODEL_SIZE=$MODEL_SIZE" + "RUN_NAME: ${RUN_NAME}" +) + # "GAS=$GRADIENT_ACCUMULATION_STEPS" + +TODAY=$(echo "${TSTAMP}" | cut --delimiter="-" --fields=1,2,3) +OUTFILE="${PARENT}/pbslogs/${TODAY}/${PBS_JOBID}.txt" + +if [[ ! -d $(dirname "${OUTFILE}") ]]; then + mkdir -p "$(dirname "${OUTFILE}")" +fi + +echo "Writing PBS_JOBSTR to ${OUTFILE}" +echo "${PBS_JOBSTR[@]}" >> "${OUTFILE}" +# echo "${PBS_JOBSTR[@]}" | tee -a "${OUTFILE}" + +echo "┌───────────────────────────────────────────┐" +echo "│ To view job output, run: \`pbstail ${PBS_JOBID}\` │" +echo "└───────────────────────────────────────────┘" diff --git a/ALCF/submit.sh b/ALCF/submit.sh new file mode 100755 index 0000000000..cc308b5be5 --- /dev/null +++ b/ALCF/submit.sh @@ -0,0 +1,66 @@ +#!/bin/bash --login +#PBS -V +# +cd "${PBS_O_WORKDIR}" || exit + +TSTAMP=$(date "+%Y-%m-%d-%H%M%S") +export TSTAMP="$TSTAMP" + +ALCF_DIR="$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1)))/ALCF" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" +echo "ALCF_DIR: ${ALCF_DIR}" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" + +# SOURCE=${BASH_SOURCE[0]} +# while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink +# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +# SOURCE=$(readlink "$SOURCE") +# [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located +# done +# DIR="$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd )" + +#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +#┃ Make sure we're not already running; if so, exit here ┃ +#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +PIDS=$(ps aux | grep pretrain_gpt.py | grep -v grep | awk '{print $2}') +if [ -n "${PIDS}" ]; then + echo "Already running! Exiting!" + exit 1 +fi + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source="${FILE}" + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi +} + +#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +#┃ source ./launch.sh ┃ +#┃ which then sources ./{args.sh,setup.sh} ┃ +#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +# SCRIPT_DIR="/lus/grand/projects/datascience/foremans/locations/polaris/projects/saforem2/Megatron-DS-Benchmarking/ALCF/" +MODEL_FILE="${ALCF_DIR}/model.sh" +ARGS_FILE="${ALCF_DIR}/args.sh" +LAUNCH_FILE="${ALCF_DIR}/launch.sh" +SETUP_FILE="${ALCF_DIR}/setup.sh" + +sourceFile "${SETUP_FILE}" +sourceFile "${ARGS_FILE}" +sourceFile "${MODEL_FILE}" +sourceFile "${LAUNCH_FILE}" +# if [[ -f "${LAUNCH_FILE}" ]]; then +# echo "source-ing ${LAUNCH_FILE}" +# # shellcheck source=./launch.sh +# source "${LAUNCH_FILE}" +# else +# echo "ERROR: UNABLE TO SOURCE ${LAUNCH_FILE}" +# fi + +setup +elasticDistributed "$@" +wait $! diff --git a/ALCF/sweep_args_theta_multinode.sh b/ALCF/sweep_args_theta_multinode.sh new file mode 100755 index 0000000000..ac6409233a --- /dev/null +++ b/ALCF/sweep_args_theta_multinode.sh @@ -0,0 +1,164 @@ +#!/bin/bash -l + +module load conda/2023-01-11 +conda activate base +# cd /home/czh5/seq/Megatron-DS-Benchmarking/ALCF +# source /home/czh5/seq/Megatron-DS-Benchmarking/venvs/thetaGPU/2023-01-11-deepspeed/bin/activate + +# rm -rf /home/czh5/genome/Megatron-DeepSpeed/dataset/*.npy +# rm -rf /home/czh5/genome/Megatron-DeepSpeed/dataset/*.done +# +SCRIPT_PATH="${BASH_SOURCE[0]}" +while [ -L "$SCRIPT_PATH" ]; do + SCRIPT_DIR="$(cd -P "$(dirname "$SCRIPT_PATH")" >/dev/null 2>&1 && pwd)" + SCRIPT_PATH="$(readlink "$SCRIPT_PATH")" + [[ ${SCRIPT_PATH} != /* ]] && SCRIPT_PATH="${SCRIPT_DIR}/${SCRIPT_PATH}" +done +SCRIPT_PATH="$(readlink -f "$SCRIPT_PATH")" +SCRIPT_DIR="$(cd -P "$(dirname -- "$SCRIPT_PATH")" >/dev/null 2>&1 && pwd)" + +SOURCE=${BASH_SOURCE[0]} +while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink + DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) + SOURCE=$(readlink "$SOURCE") + [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located +done +DIR="$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd )" + + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source="${FILE}" + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi +} + +SETUP_FILE="${DIR}/setup.sh" +MODEL_FILE="${DIR}/model.sh" +ARGS_FILE="${DIR}/args.sh" +LAUNCH_FILE="${DIR}/launch.sh" + + +sourceFile "${SETUP_FILE}" +sourceFile "${MODEL_FILE}" +sourceFile "${ARGS_FILE}" +sourceFile "${LAUNCH_FILE}" + +SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) +echo "My current script is: ${SCRIPT_DIR[0]}" + + +if [[ $(hostname) == theta* ]]; then + HOSTFILE="${COBALT_NODEFILE}" +elif [[ $(hostname) == x* ]]; then + HOSTFILE="${PBS_NODEFILE}" +else + echo "Unexpected hostname $(hostname)" +fi + +echo "Found hostfile: ${HOSTFILE}" + +NHOSTS=$(wc -l < "${HOSTFILE}") +NGPU_PER_HOST=$(nvidia-smi -L | wc -l) +PARALLEL_SIZE=$(( NHOSTS * NGPU_PER_HOST )) + +export MODEL_TYPE=${MODEL_TYPE:-"gpt"} # set bert or gpt +export SP_TYPE=${SP_TYPE:-"megatron"} # set ds or megatron + +K_VALS=( + # 2 + # 4 + 8 + # 16 + # 32 + # 64 + # 128 + # 192 + # 256 + # 272 + # 320 + # 384 + # 448 + # 512 + # 1024 +) + +SEQLEN_VALS=( +# 2048 +# 4096 +# 8192 +# 16384 +# 32768 +# 65536 +# 131072 +# 262144 +# 524288 +# 1048576 +# 2097152 +) + +MODEL_SIZE_VALS=( + # "GPT125M" + # "BERT1.2B" +# "GPT1_5B" + # "GPT2_7B" +# "GPT6_7B" + # "GPT13B" + "GPT25B" +# "GPT30B" +# "GPT33B" +) + +for MODEL_SIZE_KEY in "${MODEL_SIZE_VALS[@]}"; do + export MODEL_SIZE_KEY +# for SEQ_LEN in "${SEQLEN_VALS[@]}"; do +# export SEQ_LEN + for NUM_K in "${K_VALS[@]}"; do + # common_factor=$(( $PARALLEL_SIZE * 8 )) + # export SEQ_LEN=$(( 1024 * $NUM_K / $common_factor * $common_factor )) + + export SEQ_LEN=$(( 1024 * $NUM_K )) + + if [[ ${SP_TYPE} == "ds" ]]; then + echo "DS sequence parallel" + export SPSIZE=${PARALLEL_SIZE} + export MPSIZE=1 + export ZERO_STAGE=3 + export USE_SEQUENCE_PARALLEL=0 + bash ./benchmark_train.sh + fi + + if [[ ${SP_TYPE} == "megatron" ]]; then + echo "Megatron's sequence parallel" + + # if [ ${SEQ_LEN} -eq 8192 ]; then + # PARALLEL_SIZE=8 + # fi + + # if [ ${SEQ_LEN} -eq 16384 ]; then + # PARALLEL_SIZE=8 + # fi + + # if [ ${SEQ_LEN} -eq 32768 ]; then + # PARALLEL_SIZE=16 + # fi + + # if [ ${SEQ_LEN} -eq 65536 ]; then + # PARALLEL_SIZE=16 + # fi + + export SPSIZE=1 + export MPSIZE=${PARALLEL_SIZE} + export ZERO_STAGE=0 + export USE_SEQUENCE_PARALLEL=1 + bash ./benchmark_train.sh + fi + + printf "\n------------------------" + echo SEQ_LEN=${SEQ_LEN} + done +done diff --git a/ALCF/train-gpt3.sh b/ALCF/train-gpt3.sh new file mode 100755 index 0000000000..fa707b5df4 --- /dev/null +++ b/ALCF/train-gpt3.sh @@ -0,0 +1,71 @@ +#!/bin/bash --login + +TSTAMP=$(date "+%Y-%m-%d-%H%M%S") + +# HERE=$(python3 -c 'import os; print(os.getcwd())') +# ALCF_DIR="${HERE}/ALCF" +# +function WhereAmI() { + python3 -c 'import os; print(os.getcwd())' +} + +HERE=$(WhereAmI) +ALCF_DIR=$(find "${HERE}" -name "ALCF") + + +# ALCF_DIR="$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1)))/ALCF" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" +echo "ALCF_DIR: ${ALCF_DIR}" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" + +# SOURCE=${BASH_SOURCE[0]} +# while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink +# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +# SOURCE=$(readlink "$SOURCE") +# [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located +# done +# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +# + +#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +#┃ Make sure we're not already running; if so, exit here ┃ +#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +PIDS=$(ps aux | grep pretrain_gpt.py | grep -v grep | awk '{print $2}') +if [ -n "${PIDS}" ]; then + echo "Already running! Exiting!" + exit 1 +fi + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source="${FILE}" + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi +} + +#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +#┃ source ./launch.sh ┃ +#┃ which then sources ./{args.sh,setup.sh} ┃ +#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +LAUNCH_FILE="${ALCF_DIR}/launch.sh" + +sourceFile "${ALCF_DIR}/setup.sh" +sourceFile "${ALCF_DIR}/model.sh" +sourceFile "${ALCF_DIR}/args.sh" +sourceFile "${LAUNCH_FILE}" + +setup +# singleGPU "$@" 2>&1 & +# fullNode "$@" 2>&1 & +TORCH_VERSION=$(python3 -c 'import torch; print(torch.__version__)') +export TORCH_VERSION=$TORCH_VERSION +export CUDA_DEVICE_MAX_CONNECTIONS=1 +# elasticDistributed "$@" 2>&1 & +# elasticDistributed "$@" +# PID=$! +# wait $PID +elasticDistributed "$@" 2>&1 & From 2a03c730baa8375a40b037699969ffc16a8bd69d Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 3 Oct 2023 21:46:28 -0500 Subject: [PATCH 002/268] Update `ALCF/*` --- ALCF/args.sh | 767 ++++++++++++----------------- ALCF/benchmark_train.sh | 82 --- ALCF/launch.sh | 234 +++++---- ALCF/model.sh | 22 + ALCF/mpi_wrapper | 27 - ALCF/setup.sh | 408 +++++++-------- ALCF/sweep_args_theta_multinode.sh | 164 ------ ALCF/train-gpt3.sh | 5 +- 8 files changed, 665 insertions(+), 1044 deletions(-) delete mode 100755 ALCF/benchmark_train.sh delete mode 100755 ALCF/mpi_wrapper delete mode 100755 ALCF/sweep_args_theta_multinode.sh diff --git a/ALCF/args.sh b/ALCF/args.sh index f452d3b7aa..200fd21fc9 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -1,90 +1,45 @@ -#!/bin/bash -login - -# SCRIPT_PATH="${BASH_SOURCE[0]}" -# while [ -L "$SCRIPT_PATH" ]; do -# SCRIPT_DIR="$(cd -P "$(dirname "$SCRIPT_PATH")" >/dev/null 2>&1 && pwd)" -# SCRIPT_PATH="$(readlink "$SCRIPT_PATH")" -# [[ ${SCRIPT_PATH} != /* ]] && SCRIPT_PATH="${SCRIPT_DIR}/${SCRIPT_PATH}" -# done -# SCRIPT_PATH="$(readlink -f "$SCRIPT_PATH")" -# SCRIPT_DIR="$(cd -P "$(dirname -- "$SCRIPT_PATH")" >/dev/null 2>&1 && pwd)" -# -# SOURCE=${BASH_SOURCE[0]} -# while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink -# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) -# SOURCE=$(readlink "$SOURCE") -# [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located -# done -# DIR="$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd )" +#!/bin/bash --login function FindMegatron() { - MEGATRON_INSTALL=$(python3 -c 'import megatron; print(megatron.__file__)' | tail -1) - MEGATRON_DIR=$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1))) + MEGATRON_INSTALL=$(python3 -c 'import megatron; print(megatron.__file__)' | tail -1) + MEGATRON_DIR=$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1))) } function WhereAmI() { - python3 -c 'import os; print(os.getcwd())' + python3 -c 'import os; print(os.getcwd())' +} + +function join_by { local d=${1-} f=${2-}; if shift 2; then printf %s "$f" "${@/#/$d}"; fi; } + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source="${FILE}" + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi } -HERE=$(WhereAmI) -ALCF_DIR=$(find "${HERE}" -name "ALCF") -# [ "${MEGATRON_DIR}" ] && echo "Caught ${MEGATRON_DIR} from env" || FindMegatron -# ALCF_DIR="${MEGATRON_DIR}/ALCF" -# ALCF_DIR="$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1)))/ALCF" +USER=$(whoami) +HERE=$(WhereAmI) +ALCF_DIR="${HERE}/ALCF" PARENT=$(dirname "${ALCF_DIR}") echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" echo "ALCF_DIR: ${ALCF_DIR}" echo "PARENT: ${PARENT}" echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" -function sourceFile() { - FILE="$1" - echo "source-ing ${FILE}" - if [[ -f "${FILE}" ]]; then - # shellcheck source="${FILE}" - source "${FILE}" - else - echo "ERROR: UNABLE TO SOURCE ${FILE}" - fi -} - -USER=$(whoami) -# # DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd -LP) -# PARENT=$(dirname "$DIR") -# -# HERE=$(python3 -c 'import os; print(os.getcwd())') - -# echo "------------------------" -# echo "SCRIPT_DIR=$SCRIPT_DIR" -# echo "SCRIPT_PATH=$SCRIPT_PATH" -# echo "------------------------" -# echo "SOURCE=$SOURCE" -# echo "DIR=$DIR" -# echo "PARENT: ${PARENT}" -# echo "HERE: ${HERE}" -# echo "------------------------" - -if [[ $(hostname) == theta* ]]; then - echo "Setting up ThetaGPU from $(hostname)" - HOSTFILE="${COBALT_NODEFILE}" -elif [[ $(hostname) == x* ]]; then - echo "Setting up Polaris from $(hostname)" - HOSTFILE="${PBS_NODEFILE}" -else - echo "Unexpected hostname $(hostname)" -fi +HOSTNAME=$(hostname) +sourceFile "${ALCF_DIR}/setup.sh" -NHOSTS=$(wc -l < "${HOSTFILE}") -NGPU_PER_HOST=$(nvidia-smi -L | wc -l) -NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" WORLD_SIZE="${NGPUS}" PARALLEL_SIZE="${WORLD_SIZE}" -# # NGPUS="$((${NHOSTS}*${NGPU_PER_HOST}))" echo "NHOSTS * (NGPU / HOST) = $NHOSTS * $NGPU_PER_HOST = $NGPUS" - export MODEL_SIZE_KEY="${MODEL_SIZE_KEY:-GPT13B}" echo "==========================+" echo "Using ${MODEL_SIZE_KEY}" @@ -97,30 +52,12 @@ MODEL_TYPE=${MODEL_TYPE:-gpt} # ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ # ┃ Model Parallel / Pipeline Parallel ┃ # ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ -# ---------- -# Originals -# MPSIZE=8 -# PPSIZE=16 -# ---------- -# NHOSTS=$(wc -l < "${PBS_NODEFILE}") export DDP_IMPL="local" # FSDP | local | torch -export USE_FLASH_ATTN=${USE_FLASH_ATTN:-0} # 1 | 0 export USE_ACTIVATION_CHECKPOINTING=1 # 1 | 0 export SEQ_LEN=${SEQ_LEN:-2048} export PPSIZE=${PPSIZE:-1} -# export MPSIZE=${MPSIZE:-1} -# export SPSIZE=${SPSIZE:-1} export MICRO_BATCH=${MICRO_BATCH:-1} -# export ZERO_STAGE=${ZERO_STAGE:-1} # 0 | 1 | 2 | 3 export GRADIENT_ACCUMULATION_STEPS=${GAS:-1} -# export NHOSTS="$NHOSTS" -# export USE_SEQUENCE_PARALLEL=${USE_SEQUENCE_PARALLEL:-0} # 1 | 0 - -# NHOSTS=$(wc -l < "${COBALT_NODEFILE}") -# # NGPU_PER_HOST=8 -# NGPU_PER_HOST=$(nvidia-smi -L | wc -l) -# PARALLEL_SIZE=$((${NHOSTS}*${NGPU_PER_HOST})) - export MODEL_TYPE=${MODEL_TYPE:-"gpt"} # set bert or gpt export SP_TYPE=${SP_TYPE:-"megatron"} # set ds or megatron @@ -128,115 +65,76 @@ export SP_TYPE=${SP_TYPE:-"megatron"} # set ds or megatron # Deal with Sequence Parallel implementation --------------------------------------- # ---------------------------------------------------------------------------------- if [[ ${SP_TYPE} == "ds" ]]; then - # NOTE: -------------------------------------------------------------------------- - # SP_TYPE="ds" has NO effect, essentially running with no Seq. || - # -------------------------------------------------------------------------------- - USE_SEQUENCE_PARALLEL=0 - if [[ "$MPSIZE" == "${WORLD_SIZE}" ]]; then - echo "Caught MPSIZE: $MPSIZE from env. Setting SPSIZE=1" - SPSIZE=1 - MPSIZE="${MPSIZE}" - else - echo "Didn't catch MPSIZE from env. Setting SPSIZE=${WORLD_SIZE}, MPSIZE=1" - MPSIZE=1 - SPSIZE="${WORLD_SIZE}" - fi - # if [[ "$MPSIZE" != 0 ]]; then - # SPSIZE=$(( WORLD_SIZE - MPSIZE )) - # echo "############################################################" - # echo "Caught MPSIZE: $MPSIZE from env!" - # echo "Setting SPSIZE: (${WORLD_SIZE} - ${MPSIZE}) = ${SPSIZE}" - # echo "############################################################" - # else - # MPSIZE=1 - # SPSIZE="$WORLD_SIZE" - # echo "############################################################" - # echo "Setting MPSIZE: $SPSIZE, SPSIZE: $WORLD_SIZE = $SPSIZE" - # echo "############################################################" - # fi - # [ "$MPSIZE" ] && SPSIZE=1 || SPSIZE="${WORLD_SIZE}" - # [ "$SPSIZE" ] && MPSIZE=1 || MPSIZE="${}" - # [ "$MPSIZE" = "$WORLD_SIZE" ] && SPSIZE=1 || SPSIZE="$WORLD_SIZE" - # [ "$SPSIZE" = "$WORLD_SIZE" ] && MPSIZE=1 || MPSIZE="${WORLD_SIZE}" - # export SPSIZE="${WORLD_SIZE}" - export SPSIZE="${SPSIZE:-$WORLD_SIZE}" - export MPSIZE="${MPSIZE:-1}" - export USE_SEQUENCE_PARALLEL=0 - if [ -z "${ZERO_STAGE}" ]; then - echo "ZERO_STAGE not set, setting to 3 for ${SP_TYPE}" - ZERO_STAGE=3 - else - echo "Caught ZERO_STAGE=${ZERO_STAGE} with ${SP_TYPE}" - fi - export ZERO_STAGE="${ZERO_STAGE}" + # NOTE: -------------------------------------------------------------------- + # SP_TYPE="ds" has NO effect, essentially running with no Seq. parallelism + # -------------------------------------------------------------------------- + if [[ "$MPSIZE" == "${WORLD_SIZE}" ]]; then + # hacky workaround to try and use SP_TYPE="ds" + MPSIZE="${WORLD_SIZE}" + # ------------------------------------------------------------------------ + # Update [2023-08-22]: Chengming mentioned that this is an internal issue + # and will NOT work currently + # ------------------------------------------------------------------------ + echo "Caught MPSIZE: $MPSIZE from env. Setting SPSIZE=1" + SPSIZE=1 + MPSIZE="${MPSIZE}" + else + echo "Didn't catch MPSIZE from env. Setting SPSIZE=${WORLD_SIZE}, MPSIZE=1" + MPSIZE=1 + SPSIZE="${WORLD_SIZE}" + fi + if [ -z "${ZERO_STAGE}" ]; then + echo "ZERO_STAGE not set, setting to 3 for ${SP_TYPE}" + ZERO_STAGE=3 + else + echo "Caught ZERO_STAGE=${ZERO_STAGE} with ${SP_TYPE}" + fi + export SPSIZE="${SPSIZE:-$WORLD_SIZE}" + export MPSIZE="${MPSIZE:-1}" + export USE_SEQUENCE_PARALLEL=0 + export ZERO_STAGE="${ZERO_STAGE}" elif [[ ${SP_TYPE} == "megatron" ]]; then - # NOTE: -------------------------------------------------------------------------- - # SP_TYPE="megatron" will use Megatron's Seq. || implementation with ZERO_STAGE=0 - # -------------------------------------------------------------------------------- - # export SPSIZE=1 - # export MPSIZE="${WORLD_SIZE}" - [ "$SPSIZE" ] && echo "Caught SPSIZE: ${SPSIZE} from env" || SPSIZE=1 - [ "$MPSIZE" ] && echo "Caught MPSIZE: ${MPSIZE} from env" || MPSIZE="${WORLD_SIZE}" - [ "$ZERO_STAGE" ] && echo "Caught ${ZERO_STAGE} from env" || ZERO_STAGE=0 - # [ "$USE_SEQUENCE_PARALLEL" = 0 ] && export USE_SEQUENCE_PARALLEL=0 || export USE_SEQUENCE_PARALLEL=1 - # if [[ "$SPSIZE" == 0 ]]; then - # echo "Caught SPSIZE=$SPSIZE from env!!" - # USE_SEQUENCE_PARALLEL=0 - # else - # USE_SEQUENCE_PARALLEL=1 - # fi - # if [[ "$USE_SEQUENCE_PARALLEL" ]]; then - # echo "Caught USE_SEQUENCE_PARALLEL=${USE_SEQUENCE_PARALLEL} from env!!" - # [ "${SPSIZE}" != 0 ] && USE_SEQUENCE_PARALLEL=1 || USE_SEQUENCE_PARALLEL=0 - # [ "$USE_SEQUENCE_PARALLEL" = 0 ] && echo "Not using sequence parallelism" || USE_SEQUENCE_PARALLEL=1 - export SPSIZE="${SPSIZE}" - export MPSIZE="${MPSIZE}" - export ZERO_STAGE="${ZERO_STAGE}" - export USE_SEQUENCE_PARALLEL="${USE_SEQUENCE_PARALLEL:-1}" - # if [[ "${SPSIZE}" == 0 ]]; then - # [ "$SPSIZE" ] && USE_SEQUENCE_PARALLEL=1 || USE_SEQUENCE_PARALLEL=0 - # echo "Caught SPSIZE=${SPSIZE} from env, with ${SP_TYPE} sequence parallelism" - # export SPSIZE="${SPSIZE}" - # export USE_SEQUENCE_PARALLEL=0 - # else - # export SPSIZE=1 - # export USE_SEQUENCE_PARALLEL=1 - # fi - # if [ -z "${ZERO_STAGE}" ]; then - # echo "ZERO_STAGE not set, setting to 0 for ${SP_TYPE}" - # ZERO_STAGE=0 - # else - # echo "Caught ZERO_STAGE=${ZERO_STAGE} with ${SP_TYPE}" - # fi + # NOTE: -------------------------------------------------------------------------- + # SP_TYPE="megatron" will use Megatron's Seq. || implementation with ZERO_STAGE=0 + # -------------------------------------------------------------------------------- + [ "$SPSIZE" ] && echo "Caught SPSIZE: ${SPSIZE} from env" || SPSIZE=1 + [ "$MPSIZE" ] && echo "Caught MPSIZE: ${MPSIZE} from env" || MPSIZE="${WORLD_SIZE}" + [ "$ZERO_STAGE" ] && echo "Caught ${ZERO_STAGE} from env" || ZERO_STAGE=0 + [ "$USE_SEQUENCE_PARALLEL" ] && echo "Caught USE_SP: $USE_SEQUENCE_PARALLEL from env" || USE_SEQUENCE_PARALLEL=1 + export SPSIZE="${SPSIZE}" + export MPSIZE="${MPSIZE}" + export ZERO_STAGE="${ZERO_STAGE}" + export USE_SEQUENCE_PARALLEL="${USE_SEQUENCE_PARALLEL:-1}" else - echo "Unexpected SP_TYPE: ${SP_TYPE}" - exit 1 + echo "Unexpected SP_TYPE: ${SP_TYPE}" + # exit 1 fi # ------------------------------------------------------------------------ echo "####################################################" -echo "# USING: ${SP_TYPE}" -echo "# SPSIZE: ${SPSIZE}" -echo "# PPSIZE: ${SPSIZE}" -echo "# MPSIZE: ${MPSIZE}" -echo "# ZERO_STAGE: ${ZERO_STAGE}" -echo "# WORLD_SIZE: ${WORLD_SIZE}" -echo "# USE_SEQUENCE_PARALLEL: ${USE_SEQUENCE_PARALLEL}" +echo "USING: ${SP_TYPE}" +echo "SPSIZE: ${SPSIZE}" +echo "PPSIZE: ${SPSIZE}" +echo "MPSIZE: ${MPSIZE}" +echo "ZERO_STAGE: ${ZERO_STAGE}" +echo "WORLD_SIZE: ${WORLD_SIZE}" +echo "USE_SEQUENCE_PARALLEL: ${USE_SEQUENCE_PARALLEL}" echo "####################################################" -echo "########################################################" -echo "| ${SP_TYPE} sequence parallelism, with: " -echo "| {MPSIZE: ${MPSIZE}, SPSIZE: ${SPSIZE}, USE_SEQUENCE_PARALLEL: ${USE_SEQUENCE_PARALLEL}} !!" +echo "++++++++++++++++++++++++++++++++++++++++++++++++++++++++" +echo "${SP_TYPE} sequence parallelism, with: " +echo " {MPSIZE: ${MPSIZE}, SPSIZE: ${SPSIZE}, USE_SEQUENCE_PARALLEL: ${USE_SEQUENCE_PARALLEL}} !!" echo "########################################################" -# GLOBAL_BATCH=1 -# GLOBAL_BATCH=$(( $GLOBAL_BATCH / $MPSIZE / $PPSIZE / $SPSIZE )) -# GLOBAL_BATCH=$(( $NGPUS * $MICRO_BATCH * $GRADIENT_ACCUMULATION_STEPS )) GLOBAL_BATCH=$(( NGPUS * MICRO_BATCH * GRADIENT_ACCUMULATION_STEPS )) echo "GB = NGPUS * MB * GAS = ${NGPUS} * ${MICRO_BATCH} * ${GRADIENT_ACCUMULATION_STEPS} = ${GLOBAL_BATCH}" GLOBAL_BATCH=$(( GLOBAL_BATCH / MPSIZE / PPSIZE / SPSIZE)) echo "GB = (NGPUS * MB * GAS) / (MP * PP * SP) = (${NGPUS} * ${MICRO_BATCH} * ${GRADIENT_ACCUMULATION_STEPS}) / (${MPSIZE} * ${PPSIZE} * ${SPSIZE}) = ${GLOBAL_BATCH}" + +if [[ "${GLOBAL_BATCH}" == 0 ]]; then + GLOBAL_BATCH=1 +fi +# [ "${GLOBAL_BATCH:-${GLOBAL_BATCH}}" == 0 ] && GLOBAL_BATCH=1 || echo "GLOBAL_BATCH: ${GLOBAL_BATCH}" export GLOBAL_BATCH="$GLOBAL_BATCH" echo "--------------------------------" @@ -246,19 +144,17 @@ echo "--------------------------------" # ┏━━━━━━━━━━━━┓ # ┃ Data paths ┃ # ┗━━━━━━━━━━━━┛ +[ "$(hostname)==login*" ] && MEGATRON_DIR="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" +[ "$(hostname)==nid*" ] && MEGATRON_DIR="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" +[ "$(hostname)==theta*" ] && MEGATRON_DIR="/lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" +[ "$(hostname)==x3*" ] && MEGATRON_DIR="/lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" + # DATA_PATH=/lus/grand/projects/datascience/vsastry/genslm_subsample_200k_sequence_document/genslm_subsample_200k_sequence_document -DATA_DIR="${PARENT}/dataset" +DATA_DIR="${MEGATRON_DIR}/dataset" DATA_PATH="${DATA_DIR}/BookCorpusDataset_text_document" VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" -# DATA_PATH="/home/czh5/genome/Megatron-DeepSpeed/dataset/BookCorpusDataset_text_document" -# VOCAB_FILE="/home/czh5/genome/Megatron-DeepSpeed/dataset/gpt2-vocab.json" -# MERGE_FILE="/home/czh5/genome/Megatron-DeepSpeed/dataset/gpt2-merges.txt" -# DATA_PATH="/lus/eagle/projects/MDClimSim/chengming/gpt_datasets1/BookCorpusDataset_text_document" -# VOCAB_FILE="/lus/eagle/projects/MDClimSim/chengming/gpt_datasets1/gpt2-vocab.json" -# MERGE_FILE="/lus/eagle/projects/MDClimSim/chengming/gpt_datasets1/gpt2-merges.txt" - # ┏━━━━━━━━━━━━━━━━━━━┓ # ┃ FILE I/O SETTINGS ┃ # ┗━━━━━━━━━━━━━━━━━━━┛ @@ -268,17 +164,35 @@ RUN_STR="mp${MPSIZE}_pp${PPSIZE}_sp${SPSIZE}_${RUN_STR}" RUN_STR="z${ZERO_STAGE}_seqlen${SEQ_LEN}_${RUN_STR}" RUN_STR="${MODEL_SIZE}_${RUN_STR}" -if [[ $USE_FLASH_ATTN == 1 ]] ; then - RUN_STR="flashAttn_${RUN_STR}" +# if [[ "${USE_FLASH_ATTN}" == 0 ]]; then +# echo "Not using Flash Attention!!" +# else +# +if [[ "${USE_FLASH_ATTN1}" || "${USE_FLASH_ATTN_V1}" ]]; then + # Flash Attention 1 + [ "${USE_FLASH_ATTN}" ] && RUN_STR="flashAttn_v1_${RUN_STR}" + [ "${USE_FLASH_ATTN1}" ] && RUN_STR="flashAttn_v1_${RUN_STR}" + [ "${USE_FLASH_ATTN_V1}" ] && RUN_STR="flashAttn_v1_${RUN_STR}" +elif [[ "${USE_FLASH_ATTN2}" || "${USE_FLASH_ATTN_V2}" ]]; then + # Flash Attention 2 + [ "${USE_FLASH_ATTN2}" ] && RUN_STR="flashAttn_v2_${RUN_STR}" + [ "${USE_FLASH_ATTN_V2}" ] && RUN_STR="flashAttn_v2_${RUN_STR}" +elif [[ "${USE_FLASH_ATTN_TRITON}" ]]; then + # Triton + Flash Attn + # Triton + Flash Attn + [ "${USE_FLASH_ATTN_TRITON}" ] && RUN_STR="flashAttn_triton_${RUN_STR}" +else + echo "Not using Flash Attention!" fi + if [[ $DDP_IMPL == 'FSDP' ]]; then - RUN_STR="FSDP_${RUN_STR}" + RUN_STR="FSDP_${RUN_STR}" fi if [[ $USE_ACTIVATION_CHECKPOINTING == 1 ]] ;then - RUN_STR="actCkpt_${RUN_STR}" + RUN_STR="actCkpt_${RUN_STR}" fi if [[ $USE_SEQUENCE_PARALLEL == 1 ]] ; then - RUN_STR="SP_${RUN_STR}" + RUN_STR="SP_${RUN_STR}" fi RUN_STR="${MODEL_TYPE}_${RUN_STR}" @@ -287,6 +201,9 @@ OUTPUT_DIR="${PARENT}/outputs/${RUN_STR}" CHECKPOINT_DIR="${PARENT}/checkpoints/$RUN_STR" TENSORBOARD_DIR="${PARENT}/outputs/${RUN_STR}/tensorboard" +DATE=$(date) +export DATE="${DATE}" +export RUN_STR="${RUN_STR}" export MODEL_SIZE="$MODEL_SIZE" export TENSORBOARD_DIR=$TENSORBOARD_DIR export OUTPUT_DIR=$OUTPUT_DIR @@ -311,9 +228,9 @@ echo "OUTPUT TO: ${OUTPUT_DIR}" # echo "NVME_PATH: ${NVME_PATH}" if [[ $MODEL_TYPE == "gpt" ]] ; then - DATA_LOAD_ARGS="--data-path $DATA_PATH --vocab-file $VOCAB_FILE --merge-file $MERGE_FILE" + DATA_LOAD_ARGS="--data-path $DATA_PATH --vocab-file $VOCAB_FILE --merge-file $MERGE_FILE" else - DATA_LOAD_ARGS="" + DATA_LOAD_ARGS="" fi # Set to cpu for offloading to cpu for larger models @@ -329,319 +246,241 @@ CPU_OPTIM=" --cpu-optimizer" # ┗━━━━━━━━━━━━━━━━━━┛ DS_CONFIG=${PARENT}/ds_config-gpt.json echo "!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~!" -echo "! DS_CONFIG: ${DS_CONFIG}" +echo " DS_CONFIG: ${DS_CONFIG}" echo "!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~!" -# "optimizer": { -# "type": "Adam", -# "params": { -# "lr": 0.001, -# "betas": [0.8, 0.999], -# "eps": 1e-8, -# "weight_decay": 3e-7 -# } -# }, - -# "zero_allow_untested_optimizer": false, -# "train_batch_size" : $GLOBAL_BATCH, -# "zero_force_ds_cpu_optimizer": false, + if [[ $ZERO_STAGE == "3" ]] ; then -cat < "$DS_CONFIG" -{ - "train_micro_batch_size_per_gpu": $MICRO_BATCH, - "steps_per_print": 1, - "wall_clock_breakdown" : true, - "gradient_accumulation_steps": $GRADIENT_ACCUMULATION_STEPS, - "gradient_clipping": 1.0, - "zero_optimization": { - "stage": 3, - "stage3_max_live_parameters": 3e9, - "stage3_max_reuse_distance": 3e9, - "stage3_param_persistence_threshold": 1e5, - "stage3_prefetch_bucket_size": 1e9, - "contiguous_gradients": true, - "overlap_comm": true, - "reduce_bucket_size": 90000000, - "sub_group_size": 5e7, - "offload_param": { - "device": "cpu", - "pin_memory": true + cat < "$DS_CONFIG" + { + "train_micro_batch_size_per_gpu": $MICRO_BATCH, + "steps_per_print": 1, + "wall_clock_breakdown" : true, + "gradient_accumulation_steps": $GRADIENT_ACCUMULATION_STEPS, + "gradient_clipping": 1.0, + "zero_optimization": { + "stage": 3, + "stage3_max_live_parameters": 3e9, + "stage3_max_reuse_distance": 3e9, + "stage3_param_persistence_threshold": 1e5, + "stage3_prefetch_bucket_size": 1e9, + "contiguous_gradients": true, + "overlap_comm": true, + "reduce_bucket_size": 90000000, + "sub_group_size": 5e7, + "offload_param": { + "device": "cpu", + "pin_memory": true }, "offload_optimizer": { - "device": "cpu", - "buffer_count": 4, - "pipeline_read": false, - "pipeline_write": false, - "pin_memory": true - } - }, - "fp16": { - "enabled": true, - "initial_scale_power" : 12, - "loss_scale_window": 1000, - "hysteresis": 2, - "min_loss_scale": 1 - }, - "aio": { - "block_size": 1048576, - "queue_depth": 16, - "single_submit": false, - "overlap_events": true, - "thread_count": 2 - }, - "flops_profiler": { - "enabled": true, - "profile_step": 1, - "module_depth": -1, - "top_modules": 3, - "detailed": true, - "output_file": null - }, - "comms_logger": { - "enabled": true, - "verbose": false, - "prof_all": false, - "debug": false - }, - "wandb": { - "enabled": true, - "project": "Megatron-DS-Benchmarking" - } + "device": "cpu", + "buffer_count": 4, + "pipeline_read": false, + "pipeline_write": false, + "pin_memory": true +} +}, +"fp16": { +"enabled": true, +"initial_scale_power" : 12, +"loss_scale_window": 1000, +"hysteresis": 2, +"min_loss_scale": 1 +}, +"aio": { +"block_size": 1048576, +"queue_depth": 16, +"single_submit": false, +"overlap_events": true, +"thread_count": 2 +}, +"flops_profiler": { +"enabled": true, +"profile_step": 1, +"module_depth": -1, +"top_modules": 3, +"detailed": true, +"output_file": null +}, +"comms_logger": { +"enabled": true, +"verbose": false, +"prof_all": false, +"debug": false +}, +"wandb": { +"enabled": true, +"project": "GenSLM-Megatron-DS" +} } EOT else -cat < "$DS_CONFIG" -{ - "train_micro_batch_size_per_gpu": $MICRO_BATCH, - "gradient_accumulation_steps": $GRADIENT_ACCUMULATION_STEPS, - "steps_per_print": 1, - "wall_clock_breakdown" : true, - "zero_force_ds_cpu_optimizer": false, - "zero_optimization": { - "stage": $ZERO_STAGE, - "allgather_partitions": true, - "reduce_scatter": true, - "allgather_bucket_size": 5e8, - "overlap_comm": true, - "contiguous_gradients": true, + cat < "$DS_CONFIG" + { + "train_micro_batch_size_per_gpu": $MICRO_BATCH, + "gradient_accumulation_steps": $GRADIENT_ACCUMULATION_STEPS, + "steps_per_print": 1, + "wall_clock_breakdown" : true, + "zero_force_ds_cpu_optimizer": false, + "zero_optimization": { + "stage": $ZERO_STAGE, + "allgather_partitions": true, + "reduce_scatter": true, + "allgather_bucket_size": 5e8, + "overlap_comm": true, + "contiguous_gradients": true, + "offload_param": { + "device": "cpu", + "nvme_path": "/raid/scratch", + "pin_memory": false + }, "offload_optimizer": { - "device": "cpu" - } - }, - "optimizer": { - "type": "OneBitAdam" - }, - "scheduler": { - "type": "WarmupLR", - "params": { - "warmup_min_lr": 0, - "warmup_max_lr": 0.001, - "warmup_num_steps": 1000 - } - }, - "fp16": { - "enabled": true, - "initial_scale_power": 12 - }, - "flops_profiler": { - "enabled": true, - "profile_step": 1, - "module_depth": -1, - "top_modules": 3, - "detailed": true, - "output_file": null - }, - "comms_logger": { - "enabled": true, - "verbose": false, - "prof_all": false, - "debug": false - }, - "wandb": { - "enabled": true, - "project": "Megatron-DS-Benchmarking" - } + "device": "cpu", + "nvme_path": "/raid/scratch/" +} +}, +"scheduler": { +"type": "WarmupLR", +"params": { +"warmup_min_lr": 0, +"warmup_max_lr": 0.001, +"warmup_num_steps": 1000 +} +}, +"fp16": { +"enabled": true, +"initial_scale_power": 12 +}, +"flops_profiler": { +"enabled": true, +"profile_step": 1, +"module_depth": -1, +"top_modules": 3, +"detailed": true, +"output_file": null +}, +"comms_logger": { +"enabled": true, +"verbose": false, +"prof_all": false, +"debug": false +}, +"wandb": { +"enabled": true, +"project": "GenSLM-Megatron-DS" +} } EOT fi -# "optimizer": { -# "type": "Adam", -# "params": { -# "lr": 0.001, -# "betas": [0.8, 0.999], -# "eps": 1e-8, -# "weight_decay": 3e-7 -# } -# }, -# -# "offload_optimizer": { -# "device": "$OFFLOAD_DEVICE", -# "buffer_count": 4, -# "pipeline_read": false, -# "pipeline_write": false, -# "pin_memory": true -# } -# "train_batch_size" : $GLOBAL_BATCH, -# 'offload_optimizer': 'cpu' - # "train_batch_size" : $GLOBAL_BATCH, -# "offload_optimizer": { -# "device": "cpu", -# "nvme_path": "/raid/scratch/" -# } -# -# "optimizer": { -# "type": "AdamW", -# "params": { -# "lr": 0.001, -# "betas": [0.8, 0.999], -# "eps": 1e-8, -# "weight_decay": 3e-7 -# } -# }, -# "optimizer": { -# "type": "OneBitAdam", -# "params": { -# "lr": 0.001, -# "betas": [ -# 0.8, -# 0.999 -# ], -# "eps": 1e-8, -# "weight_decay": 3e-7, -# "freeze_step": 400, -# "cuda_aware": false, -# "comm_backend_name": "nccl" -# } -# }, -# -# "optimizer": "Adam", -# "optimizer": { -# "type": "OneBitAdam", -# "params": { -# "lr": 0.001, -# "betas": [ -# 0.8, -# 0.999 -# ], -# "eps": 1e-8, -# "weight_decay": 3e-7, -# "freeze_step": 400, -# "cuda_aware": true, -# "comm_backend_name": "nccl" -# } -# }, -# -# -# 'deepspeed_mpi': True, -# 'ds_pipeline_enabled': False, -# 'rank': 0, -# 'world_size': 1, -# 'transformer_pipeline_model_parallel_size': 1, -# 'data_parallel_size': 1, -# 'virtual_pipeline_model_parallel_ size': None, - # ┏━━━━━━━━━━━━━━━━━━━━━┓ # ┃ DeepSpeed Arguments ┃ # ┗━━━━━━━━━━━━━━━━━━━━━┛ if [[ "$DDP_IMPL" != "FSDP" ]] ; then - ds_args="" - ds_args=" --deepspeed ${ds_args}" - ds_args=" --deepspeed_mpi ${ds_args}" - ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" - ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" - if [[ "$PPSIZE" == 1 ]]; then - ds_args="--no-pipeline-parallel ${ds_args}" - else - ds_args=" --pipeline-model-parallel-size ${PPSIZE} ${ds_args}" - fi - if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then - ds_args=" --deepspeed-activation-checkpointing ${ds_args}" - fi + ds_args="" + ds_args=" --deepspeed ${ds_args}" + ds_args=" --deepspeed_mpi ${ds_args}" + ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" + ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" + if [[ "$PPSIZE" == 1 ]]; then + ds_args="--no-pipeline-parallel ${ds_args}" + else + ds_args=" --pipeline-model-parallel-size ${PPSIZE} ${ds_args}" + fi + if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + ds_args=" --deepspeed-activation-checkpointing ${ds_args}" + fi fi # ┏━━━━━━━━━━━━━━━━━━━━━━┓ # ┃ MEGATRON-LM SETTINGS ┃ # ┗━━━━━━━━━━━━━━━━━━━━━━┛ -# "--sequence-parallel-size ${SPSIZE}" gpt_args=( - "--seed ${RANDOM}" - "--DDP-impl ${DDP_IMPL}" - "--pipeline-model-parallel-size ${PPSIZE}" - "--tensor-model-parallel-size ${MPSIZE}" - "--num-layers ${NLAYERS}" - "--hidden-size ${HIDDEN}" - "--num-attention-heads ${ATEN_HEADS}" - "--micro-batch-size ${MICRO_BATCH}" - "--global-batch-size ${GLOBAL_BATCH}" - "--seq-length ${SEQ_LEN}" - "--max-position-embeddings ${SEQ_LEN}" - "--train-iters 10" - "--lr-decay-iters 320000" - "--num-workers 1" - "$DATA_LOAD_ARGS" - "--data-impl mmap" - "--split 949,50,1" - "--distributed-backend nccl" - "--lr 0.00015" - "--lr-decay-style cosine" - "--min-lr 1.0e-5" - "--weight-decay 1e-2" - "--clip-grad 1.0" - "--lr-warmup-fraction .01" - "--log-interval 1" - "--save-interval 1000" - "--eval-interval 1000" - "--eval-iters 10" - "--override-opt_param-scheduler" - "--tensorboard-dir ${TENSORBOARD_DIR}" - "--log-timers-to-tensorboard" - "--tensorboard-log-interval 1" + "--no-async-tensor-model-parallel-allreduce" + "--seed ${RANDOM}" + "--DDP-impl ${DDP_IMPL}" + "--pipeline-model-parallel-size ${PPSIZE}" + "--tensor-model-parallel-size ${MPSIZE}" + "--ds-sequence-parallel-size ${SPSIZE}" + "--num-layers ${NLAYERS}" + "--hidden-size ${HIDDEN}" + "--num-attention-heads ${ATEN_HEADS}" + "--micro-batch-size ${MICRO_BATCH}" + "--global-batch-size ${GLOBAL_BATCH}" + "--seq-length ${SEQ_LEN}" + "--max-position-embeddings ${SEQ_LEN}" + "--train-iters 10" + "--lr-decay-iters 320000" + "--num-workers 1" + "$DATA_LOAD_ARGS" + "--data-impl mmap" + "--split 949,50,1" + "--distributed-backend nccl" + "--lr 0.00015" + "--lr-decay-style cosine" + "--min-lr 1.0e-5" + "--weight-decay 1e-2" + "--clip-grad 1.0" + "--lr-warmup-fraction .01" + "--log-interval 1" + "--save-interval 1000" + "--eval-interval 1000" + "--eval-iters 0" + "--override-opt_param-scheduler" + "--tensorboard-dir ${TENSORBOARD_DIR}" + "--log-timers-to-tensorboard" + "--tensorboard-log-interval 1" ) -# --recompute-activations \ -# --recompute-granularity full \ -# --recompute-method uniform \ -# --recompute-num-layers 1 \ + if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then - gpt_args+=( + gpt_args+=( "--checkpoint-activations" "--checkpoint-num-layers 1" - ) +) fi if [[ "$DDP_IMPL" != "FSDP" ]] ; then - gpt_args+=( + gpt_args+=( # "${gpt_args[*]}" "--fp16" - ) +) else - gpt_args+=( + gpt_args+=( "--bf16" - ) +) fi -if [[ "$USE_FLASH_ATTN" == 1 ]] ; then - gpt_args+=( - "--use-flash-attn" - ) +# Flash Attention v1 +if [[ "${USE_FLASH_ATTN1}" || "${USE_FLASH_ATTN_V1}" ]]; then + [ "${USE_FLASH_ATTN}" ] && gpt_args+=("--use-flash-attn-v1") + [ "${USE_FLASH_ATTN1}" ] && gpt_args+=("--use-flash-attn-v1") + [ "${USE_FLASH_ATTN_V1}" ] && gpt_args+=("--use-flash-attn-v1") +# Flash Attention 2 +elif [[ "${USE_FLASH_ATTN2}" || "${USE_FLASH_ATTN_V2}" ]]; then + [ "${USE_FLASH_ATTN2}" ] && gpt_args+=("--use-flash-attn-v2") + [ "${USE_FLASH_ATTN_V2}" ] && gpt_args+=("--use-flash-attn-v2") +# Triton + Flash Attn +elif [[ "${USE_FLASH_ATTN_TRITON}" ]]; then + [ "${USE_FLASH_ATTN_TRITON}" ] && gpt_args+=("--use-flash-attn-triton") fi -# if [[ "$USE_SEQUENCE_PARALLEL" == 1 ]]; then -# gpt_args+=( -# "--sequence-parallel" -# ) -# fi +if [[ "$USE_SEQUENCE_PARALLEL" == 1 ]]; then + gpt_args+=( + "--sequence-parallel" +) +fi -if [[ "${SP_TYPE}" == "ds" ]]; then - gpt_args+=( +if [[ "$ZERO_STAGE" > "0" ]] ; then + gpt_args+=( "--cpu-optimizer" - ) +) fi export gpt_args=( - "${gpt_args[*]}" - "${ds_args[*]}" +"${gpt_args[*]}" +"${ds_args[*]}" ) +ARGS="$(join_by ' ' ${gpt_args[*]})" echo "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" -echo "gpt_args: ${gpt_args[*]}" +echo "ARGS: ${ARGS}" echo "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" diff --git a/ALCF/benchmark_train.sh b/ALCF/benchmark_train.sh deleted file mode 100755 index 94eb94e116..0000000000 --- a/ALCF/benchmark_train.sh +++ /dev/null @@ -1,82 +0,0 @@ -#!/bin/bash --login - -TSTAMP=$(date "+%Y-%m-%d-%H%M%S") -# DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd -LP) -# - -#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ -#┃ Make sure we're not already running; if so, exit here ┃ -#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ -PIDS=$(ps aux | grep pretrain_gpt.py | grep -v grep | awk '{print $2}') -if [ -n "${PIDS}" ]; then - echo "Already running! Exiting!" - exit 1 -fi - - -SOURCE=${BASH_SOURCE[0]} -while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink - DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) - SOURCE=$(readlink "$SOURCE") - [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located -done -DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) - - -function sourceFile() { - FILE="$1" - echo "source-ing ${FILE}" - if [[ -f "${FILE}" ]]; then - # shellcheck source="${FILE}" - source "${FILE}" - else - echo "ERROR: UNABLE TO SOURCE ${FILE}" - fi -} - -SETUP_FILE="${DIR}/setup.sh" -MODEL_FILE="${DIR}/model.sh" -ARGS_FILE="${DIR}/args.sh" -LAUNCH_FILE="${DIR}/launch.sh" - - -sourceFile "${SETUP_FILE}" -sourceFile "${MODEL_FILE}" -sourceFile "${ARGS_FILE}" -sourceFile "${LAUNCH_FILE}" - - -SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) -echo "My current script is: ${SCRIPT_DIR[0]}" - -NHOSTS=$(wc -l < "${COBALT_NODEFILE}") -# NGPU_PER_HOST=8 -NGPU_PER_HOST=$(nvidia-smi -L | wc -l) -PARALLEL_SIZE=$(( NHOSTS * NGPU_PER_HOST )) - -export MODEL_TYPE=${MODEL_TYPE:-"gpt"} # set bert or gpt -export SP_TYPE=${SP_TYPE:-"megatron"} # set ds or megatron - -echo "+-----------------------------+" -echo "| MODEL TYPE: ${MODEL_TYPE}" -echo "| SP TYPE: ${SP_TYPE}" -echo "+-----------------------------+" - -#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ -#┃ source ./launch.sh ┃ -#┃ which then sources ./{args.sh,setup.sh} ┃ -#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ - -export MODEL_TYPE=${MODEL_TYPE:-gpt} - -setup -# singleGPU "$@" 2>&1 & -# fullNode "$@" 2>&1 & -TORCH_VERSION=$(python3 -c 'import torch; print(torch.__version__)') -export TORCH_VERSION=$TORCH_VERSION -export CUDA_DEVICE_MAX_CONNECTIONS=1 -# fullNode "$@" -# elasticDistributed "$@" 2>&1 & -# elasticDistributed "$@" -PID=$! -wait $PID diff --git a/ALCF/launch.sh b/ALCF/launch.sh index 7604098667..c61a0e22ce 100755 --- a/ALCF/launch.sh +++ b/ALCF/launch.sh @@ -2,18 +2,17 @@ HOST=$(hostname) -# # DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd -LP) -# SOURCE=${BASH_SOURCE[0]} -# while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink -# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) -# SOURCE=$(readlink "$SOURCE") -# [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located -# done +function WhereAmI() { + python3 -c 'import os; print(os.getcwd())' +} + +# function join_by { +# local d=${1-} f=${2-}; if shift 2; then printf %s "$f" "${@/#/$d}"; fi; +# } -# HERE=$(python3 -c 'import os; print(os.getcwd())') -# ALCF_DIR="${HERE}/ALCF" -# -ALCF_DIR="$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1)))/ALCF" +USER=$(whoami) +HERE=$(WhereAmI) +ALCF_DIR="${HERE}/ALCF" PARENT=$(dirname "${ALCF_DIR}") echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" @@ -23,19 +22,16 @@ echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" function sourceFile() { - FILE="$1" - echo "source-ing ${FILE}" - if [[ -f "${FILE}" ]]; then - # shellcheck source=./setup.sh - source "${FILE}" - else - echo "ERROR: UNABLE TO SOURCE ${FILE}" - fi + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source=./setup.sh + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi } -# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) -# PARENT=$(dirname "${DIR}") - MASTER_ADDR=$(uname -n) MASTER_PORT=20010 SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )" @@ -46,106 +42,126 @@ sourceFile "${ALCF_DIR}/args.sh" MAIN="${PARENT}/pretrain_${MODEL_TYPE}.py" printJobInfo() { - echo "Job started at: ${TSTAMP} on $(hostname)" - echo "Job running in: ${DIR}" - echo "Training GPT-3 with ${MODEL_SIZE} parameters" - echo "Writing logs to: ${OUTPUT_DIR}" - echo 'to view output: tail -f $(tail -1 logfiles)' - echo "i.e. tail -f $(tail -1 "${PARENT}"/logfiles)" + echo "Job started at: ${TSTAMP} on $(hostname)" + echo "Job running in: ${DIR}" + echo "Training GPT-3 with ${MODEL_SIZE} parameters" + echo "Writing logs to: ${OUTPUT_DIR}" + echo 'to view output: tail -f $(tail -1 logfiles)' + echo "i.e. tail -f $(tail -1 "${PARENT}"/logfiles)" } launchJob() { - echo "using: $(which python3)" | tee -a "${OUTPUT_LOG}" - printJobInfo | tee -a "${OUTPUT_LOG}" - echo EXEC="${EXEC}" | tee -a "${OUTPUT_LOG}" - echo "Writing logs to: ${OUTPUT_LOG}" | tee -a "${OUTPUT_LOG}" - ${EXEC} "$@" # >> "${OUTPUT_LOG}" 2>&1 & -} - -singleGPU() { - echo "\ - Running on 1 host \ - with 1 GPUs each \ - for a total of 1 GPUs" - EXEC="\ - $(which python3) \ - ${MAIN} \ - ${gpt_args} \ - ${ds_args}" - OUTPUT_LOG="${OUTPUT_DIR}/logs/$USER-$HOST-nhosts1-ngpu1-$TSTAMP.log" - mkdir -p "$(dirname "${OUTPUT_LOG}")" - echo "${OUTPUT_LOG}" >> "${PARENT}/logfiles" - printJobInfo | tee -a "${OUTPUT_LOG}" - launchJob "$@" >> "${OUTPUT_LOG}" 2>&1 & + echo "using: $(which python3)" | tee -a "${OUTPUT_LOG}" + printJobInfo | tee -a "${OUTPUT_LOG}" + echo EXEC="${EXEC}" | tee -a "${OUTPUT_LOG}" + echo "Writing logs to: ${OUTPUT_LOG}" | tee -a "${OUTPUT_LOG}" + # ARGS="$@" + # export ARGS="$ARGS" + ${EXEC} "$@" # >> "${OUTPUT_LOG}" 2>&1 & } # ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ # ┃ Use all available GPUs a single nodes ┃ # ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ fullNode() { - echo "fullNode started" - echo "MPI_COMMAND ${MPI_COMMAND}" - echo "MPI_DEFAULTS ${MPI_DEFAULTS}" - echo "NGPUS ${NGPUS}" - echo "hostfile ${DIR}/hostfile" - echo "MAIN ${MAIN}" - echo "gpt_args ${gpt_args}" - NHOSTS=$(wc -l < "${HOSTFILE}") - NGPU_PER_HOST=$(nvidia-smi -L | wc -l) - # NGPU_PER_HOST=1 - NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) - # hostname > $DIR/hostfile - echo "\ - Running on $NHOSTS hosts \ - with $NGPU_PER_HOST GPUs each \ - for a total of $NGPUS GPUs" - EXEC="\ - ${MPI_COMMAND} \ - ${MPI_DEFAULTS} \ - "${MPI_ELASTIC}" - ${MPI_WRAPPER} ${MASTER_ADDR} ${MASTER_PORT} \ - ${MAIN} \ - ${gpt_args} \ - ${ds_args}" - OUTPUT_LOG="${OUTPUT_DIR}/logs/$USER-$HOST-nhosts${NHOSTS}-ngpu${NGPUS}-$TSTAMP.log" - mkdir -p "$(dirname "${OUTPUT_LOG}")" - echo "${OUTPUT_LOG}" >> "${PARENT}/logfiles" - printJobInfo | tee -a "${OUTPUT_LOG}" - launchJob "$@" 2>&1 | tee "${OUTPUT_LOG}" + echo "fullNode started" + echo "MPI_COMMAND ${MPI_COMMAND}" + echo "MPI_DEFAULTS ${MPI_DEFAULTS}" + echo "NGPUS ${NGPUS}" + echo "hostfile ${DIR}/hostfile" + echo "MAIN ${MAIN}" + echo "gpt_args ${gpt_args}" + NHOSTS=$(wc -l < "${HOSTFILE}") + NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) + # hostname > $DIR/hostfile + echo "\ + Running on $NHOSTS hosts \ + with $NGPU_PER_HOST GPUs each \ + for a total of $NGPUS GPUs" + _EXEC=( + "${MPI_COMMAND}" + "${MPI_DEFAULTS}" + "${MPI_ELASTIC}" + "${MPI_WRAPPER}" + "${MASTER_ADDR}" + "${MASTER_PORT}" + "${MAIN}" + "${gpt_args}" + "${ds_args}" + ) + # EXEC=$(join_by ' ' "${EXEC[*]}") + EXEC="${EXEC[*]}" + OUTPUT_LOG="${OUTPUT_DIR}/logs/$USER-$HOST-nhosts${NHOSTS}-ngpu${NGPUS}-$TSTAMP.log" + mkdir -p "$(dirname "${OUTPUT_LOG}")" + echo "${OUTPUT_LOG}" >> "${PARENT}/logfiles" + printJobInfo | tee -a "${OUTPUT_LOG}" + launchJob "$@" 2>&1 | tee "${OUTPUT_LOG}" } # ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ # ┃ Use all available GPUs on all available nodes ┃ # ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ elasticDistributed() { - NHOSTS=$(wc -l < "${HOSTFILE}") - NGPU_PER_HOST=$(nvidia-smi -L | wc -l) - NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) - export WORLD_SIZE="${NGPUS}" - echo "\ - Running on ${NHOSTS} hosts \ - with ${NGPU_PER_HOST} GPUs each \ - for a total of ${NGPUS} GPUs" - EXEC_STR=( - "${MPI_COMMAND}" - "${MPI_DEFAULTS}" - "${MPI_ELASTIC}" - "$(which python3)" - "${MAIN}" - "${gpt_args}" - "${ds_args}" - ) - EXEC="${EXEC_STR[*]}" - OUTPUT_LOG="${OUTPUT_DIR}/logs/$USER-$HOST-nhosts${NHOSTS}-ngpu${NGPUS}-$TSTAMP.log" - echo "Writing logs to: ${OUTPUT_LOG}" - mkdir -p "$(dirname "${OUTPUT_LOG}")" - echo "${OUTPUT_LOG}" >> "${PARENT}/logfiles" - printJobInfo | tee -a "${OUTPUT_LOG}" - # launchJob "$@" >> "${OUTPUT_LOG}" 2>&1 & - # launchJob "$@" - # printJobInfo | tee -a "${OUTPUT_LOG}" - # launchJob "$@" >> "${OUTPUT_LOG}" 2>&1 & - launchJob "$@" >> "${OUTPUT_LOG}" 2>&1 & - PID=$! - wait $PID + if [[ "$(hostname)==theta*" || "$(hostname)==x3*" ]]; then + if [[ $(hostname) == theta* ]]; then + echo "Setting up ThetaGPU from $(hostname)" + HOSTFILE="${COBALT_NODEFILE}" + elif [[ $(hostname) == x3* ]]; then + echo "Setting up Polaris from $(hostname)" + HOSTFILE="${PBS_NODEFILE}" + else + echo "Unknown hostname $(hostname)" + exit 1 + fi + NHOSTS=$(wc -l < "${HOSTFILE}") + NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + EXEC_STR=( + "${MPI_COMMAND}" + "${MPI_DEFAULTS}" + "${MPI_ELASTIC}" + "$(which python3)" + "${MAIN}" + "${gpt_args}" + "${ds_args}" + ) + elif [[ "$(hostname)==nid*" || "$(hostname)==login*" ]]; then + echo "Setting up from Perlmutter on $(hostname)" + [ "$(hostname)==nid*" ] && NHOSTS="$SLURM_NNODES" || NHOSTS=1 + [ "$(hostname)==nid*" ] && export MACHINE="perlmutter" || export MACHINE="NERSC" + NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + # NGPU_PER_HOST="$SLURM_GPUS_ON_NODE" + NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + # export MACHINE="perlmutter" + export MASTER_ADDR="127.0.0.1" + export MASTER_PORT="5432" + EXEC_STR=( + "srun" + "-N ${NHOSTS}" + "-n ${NGPUS}" + "-l -u" + "$(which python3)" + "${MAIN}" + "${gpt_args}" + "${ds_args}" + ) + else + echo "Unexpected hostname $(hostname)" + fi + export WORLD_SIZE="${NGPUS}" + echo "\ + Running on ${NHOSTS} hosts \ + with ${NGPU_PER_HOST} GPUs each \ + for a total of ${NGPUS} GPUs" + EXEC="${EXEC_STR[*]}" + OUTPUT_LOG="${OUTPUT_DIR}/logs/$USER-$HOST-nhosts${NHOSTS}-ngpu${NGPUS}-$TSTAMP.log" + echo "EXEC_STR: ${EXEC_STR}" + echo "Writing logs to: ${OUTPUT_LOG}" + mkdir -p "$(dirname "${OUTPUT_LOG}")" + echo "${OUTPUT_LOG}" >> "${PARENT}/logfiles" + printJobInfo | tee -a "${OUTPUT_LOG}" + launchJob "$@" >> "${OUTPUT_LOG}" 2>&1 & + PID=$! + wait $PID } diff --git a/ALCF/model.sh b/ALCF/model.sh index 2427893e9b..c41a908203 100755 --- a/ALCF/model.sh +++ b/ALCF/model.sh @@ -258,6 +258,28 @@ A_NLAYERS[$MODEL_145B_KEY]=80 A_HIDDEN[$MODEL_145B_KEY]=12288 A_ATEN_HEADS[$MODEL_145B_KEY]=96 +MODEL_1T_1L_KEY="GPT1T_1L" +A_NLAYERS[$MODEL_1T_1L_KEY]=1 +A_HIDDEN[$MODEL_1T_1L_KEY]=25600 +A_ATEN_HEADS[$MODEL_1T_1L_KEY]=160 + +MODEL_1T_2L_KEY="GPT1T_2L" +A_NLAYERS[$MODEL_1T_2L_KEY]=2 +A_HIDDEN[$MODEL_1T_2L_KEY]=25600 +A_ATEN_HEADS[$MODEL_1T_2L_KEY]=160 + +MODEL_1T_4L_KEY="GPT1T_4L" +A_NLAYERS[$MODEL_1T_4L_KEY]=4 +A_HIDDEN[$MODEL_1T_4L_KEY]=25600 +A_ATEN_HEADS[$MODEL_1T_4L_KEY]=160 + + +MODEL_1T_8L_KEY="GPT1T_8L" +A_NLAYERS[$MODEL_1T_8L_KEY]=8 +A_HIDDEN[$MODEL_1T_8L_KEY]=25600 +A_ATEN_HEADS[$MODEL_1T_8L_KEY]=160 + + export MODEL_SIZE="${MODEL_SIZE_KEY}" export NLAYERS="${A_NLAYERS[$MODEL_SIZE_KEY]}" export HIDDEN="${A_HIDDEN[$MODEL_SIZE_KEY]}" diff --git a/ALCF/mpi_wrapper b/ALCF/mpi_wrapper deleted file mode 100755 index 770f950e1d..0000000000 --- a/ALCF/mpi_wrapper +++ /dev/null @@ -1,27 +0,0 @@ -#!/usr/bin/env bash - -set -e - -PYTHON=${PYTHON:-python3} - -MASTER_ADDR="$1" -MASTER_PORT="$2" -TRAINING_SCRIPT="$3" - -shift 3 - -test -n "${MASTER_ADDR}" -a -n "${MASTER_PORT}" -a -n "${OMPI_COMM_WORLD_RANK}" -a -n "${OMPI_COMM_WORLD_SIZE}" -a -n "${OMPI_COMM_WORLD_LOCAL_RANK}" -test -f "${TRAINING_SCRIPT}" - -set -x - -LOCAL_RANK=$((OMPI_COMM_WORLD_RANK % 8)) - -exec env \ - MASTER_ADDR="${MASTER_ADDR}" \ - MASTER_PORT="${MASTER_PORT}" \ - RANK="${OMPI_COMM_WORLD_RANK}" \ - WORLD_SIZE="${OMPI_COMM_WORLD_SIZE}" \ - ${PYTHON} -u "${TRAINING_SCRIPT}" "--local_rank=${LOCAL_RANK}" "$@" - -exit 1 diff --git a/ALCF/setup.sh b/ALCF/setup.sh index 0b90daf02e..b3b135c513 100755 --- a/ALCF/setup.sh +++ b/ALCF/setup.sh @@ -1,228 +1,244 @@ #!/bin/bash --login # -# DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd -LP) -SOURCE=${BASH_SOURCE[0]} -while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink - DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) - SOURCE=$(readlink "$SOURCE") - [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located -done -DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) -PARENT=$(dirname "${DIR}") - -export CUDA_DEVICE_MAX_CONNECTIONS=1 - -thetagpuMPI() { - NHOSTS=$(wc -l < "${COBALT_NODEFILE}") - NGPU_PER_HOST=$(nvidia-smi -L | wc -l) - NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) - NVME_PATH="/raid/scratch/" - MPI_COMMAND=$(which mpirun) - # export PATH="${CONDA_PREFIX}/bin:${PATH}" - MPI_DEFAULTS="\ - --hostfile ${HOSTFILE} \ - -x CFLAGS \ - -x LDFLAGS \ - -x http_proxy \ - -x PYTHONUSERBASE \ - -x https_proxy \ - -x PATH \ - -x CUDA_DEVICE_MAX_CONNECTIONS \ - -x LD_LIBRARY_PATH" - MPI_ELASTIC="\ - -n ${NGPUS} \ - -npernode ${NGPU_PER_HOST}" +function WhereAmI() { + python3 -c 'import os; print(os.getcwd())' } -polarisMPI() { - NHOSTS=$(wc -l < "${PBS_NODEFILE}") - NGPU_PER_HOST=$(nvidia-smi -L | wc -l) - NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) - MPI_COMMAND=$(which mpiexec) - NVME_PATH="/local/scratch/" - MPI_DEFAULTS="\ - --envall \ - --verbose \ - --hostfile ${HOSTFILE}" - MPI_ELASTIC="\ - -n ${NGPUS} \ - --ppn ${NGPU_PER_HOST}" +HERE=$(WhereAmI) +# ALCF_DIR=$(find "${HERE}" -name "ALCF") +ALCF_DIR="${HERE}/ALCF" +PARENT=$(dirname "${ALCF_DIR}") + +function join_by { local d=${1-} f=${2-}; if shift 2; then printf %s "$f" "${@/#/$d}"; fi; } + +function setupVenv() { + VENV_DIR="$1" + # VENV_DIR="${PARENT}/venvs/perlmutter/torch2.0.1/" + if [[ -d "${VENV_DIR}" ]]; then + echo "Found venv at: ${VENV_DIR}" + source "${VENV_DIR}/bin/activate" + else + echo "Skipping setupVenv() on $(hostname)" + fi } -setupMPI() { - if [[ $(hostname) == theta* ]]; then - echo "Setting up MPI on ThetaGPU from $(hostname)" - thetagpuMPI - elif [[ $(hostname) == x* ]]; then - echo "Setting up MPI on Polaris from $(hostname)" - polarisMPI - else - echo "Unexpected hostname $(hostname)" - fi +function loadCondaEnv() { + if [[ "${CONDA_EXE}" ]]; then + echo "Already inside ${CONDA_EXE}, exiting!" + else + MODULE_STR="$1" + module load "conda/${MODULE_STR}" + conda activate base + fi } -condaThetaGPU220701() { - module load conda/2022-07-01 ; conda activate base - conda activate \ - /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2022-07-01 - # if [[ -f "${PARENT}/.venvs/thetaGPU/2022-07-01-deepspeed/bin/activate" ]]; then - # echo "Found virtual environment!" - # source "${PARENT}/.venvs/thetaGPU/2022-07-01-deepspeed/bin/activate" - # fi +function thetagpuMPI() { + if [[ $(hostname) == theta* ]]; then + export HOSTFILE="${COBALT_NODEFILE}" + NHOSTS=$(wc -l < "${COBALT_NODEFILE}") + NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) + NVME_PATH="/raid/scratch/" + MPI_COMMAND=$(which mpirun) + # export PATH="${CONDA_PREFIX}/bin:${PATH}" + _MPI_DEFAULTS=( + "--hostfile ${HOSTFILE}" + "-x CFLAGS" + "-x LDFLAGS" + "-x http_proxy" + "-x PYTHONUSERBASE" + "-x https_proxy" + "-x PATH" + "-x CUDA_DEVICE_MAX_CONNECTIONS" + "-x LD_LIBRARY_PATH" + ) + _MPI_ELASTIC=( + "-n ${NGPUS}" + "-npernode ${NGPU_PER_HOST}" + ) + export MPI_DEFAULTS="$(join_by ' ' ${_MPI_DEFAULTS})" + export MPI_ELASTIC="$(join_by ' ' ${_MPI_ELASTIC})" + else + echo "Skipping thetaGPUMPI() on $(hostname)" + fi } -condaThetaGPU230111() { - module load conda/2023-01-11 ; conda activate base -# conda activate \ -# /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2023-01-11-deepspeed - VENV_DIR="${PARENT}/venvs/thetaGPU/2023-01-11-deepspeed" - if [[ -d "${VENV_DIR}" ]] ; then - echo "Found venv at: ${VENV_DIR}" - # shellcheck source='../venvs/thetaGPU/2023-01-10/bin/activate' - source "${VENV_DIR}/bin/activate" - fi +function polarisMPI() { + if [[ $(hostname) == x3* ]]; then + export HOSTFILE="${PBS_NODEFILE}" + export NHOSTS=$(wc -l < "${PBS_NODEFILE}") + export NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + export NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) + export MPI_COMMAND=$(which mpiexec) + export NVME_PATH="/local/scratch/" + _MPI_DEFAULTS=( + "--envall" + "--verbose" + "--hostfile ${HOSTFILE}" + ) + _MPI_ELASTIC=( + "-n ${NGPUS}" + "--ppn ${NGPU_PER_HOST}" + ) + export MPI_DEFAULTS="$(join_by ' ' ${_MPI_DEFAULTS})" + export MPI_ELASTIC="$(join_by ' ' ${_MPI_ELASTIC})" + else + echo "Skipping polarisMPI() on $(hostname)" + fi } -condaThetaGPU() { - module load conda/2022-07-01 ; conda activate base - conda activate \ - /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2022-07-01 - echo "USING PYTHON: $(which python3)" +function setupMPI() { + if [[ $(hostname) == theta* ]]; then + echo "Setting up MPI on ThetaGPU from $(hostname)" + thetagpuMPI + elif [[ $(hostname) == x* ]]; then + echo "Setting up MPI on Polaris from $(hostname)" + polarisMPI + else + echo "Skipping setupMPI() on hostname $(hostname)" + fi + echo "++ SetupMPI() +++++++++++++++++++++++++++++++++" + echo "Using HOSTFILE: $HOSTFILE" + echo "NHOSTS: ${NHOSTS}" + echo "NGPU_PER_HOST: ${NGPU_PER_HOST}" + echo "NGPUS: $NGPUS" + echo "+++++++++++++++++++++++++++++++++++++++++++++++" } -condaThetaGPU_mtanaka() { - # module load conda/2023-01-11 ; conda activate base - # conda activate \ - # /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2023-01-11-deepspeed - VENV_DIR="/lus/grand/projects/datascience/mtanaka/dsseq/venv/dsseq" - if [[ -d "${VENV_DIR}" ]] ; then - echo "Found venv at: ${VENV_DIR}" - # shellcheck source='../venvs/thetaGPU/2023-01-10/bin/activate' - source "${VENV_DIR}/bin/activate" - fi +function condaPolaris() { + if [[ "$(hostname)" == x3* ]]; then + DATE_STR="2023-09-29" + [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}" + [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" + else + echo "Skipping condaPolaris() on $(hostname)" + fi } -condaPolaris220908() { - echo "Loading: 'module load conda 2022-09-08 ; conda activate base'" - module load conda/2022-09-08 ; conda activate base - conda activate /lus/grand/projects/datascience/foremans/locations/polaris/miniconda3/envs/2022-09-08-deepspeed - export CFLAGS="-I${CONDA_PREFIX}/include" - export LDFLAGS="-L${CONDA_PREFIX}/lib" - VENV_DIR="${PARENT}/venvs/polaris/2022-09-08" - if [[ -d "${VENV_DIR}" ]]; then - echo "Found venv at: ${VENV_DIR}" - source "${VENV_DIR}/bin/activate" - fi +function condaThetaGPU() { + if [[ "$(hostname)" == theta* ]]; then + DATE_STR="2023-01-11" + [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}" + [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" + else + echo "Skipping condaThetaGPU() on $(hostname)" + fi } -condaPolaris230110() { - echo "Loading: 'module load conda 2023-01-10-unstable ; conda activate base'" - module load conda/2023-01-10-unstable ; conda activate base - export CFLAGS="-I${CONDA_PREFIX}/include" - export LDFLAGS="-L${CONDA_PREFIX}/lib" - # conda activate \ - # /lus/grand/projects/datascience/foremans/locations/polaris/miniconda3/envs/2023-01-10 - VENV_DIR="${PARENT}/venvs/polaris/2023-01-10/" - if [[ -d "${VENV_DIR}" ]]; then - echo "Found venv at: ${VENV_DIR}" - # shellcheck source=../venvs/polaris/2023-01-10/bin/activate - source "${VENV_DIR}/bin/activate" - fi +function setupThetaGPU() { + export LAB="ALCF" + export MACHINE="ThetaGPU" + if [[ $(hostname) == theta* ]]; then + setupMPI + DATE_STR="2023-01-11" + [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}" || echo "Caught CONDA_EXE: ${CONDA_EXE}" + [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" || echo "Caught VIRTUAL_ENV: ${VIRTUAL_ENV}" + else + echo "Skipping setupThetaGPU() on $(hostname)" + fi } -condaThetaGPU230426() { - echo "Loading: 'module load conda 2023-01-10-unstable ; conda activate base'" - module load conda/2023-01-11 - conda activate base - conda activate /lus/grand/projects/datascience/foremans/locations/thetaGPU/miniconda3/envs/2023-04-26 - VENV_DIR="${PARENT}/venvs/thetaGPU/2023-04-26/" - if [[ -d "${VENV_DIR}" ]]; then - echo "Found venv at: ${VENV_DIR}" - # shellcheck source=../venvs/thetaGPU/2023-04-26/ - source "${VENV_DIR}/bin/activate" - fi - thetagpuMPI - export CFLAGS="-I${CONDA_PREFIX}/include" - export LDFLAGS="-L${CONDA_PREFIX}/lib" +function setupPolaris() { + export LAB="ALCF" + export MACHINE="Polaris" + if [[ "$(hostname)" == x3* ]]; then + # SETUP MPI -------------------------------- + setupMPI + # SETUP Python -------------------------------- + DATE_STR="2023-09-29" + [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}-unstable" || echo "Caught CONDA_EXE: ${CONDA_EXE}" + [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" || echo "Caught VIRTUAL_ENV: ${VIRTUAL_ENV}" + else + echo "Skipping setupPolaris() on $(hostname)" + fi } -condaPolaris() { - condaPolaris230110 - echo "USING PYTHON: $(which python3)" +function setupALCF() { + if [[ $(hostname) == theta* || $(hostname) == x3* ]]; then + setupMPI + [ "$(hostname)==theta*" ] && setupThetaGPU || echo "Skipping setupThetaGPU from $(hostname)" + [ "$(hostname)==x3*" ] && setupPolaris || echo "Skipping setupPolaris from $(hostname)" + else + echo "Skipping setupALCF() on $(hostname)" + fi } -# ┏━━━━━━━━━━┓ -# ┃ ThetaGPU ┃ -# ┗━━━━━━━━━━┛ -setupThetaGPU() { - if [[ $(hostname) == theta* ]]; then - export MACHINE="ThetaGPU" - HOSTFILE="${COBALT_NODEFILE}" - # -- Python / Conda setup ------------------------------------------------- - thetagpuMPI - condaThetaGPU230426 - else - echo "Unexpected hostname: $(hostname)" - fi +# ┏━━━━━━━┓ +# ┃ NERSC ┃ +# ┗━━━━━━━┛ +function setupPerlmutter() { + if [[ $(hostname) == login* || $(hostname) == nid* ]]; then + module load libfabric cudatoolkit pytorch/2.0.1 + if [[ $(hostname) == login* ]]; then + export MACHINE="NERSC" + module load pytorch/2.0.1 + export NHOSTS=1 + export NGPU_PER_HOST=1 + export NGPUS=1 + # echo "$(hostname)" > "${HERE}/hostfile" + elif [[ $(hostname) == nid* ]]; then + export NODELIST="${SLURM_JOB_NODELIST:-$(hostname)}" + export NODE_RANK=0 + export CUDA_DEVICE_MAX_CONNECTIONS=1 + export MACHINE="PERLMUTTER" + export NHOSTS="${SLURM_NNODES:-1}" + export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" + export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + else + echo "Unexpected $(hostname) on NERSC" + fi + echo "+++++++++++++++++++++++++++++++++++" + echo "Using python: $(which python3)" + echo "+++++++++++++++++++++++++++++++++++" + else + echo "Skipping setupPerlmutter() on $(hostname)" + fi } -# ┏━━━━━━━━━┓ -# ┃ Polaris ┃ -# ┗━━━━━━━━━┛ -setupPolaris() { - if [[ $(hostname) == x* ]]; then - export MACHINE="Polaris" - HOSTFILE="${PBS_NODEFILE}" - # -- MPI / Comms Setup ---------------------------------------------------- - condaPolaris - polarisMPI - # export IBV_FORK_SAFE=1 - else - echo "Unexpected hostname: $(hostname)" - fi + +function setupMachine() { + HOSTNAME="$(hostname)" + if [[ $(hostname) == theta* || $(hostname) == x3* ]]; then + export LAB="ALCF" + setupALCF + [ "${HOSTNAME}==theta*" ] && condaThetaGPU + [ "${HOSTNAME}==x3*" ] && condaPolaris + elif [[ "${HOSTNAME}== nid*" || "${HOSTNAME}== login*" ]]; then + export LAB="NERSC" + setupPerlmutter + [ "${HOSTNAME}==login*" ] && setupPerlmutter + [ "${HOSTNAME}==nid*" ] && setupPerlmutter + else + echo "Unexpected hostname: $(hostname)" + fi } # ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ # ┃ SETUP CONDA + MPI ENVIRONMENT @ ALCF ┃ # ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ -setup() { - # unset PYTHONUSERBASE - export NCCL_DEBUG=warn - export WANDB_CACHE_DIR="./cache/wandb" - CFLAGS="-I${CONDA_PREFIX}/include/" - LDFLAGS="-L${CONDA_PREFIX}/lib/" - # export CFLAGS="${CFLAGS}" - # export LDFLAGS="${LDFLAGS}" - # export PATH="${CONDA_PREFIX}/bin:${PATH}" - - export NVME_PATH="${NVME_PATH}" - export MPI_DEFAULTS="${MPI_DEFAULTS}" - export MPI_ELASTIC="${MPI_ELASTIC}" - export MPI_COMMAND="${MPI_COMMAND}" - - PYTHON_EXECUTABLE="$(which python3)" - export PYTHON_EXECUTABLE="${PYTHON_EXECUTABLE}" - echo "USING PYTHON: $(which python3)" - echo "CFLAGS: ${CFLAGS}" - echo "LDFLAGS: ${LDFLAGS}" - # source "${DIR}/args.sh" - - if [[ $(hostname) == theta* ]]; then - echo "Setting up ThetaGPU from $(hostname)" - setupThetaGPU - elif [[ $(hostname) == x* ]]; then - echo "Setting up Polaris from $(hostname)" - setupPolaris - else - echo "Unexpected hostname $(hostname)" - fi - export NODE_RANK=0 - # export RANK=0 - export NNODES=$NHOSTS - export GPUS_PER_NODE=$NGPU_PER_HOST - export WORLD_SIZE=$NGPUS - export NGPUS="${NGPUS}" - export NHOSTS="${NHOSTS}" - export NGPU_PER_HOST="${NGPU_PER_HOST}" - export CUDA_DEVICE_MAX_CONNECTIONS=1 +function setup() { + export NCCL_DEBUG=warn + # TORCH_EXTENSIONS_DIR="${HERE}/.cache/torch_extensions" + export WANDB_CACHE_DIR="./cache/wandb" + setupMachine + PYTHON_EXECUTABLE="$(which python3)" + export PYTHON_EXECUTABLE="${PYTHON_EXECUTABLE}" + echo "USING PYTHON: $(which python3)" + # echo "CFLAGS: ${CFLAGS}" + # echo "LDFLAGS: ${LDFLAGS}" + # export NODE_RANK=0 + export NNODES=$NHOSTS + export GPUS_PER_NODE=$NGPU_PER_HOST + export WORLD_SIZE=$NGPUS + export NGPUS="${NGPUS}" + export NHOSTS="${NHOSTS}" + export NGPU_PER_HOST="${NGPU_PER_HOST}" + export CUDA_DEVICE_MAX_CONNECTIONS=1 + echo "########################################" + echo "NHOSTS: ${NHOSTS}" + echo "NGPU_PER_HOST: ${NGPU_PER_HOST}" + echo "NGPUS: (${NHOSTS} * ${NGPU_PER_HOST}) = ${NGPUS}" + echo "########################################" } + +setup diff --git a/ALCF/sweep_args_theta_multinode.sh b/ALCF/sweep_args_theta_multinode.sh deleted file mode 100755 index ac6409233a..0000000000 --- a/ALCF/sweep_args_theta_multinode.sh +++ /dev/null @@ -1,164 +0,0 @@ -#!/bin/bash -l - -module load conda/2023-01-11 -conda activate base -# cd /home/czh5/seq/Megatron-DS-Benchmarking/ALCF -# source /home/czh5/seq/Megatron-DS-Benchmarking/venvs/thetaGPU/2023-01-11-deepspeed/bin/activate - -# rm -rf /home/czh5/genome/Megatron-DeepSpeed/dataset/*.npy -# rm -rf /home/czh5/genome/Megatron-DeepSpeed/dataset/*.done -# -SCRIPT_PATH="${BASH_SOURCE[0]}" -while [ -L "$SCRIPT_PATH" ]; do - SCRIPT_DIR="$(cd -P "$(dirname "$SCRIPT_PATH")" >/dev/null 2>&1 && pwd)" - SCRIPT_PATH="$(readlink "$SCRIPT_PATH")" - [[ ${SCRIPT_PATH} != /* ]] && SCRIPT_PATH="${SCRIPT_DIR}/${SCRIPT_PATH}" -done -SCRIPT_PATH="$(readlink -f "$SCRIPT_PATH")" -SCRIPT_DIR="$(cd -P "$(dirname -- "$SCRIPT_PATH")" >/dev/null 2>&1 && pwd)" - -SOURCE=${BASH_SOURCE[0]} -while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink - DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) - SOURCE=$(readlink "$SOURCE") - [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located -done -DIR="$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd )" - - -function sourceFile() { - FILE="$1" - echo "source-ing ${FILE}" - if [[ -f "${FILE}" ]]; then - # shellcheck source="${FILE}" - source "${FILE}" - else - echo "ERROR: UNABLE TO SOURCE ${FILE}" - fi -} - -SETUP_FILE="${DIR}/setup.sh" -MODEL_FILE="${DIR}/model.sh" -ARGS_FILE="${DIR}/args.sh" -LAUNCH_FILE="${DIR}/launch.sh" - - -sourceFile "${SETUP_FILE}" -sourceFile "${MODEL_FILE}" -sourceFile "${ARGS_FILE}" -sourceFile "${LAUNCH_FILE}" - -SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) -echo "My current script is: ${SCRIPT_DIR[0]}" - - -if [[ $(hostname) == theta* ]]; then - HOSTFILE="${COBALT_NODEFILE}" -elif [[ $(hostname) == x* ]]; then - HOSTFILE="${PBS_NODEFILE}" -else - echo "Unexpected hostname $(hostname)" -fi - -echo "Found hostfile: ${HOSTFILE}" - -NHOSTS=$(wc -l < "${HOSTFILE}") -NGPU_PER_HOST=$(nvidia-smi -L | wc -l) -PARALLEL_SIZE=$(( NHOSTS * NGPU_PER_HOST )) - -export MODEL_TYPE=${MODEL_TYPE:-"gpt"} # set bert or gpt -export SP_TYPE=${SP_TYPE:-"megatron"} # set ds or megatron - -K_VALS=( - # 2 - # 4 - 8 - # 16 - # 32 - # 64 - # 128 - # 192 - # 256 - # 272 - # 320 - # 384 - # 448 - # 512 - # 1024 -) - -SEQLEN_VALS=( -# 2048 -# 4096 -# 8192 -# 16384 -# 32768 -# 65536 -# 131072 -# 262144 -# 524288 -# 1048576 -# 2097152 -) - -MODEL_SIZE_VALS=( - # "GPT125M" - # "BERT1.2B" -# "GPT1_5B" - # "GPT2_7B" -# "GPT6_7B" - # "GPT13B" - "GPT25B" -# "GPT30B" -# "GPT33B" -) - -for MODEL_SIZE_KEY in "${MODEL_SIZE_VALS[@]}"; do - export MODEL_SIZE_KEY -# for SEQ_LEN in "${SEQLEN_VALS[@]}"; do -# export SEQ_LEN - for NUM_K in "${K_VALS[@]}"; do - # common_factor=$(( $PARALLEL_SIZE * 8 )) - # export SEQ_LEN=$(( 1024 * $NUM_K / $common_factor * $common_factor )) - - export SEQ_LEN=$(( 1024 * $NUM_K )) - - if [[ ${SP_TYPE} == "ds" ]]; then - echo "DS sequence parallel" - export SPSIZE=${PARALLEL_SIZE} - export MPSIZE=1 - export ZERO_STAGE=3 - export USE_SEQUENCE_PARALLEL=0 - bash ./benchmark_train.sh - fi - - if [[ ${SP_TYPE} == "megatron" ]]; then - echo "Megatron's sequence parallel" - - # if [ ${SEQ_LEN} -eq 8192 ]; then - # PARALLEL_SIZE=8 - # fi - - # if [ ${SEQ_LEN} -eq 16384 ]; then - # PARALLEL_SIZE=8 - # fi - - # if [ ${SEQ_LEN} -eq 32768 ]; then - # PARALLEL_SIZE=16 - # fi - - # if [ ${SEQ_LEN} -eq 65536 ]; then - # PARALLEL_SIZE=16 - # fi - - export SPSIZE=1 - export MPSIZE=${PARALLEL_SIZE} - export ZERO_STAGE=0 - export USE_SEQUENCE_PARALLEL=1 - bash ./benchmark_train.sh - fi - - printf "\n------------------------" - echo SEQ_LEN=${SEQ_LEN} - done -done diff --git a/ALCF/train-gpt3.sh b/ALCF/train-gpt3.sh index fa707b5df4..bb054b0386 100755 --- a/ALCF/train-gpt3.sh +++ b/ALCF/train-gpt3.sh @@ -10,7 +10,8 @@ function WhereAmI() { } HERE=$(WhereAmI) -ALCF_DIR=$(find "${HERE}" -name "ALCF") +# ALCF_DIR=$(find "${HERE}" -name "ALCF") +ALCF_DIR="${HERE}/ALCF" # ALCF_DIR="$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1)))/ALCF" @@ -30,7 +31,7 @@ echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" #┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ #┃ Make sure we're not already running; if so, exit here ┃ #┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ -PIDS=$(ps aux | grep pretrain_gpt.py | grep -v grep | awk '{print $2}') +PIDS=$(ps aux | egrep "$USER.+mpi.+pretrain_gpt.py" | grep -v grep | awk '{print $2}') if [ -n "${PIDS}" ]; then echo "Already running! Exiting!" exit 1 From 7fc2221d20890f1a3c7d1e0ca4f06164ff6de2f5 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 3 Oct 2023 23:45:20 -0500 Subject: [PATCH 003/268] Update `pretrain_gpt.py` --- pretrain_gpt.py | 224 +++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 211 insertions(+), 13 deletions(-) diff --git a/pretrain_gpt.py b/pretrain_gpt.py index 149414848c..272f05318b 100644 --- a/pretrain_gpt.py +++ b/pretrain_gpt.py @@ -2,8 +2,11 @@ """Pretrain GPT""" +import os import torch import math +# import logging + from functools import partial from megatron import get_args from megatron import print_rank_0 @@ -18,25 +21,125 @@ from megatron.utils import get_ltor_masks_and_position_ids from megatron.utils import average_losses_across_data_parallel_group from megatron.arguments import core_transformer_config_from_args +from megatron.utils import ( + report_memory, + throughput_calculator, + checkpoint_throughput_calculator +) +from pathlib import Path import deepspeed from deepspeed.runtime.utils import see_memory_usage from deepspeed.accelerator.real_accelerator import get_accelerator -import os import subprocess +import wandb +import time from torch import nn import torch.nn.functional as F +# from ezpz import get_logger +from ezpz.dist import setup_torch, get_world_size + +RANK = setup_torch( + backend='deepspeed', + port='5432', +) +WORLD_SIZE = get_world_size() +LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" + + +# os.environ[''] +# wblogger = logging.getLogger("wandb") +# wblogger.setLevel(logging.DEBUG) + +# log = get_logger(__name__, level=LEVEL) +# +# log.critical(f"Hello from rank: {RANK} / {WORLD_SIZE} !") + +import socket +from typing import Optional +# log.critical(f"Setting up W&B from rank: {RANK} with {wb_project_name}") + + +def setup_wandb(project_name: Optional[str] = None): + print(f"Setting up W&B from: {RANK}") + project_name = ( + os.environ.get('WB_PROJECT', 'GenSLM-Megatron-DS') + if project_name is None else project_name + ) + print(f"Setting up wandb from rank: {RANK}") + print(f"Using: WB PROJECT: {project_name}") + # if get_rank() == 0: + # tensorboard_dir = args.tensorboard_dir + tensorboard_dir = None + # if config is None: + tensorboard_dir = os.environ.get('TENSORBOARD_DIR', None) + # else: + # tensorboard_dir = ( + # config.get( + # 'tensorboard_dir', + # None, # os.getcwd() + # ) + # ) + if tensorboard_dir is not None: + print(f'Patching tensorboard from {tensorboard_dir}') + wandb.tensorboard.patch(root_logdir=tensorboard_dir) + # wbrun_id = wandb.util.generate_id() + current_time = time.time() + # local_time = time.localtime(current_time) + # if wandb.run is None: + wandb.init( + resume='allow', + sync_tensorboard=(tensorboard_dir is not None), # True, + project=(project_name if project_name is not None else None), + # dir=(tensorboard_dir if tensorboard_dir is not None else None), + ) + assert wandb.run is not None + print(f"W&B RUN: [{wandb.run.name}]({wandb.run.url})") + wandb.run.config.update({'current_time': current_time}) + model_size = os.environ.get('MODEL_SIZE', None) + wandb.run.config.update({'world_size': get_world_size()}) + # if config is not None: + # wandb.run.config.update(config) + env = { + k: v for k, v in dict(os.environ).items() + if not k.startswith('_ModuleTable') + } + _ = env.pop('LS_COLORS', None) + _ = env.pop('PS1', None) + wandb.run.config.update({'env': env}) + hostname = socket.gethostbyaddr(socket.gethostname())[0] + if hostname.startswith('theta'): + wandb.run.config.update({'machine': 'ThetaGPU'}) + elif hostname.startswith('x3'): + wandb.run.config.update({'machine': 'Polaris'}) + elif hostname.startswith('x1'): + wandb.run.config.update({'machine': 'Sunspot'}) + elif hostname.startswith('nid'): + wandb.run.config.update({'machine': 'Perlmutter'}) + elif hostname.startswith('login'): + wandb.run.config.update({'machine': 'NERSC'}) + else: + wandb.run.config.update({'machine': hostname}) + if model_size is not None: + wandb.run.config.update({'MODEL_SIZE': model_size}) + def model_provider(pre_process=True, post_process=True): """Build the model.""" - print_rank_0('building GPT model ...') - see_memory_usage(f"Before Building Model", force=True) - + see_memory_usage("Before Building Model", force=True) args = get_args() config = core_transformer_config_from_args(args) + # args = get_args() + # timers = get_timers() + if wandb.run is not None: + print(f"Updating WandB run: [{wandb.run.name}]({wandb.run.url})") + wandb.run.config.update({"args": vars(args)}) + if RANK == 0: + git_ds_info() + with deepspeed.zero.Init(sequence_data_parallel_group=mpu.get_sequence_data_parallel_group(), remote_device=None if args.remote_device == 'none' else args.remote_device, config_dict_or_path=args.deepspeed_config, @@ -92,7 +195,21 @@ def model_provider(pre_process=True, post_process=True): pre_process=pre_process, post_process=post_process ) - see_memory_usage(f"After Building Model", force=True) + num_params = sum(p.numel() for p in model.parameters() if p.requires_grad) + # print_rank_0('\n ------------------------ ') + # print_rank_0(f'num of parameters {num_params}') + # print_rank_0('------------------------\n ') + print_rank_0(80 * '-') + print_rank_0(f"Number of parameters in model: {num_params}") + print_rank_0(80 * '-') + see_memory_usage("After Building Model", force=True) + if wandb.run is not None: + wandb.run.watch( + model, + log='all', + log_graph=True, + ) + wandb.run.config.update({'num_params': num_params}) return model @@ -118,7 +235,8 @@ def get_batch(data_iterator): tokens = tokens_[:, :-1].contiguous() # Get the masks and postition ids. - skip_mask = args.use_flash_attn or args.use_flash_attn_triton + skip_mask = hasattr(args, 'use_flash_attn') or hasattr(args, 'flash_attn_triton') + # skip_mask = args.use_flash_attn or args.use_flash_attn_triton attention_mask, loss_mask, position_ids = get_ltor_masks_and_position_ids( tokens, tokenizer.eod, @@ -357,11 +475,91 @@ def git_ds_info(): print(f'**** Git info for Megatron: git_hash={git_hash} git_branch={git_branch} ****') +def main(): + if RANK == 0: + setup_wandb() + + model = pretrain( + train_valid_test_datasets_provider, + model_provider, + ModelType.encoder_or_decoder, + forward_step, + args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + data_post_process=data_post_process + ) + # # from megatron.training import get_model + # if wandb.run is not None: + # args = get_args() + # timers = get_timers() + # # model = get_model(model_provider, ModelType.encoder_or_decoder) + # elapsed_time = timers('interval-time').elapsed(barrier=True) + # total_iterations = os.environ.get( + # "TOTAL_ITERATIONS", + # (args.train_iters + args.eval_iters) + # ) + # seq_len = args.seq_length + # elapsed_time_per_iteration = elapsed_time / total_iterations + # if model is not None: + # samples_per_sec, tflops, approx_params_in_billions = throughput_calculator( + # model, + # args, + # elapsed_time, + # total_iterations, + # ) + # # Compute throughput. + # samples_per_sec_per_replica = samples_per_sec / args.data_parallel_size + # tokens_per_sec = samples_per_sec * seq_len + # tokens_per_sec_per_replica = tokens_per_sec / args.data_parallel_size + # sample_consumption_rate = args.consumed_train_samples / elapsed_time + # token_consumption_rate = args.consumed_train_tokens / elapsed_time + # # Tensorboard values. + # tdata = { + # # 'iteration': iteration, + # 'consumed_train_samples': args.consumed_train_samples, + # 'consumed_train_tokens': args.consumed_train_tokens, + # # 'learning_rate': learning_rate, + # # 'batch_size': batch_size, + # # 'loss_scale': loss_scale, + # # 'grad_norm': grad_norm, + # } + # # for key in loss_dict: + # # tdata[f'lm-loss/{key}'] = loss_dict[key] + # + # tdata = {f'train/{k}': v for k, v in tdata.items()} + # # if wbrun is not None and wbrun is wandb.run: + # if wandb.run is not None: + # wandb.run.log(tdata, commit=False) + # tput = { + # 'throughput/iteration-time': elapsed_time_per_iteration, # 1000 ms / s + # 'throughput/samples_per_sec': samples_per_sec, + # 'throughput/samples_per_sec_per_replica': samples_per_sec_per_replica, + # 'throughput/tokens_per_sec': tokens_per_sec, + # 'throughput/tokens_per_sec_per_replica': tokens_per_sec_per_replica, + # 'throughput/tflops': tflops, + # 'throughput/approx_params_in_billions': approx_params_in_billions, + # 'throughput/sample_consumption_rate': sample_consumption_rate, + # 'throughput/token_consumption_rate': token_consumption_rate, + # 'throughput/elapsed_ms_per_iteration': elapsed_time_per_iteration, + # } + # wandb.run.log(tput) + return model + + + if __name__ == "__main__": - git_ds_info() - pretrain(train_valid_test_datasets_provider, - model_provider, - ModelType.encoder_or_decoder, - forward_step, - args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, - data_post_process=data_post_process) + # git_ds_info() + # pretrain(train_valid_test_datasets_provider, + # model_provider, + # ModelType.encoder_or_decoder, + # forward_step, + # args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + # data_post_process=data_post_process) + import sys + import deepspeed.comm as dist + model = main() + dist.log_summary() + if wandb.run is not None: + print(f"wandb.run.name: {wandb.run.name}") + print(f"wandb.run.url: {wandb.run.url}") + wandb.finish() + sys.exit() From 02cef749db7426e7a918b96147c5bd4a1a8e4228 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 10 Oct 2023 18:59:07 -0500 Subject: [PATCH 004/268] Update `ALCF/launch.sh` --- ALCF/launch.sh | 2 ++ 1 file changed, 2 insertions(+) diff --git a/ALCF/launch.sh b/ALCF/launch.sh index c61a0e22ce..dc7a08d991 100755 --- a/ALCF/launch.sh +++ b/ALCF/launch.sh @@ -117,6 +117,8 @@ elasticDistributed() { NHOSTS=$(wc -l < "${HOSTFILE}") NGPU_PER_HOST=$(nvidia-smi -L | wc -l) NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + export MASTER_ADDR="127.0.0.1" + export MASTER_PORT="5432" EXEC_STR=( "${MPI_COMMAND}" "${MPI_DEFAULTS}" From cb9397b361947847209be0128d3ec02deec9a214 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 10 Oct 2023 18:59:21 -0500 Subject: [PATCH 005/268] Update `ALCF/setup.sh` --- ALCF/setup.sh | 78 ++++++++++++++++++++++++++++++++------------------- 1 file changed, 49 insertions(+), 29 deletions(-) diff --git a/ALCF/setup.sh b/ALCF/setup.sh index b3b135c513..b8918df147 100755 --- a/ALCF/setup.sh +++ b/ALCF/setup.sh @@ -41,23 +41,36 @@ function thetagpuMPI() { NVME_PATH="/raid/scratch/" MPI_COMMAND=$(which mpirun) # export PATH="${CONDA_PREFIX}/bin:${PATH}" - _MPI_DEFAULTS=( - "--hostfile ${HOSTFILE}" - "-x CFLAGS" - "-x LDFLAGS" - "-x http_proxy" - "-x PYTHONUSERBASE" - "-x https_proxy" - "-x PATH" - "-x CUDA_DEVICE_MAX_CONNECTIONS" - "-x LD_LIBRARY_PATH" - ) - _MPI_ELASTIC=( - "-n ${NGPUS}" - "-npernode ${NGPU_PER_HOST}" - ) - export MPI_DEFAULTS="$(join_by ' ' ${_MPI_DEFAULTS})" - export MPI_ELASTIC="$(join_by ' ' ${_MPI_ELASTIC})" + MPI_DEFAULTS="\ + --hostfile ${HOSTFILE} \ + -x CFLAGS \ + -x LDFLAGS \ + -x http_proxy \ + -x CUDA_DEVICE_MAX_CONNECTIONS \ + -x PYTHONUSERBASE \ + -x https_proxy \ + -x PATH \ + -x LD_LIBRARY_PATH" + MPI_ELASTIC="\ + -n ${NGPUS} \ + -npernode ${NGPU_PER_HOST}" + # _MPI_DEFAULTS=( + # "--hostfile ${HOSTFILE}" + # "-x CFLAGS" + # "-x LDFLAGS" + # "-x http_proxy" + # "-x PYTHONUSERBASE" + # "-x https_proxy" + # "-x PATH" + # "-x CUDA_DEVICE_MAX_CONNECTIONS" + # "-x LD_LIBRARY_PATH" + # ) + # _MPI_ELASTIC=( + # "-n ${NGPUS}" + # "-npernode ${NGPU_PER_HOST}" + # ) + # export MPI_DEFAULTS="$(join_by ' ' ${_MPI_DEFAULTS})" + # export MPI_ELASTIC="$(join_by ' ' ${_MPI_ELASTIC})" else echo "Skipping thetaGPUMPI() on $(hostname)" fi @@ -71,17 +84,24 @@ function polarisMPI() { export NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) export MPI_COMMAND=$(which mpiexec) export NVME_PATH="/local/scratch/" - _MPI_DEFAULTS=( - "--envall" - "--verbose" - "--hostfile ${HOSTFILE}" - ) - _MPI_ELASTIC=( - "-n ${NGPUS}" - "--ppn ${NGPU_PER_HOST}" - ) - export MPI_DEFAULTS="$(join_by ' ' ${_MPI_DEFAULTS})" - export MPI_ELASTIC="$(join_by ' ' ${_MPI_ELASTIC})" + MPI_DEFAULTS="\ + --envall \ + --verbose \ + --hostfile ${HOSTFILE}" + MPI_ELASTIC="\ + -n ${NGPUS} \ + --ppn ${NGPU_PER_HOST}" + # _MPI_DEFAULTS=( + # "--envall" + # "--verbose" + # "--hostfile ${HOSTFILE}" + # ) + # _MPI_ELASTIC=( + # "-n ${NGPUS}" + # "--ppn ${NGPU_PER_HOST}" + # ) + # export MPI_DEFAULTS="$(join_by ' ' ${_MPI_DEFAULTS})" + # export MPI_ELASTIC="$(join_by ' ' ${_MPI_ELASTIC})" else echo "Skipping polarisMPI() on $(hostname)" fi @@ -107,7 +127,7 @@ function setupMPI() { function condaPolaris() { if [[ "$(hostname)" == x3* ]]; then - DATE_STR="2023-09-29" + DATE_STR="2023-10-04" [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}" [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" else From 36c4c79490af081bdd5a89353f0de31238ee1aab Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 11 Oct 2023 07:28:22 -0500 Subject: [PATCH 006/268] Move to public dataset --- ALCF/args.sh | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/ALCF/args.sh b/ALCF/args.sh index 200fd21fc9..058e8f5df5 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -146,8 +146,10 @@ echo "--------------------------------" # ┗━━━━━━━━━━━━┛ [ "$(hostname)==login*" ] && MEGATRON_DIR="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" [ "$(hostname)==nid*" ] && MEGATRON_DIR="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" -[ "$(hostname)==theta*" ] && MEGATRON_DIR="/lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" -[ "$(hostname)==x3*" ] && MEGATRON_DIR="/lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" +[ "$(hostname)==theta*" ] && MEGATRON_DIR="/lus/eagle/projects/datasets/BookCorpusDataset" +# "/lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" +[ "$(hostname)==x3*" ] && MEGATRON_DIR="/lus/eagle/projects/datasets/BookCorpusDataset" +# /lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" # DATA_PATH=/lus/grand/projects/datascience/vsastry/genslm_subsample_200k_sequence_document/genslm_subsample_200k_sequence_document DATA_DIR="${MEGATRON_DIR}/dataset" From 4709afc3616f5e4d1ab454f3e697ff27a3d4e46e Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 11 Oct 2023 21:01:33 -0500 Subject: [PATCH 007/268] Update `ALCF/args.sh` --- ALCF/args.sh | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/ALCF/args.sh b/ALCF/args.sh index 058e8f5df5..ad929532d0 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -144,16 +144,20 @@ echo "--------------------------------" # ┏━━━━━━━━━━━━┓ # ┃ Data paths ┃ # ┗━━━━━━━━━━━━┛ -[ "$(hostname)==login*" ] && MEGATRON_DIR="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" -[ "$(hostname)==nid*" ] && MEGATRON_DIR="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" -[ "$(hostname)==theta*" ] && MEGATRON_DIR="/lus/eagle/projects/datasets/BookCorpusDataset" +[ "$(hostname)==login*" ] && DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" +[ "$(hostname)==nid*" ] && DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" +# [ "$(hostname)==theta*" ] && DATA_PARENT="/lus/eagle/projects/datasets/BookCorpusDataset" +[ "$(hostname)==theta*" ] && DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" +[ "$(hostname)==x3*" ] && DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" # "/lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" -[ "$(hostname)==x3*" ] && MEGATRON_DIR="/lus/eagle/projects/datasets/BookCorpusDataset" +# /lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k/dataset/genslm_subsample_200k_sequence_document" +# [ "$(hostname)==x3*" ] && DATA_PARENT="/lus/eagle/projects/datasets/BookCorpusDataset" # /lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" +# /lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k/dataset/genslm_subsample_200k_sequence_document.bin # DATA_PATH=/lus/grand/projects/datascience/vsastry/genslm_subsample_200k_sequence_document/genslm_subsample_200k_sequence_document -DATA_DIR="${MEGATRON_DIR}/dataset" -DATA_PATH="${DATA_DIR}/BookCorpusDataset_text_document" +DATA_DIR="${DATA_PARENT}/dataset" +DATA_PATH="${DATA_DIR}/genslm_subsample_200k_sequence_document" VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" From 3e603c680579b5cf09b5fef4b858598b93191cf3 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 14:23:44 -0500 Subject: [PATCH 008/268] Update `ALCF/args.sh` --- ALCF/args.sh | 21 ++++++++++++++++++--- 1 file changed, 18 insertions(+), 3 deletions(-) diff --git a/ALCF/args.sh b/ALCF/args.sh index ad929532d0..3740cc067a 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -60,8 +60,11 @@ export MICRO_BATCH=${MICRO_BATCH:-1} export GRADIENT_ACCUMULATION_STEPS=${GAS:-1} export MODEL_TYPE=${MODEL_TYPE:-"gpt"} # set bert or gpt export SP_TYPE=${SP_TYPE:-"megatron"} # set ds or megatron +export ZERO_STAGE=${ZERO_STAGE:-1} +export MPSIZE=${MPSIZE:-${WORLD_SIZE:-1}} +export SPSIZE=${SPSIZE:-1} - +# # Deal with Sequence Parallel implementation --------------------------------------- # ---------------------------------------------------------------------------------- if [[ ${SP_TYPE} == "ds" ]]; then @@ -100,6 +103,12 @@ elif [[ ${SP_TYPE} == "megatron" ]]; then [ "$MPSIZE" ] && echo "Caught MPSIZE: ${MPSIZE} from env" || MPSIZE="${WORLD_SIZE}" [ "$ZERO_STAGE" ] && echo "Caught ${ZERO_STAGE} from env" || ZERO_STAGE=0 [ "$USE_SEQUENCE_PARALLEL" ] && echo "Caught USE_SP: $USE_SEQUENCE_PARALLEL from env" || USE_SEQUENCE_PARALLEL=1 + if [[ ${PPSIZE} > 1 ]]; then # && ${MPSIZE}==${WORLD_SIZE} ]]; + MPSIZE=$(( WORLD_SIZE / PPSIZE )) + echo "Re-setting MPSIZE to ${WORLD_SIZE} / ${PPSIZE} = $(( WORLD_SIZE / PPSIZE ))" + echo "MPSIZE: $MPSIZE" + # MPSIZE="${WORLD_SIZE}/" + fi export SPSIZE="${SPSIZE}" export MPSIZE="${MPSIZE}" export ZERO_STAGE="${ZERO_STAGE}" @@ -109,7 +118,7 @@ else # exit 1 fi # ------------------------------------------------------------------------ - +# echo "####################################################" echo "USING: ${SP_TYPE}" echo "SPSIZE: ${SPSIZE}" @@ -137,8 +146,14 @@ fi # [ "${GLOBAL_BATCH:-${GLOBAL_BATCH}}" == 0 ] && GLOBAL_BATCH=1 || echo "GLOBAL_BATCH: ${GLOBAL_BATCH}" export GLOBAL_BATCH="$GLOBAL_BATCH" +DPSIZE=$(( $WORLD_SIZE / $PPSIZE / $MPSIZE )) + +# echo "@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@" +# echo "@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@" + echo "--------------------------------" echo "GLOBAL_BATCH=${GLOBAL_BATCH}" +echo "USING DPSIZE: ${DPSIZE}" echo "--------------------------------" # ┏━━━━━━━━━━━━┓ @@ -194,7 +209,7 @@ fi if [[ $DDP_IMPL == 'FSDP' ]]; then RUN_STR="FSDP_${RUN_STR}" fi -if [[ $USE_ACTIVATION_CHECKPOINTING == 1 ]] ;then +if [[ $USE_ACTIVATION_CHECKPOINTING == 1 ]]; then RUN_STR="actCkpt_${RUN_STR}" fi if [[ $USE_SEQUENCE_PARALLEL == 1 ]] ; then From a8454935fabdbe1e88dcba54204e61a509ec7c56 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 14:26:49 -0500 Subject: [PATCH 009/268] Update `ALCF/launch.sh` --- ALCF/launch.sh | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/ALCF/launch.sh b/ALCF/launch.sh index dc7a08d991..affab7073e 100755 --- a/ALCF/launch.sh +++ b/ALCF/launch.sh @@ -103,7 +103,7 @@ fullNode() { # ┃ Use all available GPUs on all available nodes ┃ # ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ elasticDistributed() { - if [[ "$(hostname)==theta*" || "$(hostname)==x3*" ]]; then + if [[ $(hostname) == theta* || $(hostname) == x3* ]]; then if [[ $(hostname) == theta* ]]; then echo "Setting up ThetaGPU from $(hostname)" HOSTFILE="${COBALT_NODEFILE}" @@ -128,10 +128,10 @@ elasticDistributed() { "${gpt_args}" "${ds_args}" ) - elif [[ "$(hostname)==nid*" || "$(hostname)==login*" ]]; then + elif [[ $(hostname) == nid* || $(hostname) == login* ]]; then echo "Setting up from Perlmutter on $(hostname)" - [ "$(hostname)==nid*" ] && NHOSTS="$SLURM_NNODES" || NHOSTS=1 - [ "$(hostname)==nid*" ] && export MACHINE="perlmutter" || export MACHINE="NERSC" + [ $(hostname) == nid* ] && NHOSTS="$SLURM_NNODES" || NHOSTS=1 + [ $(hostname) == nid* ] && export MACHINE="perlmutter" || export MACHINE="NERSC" NGPU_PER_HOST=$(nvidia-smi -L | wc -l) # NGPU_PER_HOST="$SLURM_GPUS_ON_NODE" NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" From f5c8f991443dc9b9cb55fb3dc6c7edf26c517c38 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 14:27:14 -0500 Subject: [PATCH 010/268] Update `ALCF/setup.sh` --- ALCF/setup.sh | 27 +++++++++++++++------------ 1 file changed, 15 insertions(+), 12 deletions(-) diff --git a/ALCF/setup.sh b/ALCF/setup.sh index b8918df147..94416982b8 100755 --- a/ALCF/setup.sh +++ b/ALCF/setup.sh @@ -126,7 +126,7 @@ function setupMPI() { } function condaPolaris() { - if [[ "$(hostname)" == x3* ]]; then + if [[ $(hostname) == x3* ]]; then DATE_STR="2023-10-04" [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}" [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" @@ -136,10 +136,12 @@ function condaPolaris() { } function condaThetaGPU() { - if [[ "$(hostname)" == theta* ]]; then + if [[ $(hostname) == theta* ]]; then DATE_STR="2023-01-11" - [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}" - [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" + [ "${CONDA_EXE}" ] && echo "Caught CONDA_EXE: ${CONDA_EXE}" || loadCondaEnv "${DATE_STR}" + [ "${VIRTUAL_ENV}" ] && echo "Caught VIRTUAL_ENV: ${VIRTUAL_ENV}" || setupVenv "${DATE_STR}" + # [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}" + # [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" else echo "Skipping condaThetaGPU() on $(hostname)" fi @@ -151,8 +153,8 @@ function setupThetaGPU() { if [[ $(hostname) == theta* ]]; then setupMPI DATE_STR="2023-01-11" - [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}" || echo "Caught CONDA_EXE: ${CONDA_EXE}" - [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" || echo "Caught VIRTUAL_ENV: ${VIRTUAL_ENV}" + [ "${CONDA_EXE}" ] && echo "Caught CONDA_EXE: ${CONDA_EXE}" || loadCondaEnv "${DATE_STR}" + [ "${VIRTUAL_ENV}" ] && echo "Caught VIRTUAL_ENV: ${VIRTUAL_ENV}" || setupVenv "${DATE_STR}" else echo "Skipping setupThetaGPU() on $(hostname)" fi @@ -161,23 +163,24 @@ function setupThetaGPU() { function setupPolaris() { export LAB="ALCF" export MACHINE="Polaris" - if [[ "$(hostname)" == x3* ]]; then + if [[ $(hostname) == x3* ]]; then # SETUP MPI -------------------------------- setupMPI # SETUP Python -------------------------------- DATE_STR="2023-09-29" - [ "${CONDA_EXE}" ] || loadCondaEnv "${DATE_STR}-unstable" || echo "Caught CONDA_EXE: ${CONDA_EXE}" - [ "${VIRTUAL_ENV}" ] || setupVenv "${DATE_STR}" || echo "Caught VIRTUAL_ENV: ${VIRTUAL_ENV}" + [ "${CONDA_EXE}" ] && echo "Caught CONDA_EXE: ${CONDA_EXE}" || loadCondaEnv "${DATE_STR}-unstable" + [ "${VIRTUAL_ENV}" ] && echo "Caught VIRTUAL_ENV: ${VIRTUAL_ENV}" || setupVenv "${DATE_STR}" else echo "Skipping setupPolaris() on $(hostname)" fi } function setupALCF() { + # if [[ $(hostname -s) == theta* || $(hostname -s) == x3* ]]; then echo "True" ; else echo "False" ; fi if [[ $(hostname) == theta* || $(hostname) == x3* ]]; then setupMPI - [ "$(hostname)==theta*" ] && setupThetaGPU || echo "Skipping setupThetaGPU from $(hostname)" - [ "$(hostname)==x3*" ] && setupPolaris || echo "Skipping setupPolaris from $(hostname)" + [ $(hostname) == theta* ] && setupThetaGPU || echo "Skipping setupThetaGPU from $(hostname)" + [ $(hostname) == x3* ] && setupPolaris || echo "Skipping setupPolaris from $(hostname)" else echo "Skipping setupALCF() on $(hostname)" fi @@ -223,7 +226,7 @@ function setupMachine() { setupALCF [ "${HOSTNAME}==theta*" ] && condaThetaGPU [ "${HOSTNAME}==x3*" ] && condaPolaris - elif [[ "${HOSTNAME}== nid*" || "${HOSTNAME}== login*" ]]; then + elif [[ $(hostname) == nid* || $(hostname) == login* ]]; then export LAB="NERSC" setupPerlmutter [ "${HOSTNAME}==login*" ] && setupPerlmutter From 64fd153e0b26e0f78417bc1f617fa872f9c3c208 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 14:05:56 -0700 Subject: [PATCH 011/268] Update `pretrain_gpt.py` --- pretrain_gpt.py | 143 ++++++++++++++++++++++++++---------------------- 1 file changed, 78 insertions(+), 65 deletions(-) diff --git a/pretrain_gpt.py b/pretrain_gpt.py index 272f05318b..63b46ed0d9 100644 --- a/pretrain_gpt.py +++ b/pretrain_gpt.py @@ -39,7 +39,7 @@ import torch.nn.functional as F # from ezpz import get_logger -from ezpz.dist import setup_torch, get_world_size +from ezpz.dist import setup_torch, get_world_size, setup_wandb RANK = setup_torch( backend='deepspeed', @@ -48,6 +48,19 @@ WORLD_SIZE = get_world_size() LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" +if RANK == 0: + print(f"Setting up W&B from: {RANK}") + project_name = ( + os.environ.get( + 'WB_PROJECT', + os.environ.get( + 'WANDB_PROJECT', + 'GenSLM-Megatron-DS' + ), + ) + ) + setup_wandb(project_name=project_name) + # os.environ[''] # wblogger = logging.getLogger("wandb") @@ -62,68 +75,68 @@ # log.critical(f"Setting up W&B from rank: {RANK} with {wb_project_name}") -def setup_wandb(project_name: Optional[str] = None): - print(f"Setting up W&B from: {RANK}") - project_name = ( - os.environ.get('WB_PROJECT', 'GenSLM-Megatron-DS') - if project_name is None else project_name - ) - print(f"Setting up wandb from rank: {RANK}") - print(f"Using: WB PROJECT: {project_name}") - # if get_rank() == 0: - # tensorboard_dir = args.tensorboard_dir - tensorboard_dir = None - # if config is None: - tensorboard_dir = os.environ.get('TENSORBOARD_DIR', None) - # else: - # tensorboard_dir = ( - # config.get( - # 'tensorboard_dir', - # None, # os.getcwd() - # ) - # ) - if tensorboard_dir is not None: - print(f'Patching tensorboard from {tensorboard_dir}') - wandb.tensorboard.patch(root_logdir=tensorboard_dir) - # wbrun_id = wandb.util.generate_id() - current_time = time.time() - # local_time = time.localtime(current_time) - # if wandb.run is None: - wandb.init( - resume='allow', - sync_tensorboard=(tensorboard_dir is not None), # True, - project=(project_name if project_name is not None else None), - # dir=(tensorboard_dir if tensorboard_dir is not None else None), - ) - assert wandb.run is not None - print(f"W&B RUN: [{wandb.run.name}]({wandb.run.url})") - wandb.run.config.update({'current_time': current_time}) - model_size = os.environ.get('MODEL_SIZE', None) - wandb.run.config.update({'world_size': get_world_size()}) - # if config is not None: - # wandb.run.config.update(config) - env = { - k: v for k, v in dict(os.environ).items() - if not k.startswith('_ModuleTable') - } - _ = env.pop('LS_COLORS', None) - _ = env.pop('PS1', None) - wandb.run.config.update({'env': env}) - hostname = socket.gethostbyaddr(socket.gethostname())[0] - if hostname.startswith('theta'): - wandb.run.config.update({'machine': 'ThetaGPU'}) - elif hostname.startswith('x3'): - wandb.run.config.update({'machine': 'Polaris'}) - elif hostname.startswith('x1'): - wandb.run.config.update({'machine': 'Sunspot'}) - elif hostname.startswith('nid'): - wandb.run.config.update({'machine': 'Perlmutter'}) - elif hostname.startswith('login'): - wandb.run.config.update({'machine': 'NERSC'}) - else: - wandb.run.config.update({'machine': hostname}) - if model_size is not None: - wandb.run.config.update({'MODEL_SIZE': model_size}) +# def setup_wandb(project_name: Optional[str] = None): +# print(f"Setting up W&B from: {RANK}") +# project_name = ( +# os.environ.get('WB_PROJECT', 'GenSLM-Megatron-DS') +# if project_name is None else project_name +# ) +# print(f"Setting up wandb from rank: {RANK}") +# print(f"Using: WB PROJECT: {project_name}") +# # if get_rank() == 0: +# # tensorboard_dir = args.tensorboard_dir +# tensorboard_dir = None +# # if config is None: +# tensorboard_dir = os.environ.get('TENSORBOARD_DIR', None) +# # else: +# # tensorboard_dir = ( +# # config.get( +# # 'tensorboard_dir', +# # None, # os.getcwd() +# # ) +# # ) +# if tensorboard_dir is not None: +# print(f'Patching tensorboard from {tensorboard_dir}') +# wandb.tensorboard.patch(root_logdir=tensorboard_dir) +# # wbrun_id = wandb.util.generate_id() +# current_time = time.time() +# # local_time = time.localtime(current_time) +# # if wandb.run is None: +# wandb.init( +# resume='allow', +# sync_tensorboard=(tensorboard_dir is not None), # True, +# project=(project_name if project_name is not None else None), +# # dir=(tensorboard_dir if tensorboard_dir is not None else None), +# ) +# assert wandb.run is not None +# print(f"W&B RUN: [{wandb.run.name}]({wandb.run.url})") +# wandb.run.config.update({'current_time': current_time}) +# model_size = os.environ.get('MODEL_SIZE', None) +# wandb.run.config.update({'world_size': get_world_size()}) +# # if config is not None: +# # wandb.run.config.update(config) +# env = { +# k: v for k, v in dict(os.environ).items() +# if not k.startswith('_ModuleTable') +# } +# _ = env.pop('LS_COLORS', None) +# _ = env.pop('PS1', None) +# wandb.run.config.update({'env': env}) +# hostname = socket.gethostbyaddr(socket.gethostname())[0] +# if hostname.startswith('theta'): +# wandb.run.config.update({'machine': 'ThetaGPU'}) +# elif hostname.startswith('x3'): +# wandb.run.config.update({'machine': 'Polaris'}) +# elif hostname.startswith('x1'): +# wandb.run.config.update({'machine': 'Sunspot'}) +# elif hostname.startswith('nid'): +# wandb.run.config.update({'machine': 'Perlmutter'}) +# elif hostname.startswith('login'): +# wandb.run.config.update({'machine': 'NERSC'}) +# else: +# wandb.run.config.update({'machine': hostname}) +# if model_size is not None: +# wandb.run.config.update({'MODEL_SIZE': model_size}) def model_provider(pre_process=True, post_process=True): @@ -476,8 +489,8 @@ def git_ds_info(): def main(): - if RANK == 0: - setup_wandb() + # if RANK == 0: + # setup_wandb() model = pretrain( train_valid_test_datasets_provider, From a2fabf2e8d3b628ec0f7761b90293dcc83097d96 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 15:01:50 -0700 Subject: [PATCH 012/268] Clean up data paths in `ALCF/args.sh` --- ALCF/args.sh | 43 ++++++++++++++++++++++++++++++------------- 1 file changed, 30 insertions(+), 13 deletions(-) diff --git a/ALCF/args.sh b/ALCF/args.sh index 3740cc067a..fad650b1dd 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -159,22 +159,39 @@ echo "--------------------------------" # ┏━━━━━━━━━━━━┓ # ┃ Data paths ┃ # ┗━━━━━━━━━━━━┛ -[ "$(hostname)==login*" ] && DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" -[ "$(hostname)==nid*" ] && DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" -# [ "$(hostname)==theta*" ] && DATA_PARENT="/lus/eagle/projects/datasets/BookCorpusDataset" -[ "$(hostname)==theta*" ] && DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" -[ "$(hostname)==x3*" ] && DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" -# "/lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" -# /lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k/dataset/genslm_subsample_200k_sequence_document" -# [ "$(hostname)==x3*" ] && DATA_PARENT="/lus/eagle/projects/datasets/BookCorpusDataset" -# /lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" -# /lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k/dataset/genslm_subsample_200k_sequence_document.bin - -# DATA_PATH=/lus/grand/projects/datascience/vsastry/genslm_subsample_200k_sequence_document/genslm_subsample_200k_sequence_document +if [[ $(hostname) == nid* || $(hostname) == login* ]]; then + DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" + DATA_TYPE="BookCorpusDataset_text_document" +elif [[ $(hostname) == theta* || $(hostname) == x3* ]]; then + DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" + DATA_TYPE="genslm_subsample_200k_sequence_document" +else + echo "Unable to determine DATA_PARENT for $(hostname)." + echo "Exiting!" + exit 1 +fi + DATA_DIR="${DATA_PARENT}/dataset" -DATA_PATH="${DATA_DIR}/genslm_subsample_200k_sequence_document" +DATA_PATH="${DATA_DIR}/${DATA_TYPE}" VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" +# # +# [ "$(hostname)==login*" ] && DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" +# [ "$(hostname)==nid*" ] && DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" +# # [ "$(hostname)==theta*" ] && DATA_PARENT="/lus/eagle/projects/datasets/BookCorpusDataset" +# [ "$(hostname)==theta*" ] && DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" +# [ "$(hostname)==x3*" ] && DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" +# # "/lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" +# # /lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k/dataset/genslm_subsample_200k_sequence_document" +# # [ "$(hostname)==x3*" ] && DATA_PARENT="/lus/eagle/projects/datasets/BookCorpusDataset" +# # /lus/grand/projects/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DS-Benchmarking" +# # /lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k/dataset/genslm_subsample_200k_sequence_document.bin +# +# # DATA_PATH=/lus/grand/projects/datascience/vsastry/genslm_subsample_200k_sequence_document/genslm_subsample_200k_sequence_document +# DATA_DIR="${DATA_PARENT}/dataset" +# DATA_PATH="${DATA_DIR}/genslm_subsample_200k_sequence_document" +# VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" +# MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" # ┏━━━━━━━━━━━━━━━━━━━┓ # ┃ FILE I/O SETTINGS ┃ From 416fb9cb0da3d6f09f4184dbcf0f70461de4f15f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 15:02:19 -0700 Subject: [PATCH 013/268] Updating launch vars in `ALCF/launch.sh` on Perlmutter --- ALCF/launch.sh | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/ALCF/launch.sh b/ALCF/launch.sh index affab7073e..ebd1b43f1e 100755 --- a/ALCF/launch.sh +++ b/ALCF/launch.sh @@ -130,8 +130,10 @@ elasticDistributed() { ) elif [[ $(hostname) == nid* || $(hostname) == login* ]]; then echo "Setting up from Perlmutter on $(hostname)" - [ $(hostname) == nid* ] && NHOSTS="$SLURM_NNODES" || NHOSTS=1 - [ $(hostname) == nid* ] && export MACHINE="perlmutter" || export MACHINE="NERSC" + NHOSTS=${SLURM_NNODES-1} + MACHINE="Perlmutter" + # [ $(hostname) == nid* ] && NHOSTS="$SLURM_NNODES" || NHOSTS=1 + # [ $(hostname) == nid* ] && export MACHINE="perlmutter" || export MACHINE="NERSC" NGPU_PER_HOST=$(nvidia-smi -L | wc -l) # NGPU_PER_HOST="$SLURM_GPUS_ON_NODE" NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" From 3cd7eccc9df9817874824b3fbd232385c1df3d08 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 18:50:33 -0700 Subject: [PATCH 014/268] Create `Perlmutter` branch Changes: - `ALCF/args.sh` - `ALCF/launch.sh` - `ALCF/setup.sh` to simplify setup and launching with `srun` on Perlmutter @ NERSC --- ALCF/args.sh | 1 + ALCF/launch.sh | 43 +++++++++++++++++++++++++++++-------- ALCF/setup.sh | 57 +++++++++++++++++++++++++++++++------------------- 3 files changed, 71 insertions(+), 30 deletions(-) diff --git a/ALCF/args.sh b/ALCF/args.sh index fad650b1dd..62b4c6494f 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -503,6 +503,7 @@ elif [[ "${USE_FLASH_ATTN_TRITON}" ]]; then fi if [[ "$USE_SEQUENCE_PARALLEL" == 1 ]]; then + export CUDA_DEVICE_MAX_CONNECTIONS=1 gpt_args+=( "--sequence-parallel" ) diff --git a/ALCF/launch.sh b/ALCF/launch.sh index ebd1b43f1e..5790727f7d 100755 --- a/ALCF/launch.sh +++ b/ALCF/launch.sh @@ -99,6 +99,21 @@ fullNode() { launchJob "$@" 2>&1 | tee "${OUTPUT_LOG}" } + +function setupSrun() { + if [[ $(hostname) == login* || $(hostname) == nid* ]]; then + export NODELIST="${SLURM_JOB_NODELIST:-$(hostname)}" + export MACHINE="Perlmutter" + export NHOSTS="${SLURM_NNODES:-1}" + export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" + export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + export SRUN_EXEC="srun -N ${NHOSTS} -n ${NGPUS} -l -u" + else + echo "Skipping setupSrun() on $(hostname)" + fi +} + + # ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ # ┃ Use all available GPUs on all available nodes ┃ # ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ @@ -130,26 +145,36 @@ elasticDistributed() { ) elif [[ $(hostname) == nid* || $(hostname) == login* ]]; then echo "Setting up from Perlmutter on $(hostname)" - NHOSTS=${SLURM_NNODES-1} + # NHOSTS=${SLURM_NNODES-1} MACHINE="Perlmutter" + setupPerlmutter + setupSrun + echo "SRUN_EXEC: ${SRUN_EXEC}" # [ $(hostname) == nid* ] && NHOSTS="$SLURM_NNODES" || NHOSTS=1 # [ $(hostname) == nid* ] && export MACHINE="perlmutter" || export MACHINE="NERSC" - NGPU_PER_HOST=$(nvidia-smi -L | wc -l) + # NGPU_PER_HOST=$(nvidia-smi -L | wc -l) # NGPU_PER_HOST="$SLURM_GPUS_ON_NODE" - NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + # NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" # export MACHINE="perlmutter" - export MASTER_ADDR="127.0.0.1" - export MASTER_PORT="5432" + export MASTER_ADDR="$SLURMD_NODENAME" + # export MASTER_PORT="5432" EXEC_STR=( - "srun" - "-N ${NHOSTS}" - "-n ${NGPUS}" - "-l -u" + "${SRUN_EXEC}" "$(which python3)" "${MAIN}" "${gpt_args}" "${ds_args}" ) + # EXEC_STR=( + # "srun" + # "-N ${NHOSTS}" + # "-n ${NGPUS}" + # "-l -u" + # "$(which python3)" + # "${MAIN}" + # "${gpt_args}" + # "${ds_args}" + # ) else echo "Unexpected hostname $(hostname)" fi diff --git a/ALCF/setup.sh b/ALCF/setup.sh index 94416982b8..47b2d17667 100755 --- a/ALCF/setup.sh +++ b/ALCF/setup.sh @@ -176,7 +176,6 @@ function setupPolaris() { } function setupALCF() { - # if [[ $(hostname -s) == theta* || $(hostname -s) == x3* ]]; then echo "True" ; else echo "False" ; fi if [[ $(hostname) == theta* || $(hostname) == x3* ]]; then setupMPI [ $(hostname) == theta* ] && setupThetaGPU || echo "Skipping setupThetaGPU from $(hostname)" @@ -186,30 +185,45 @@ function setupALCF() { fi } + +function setupSrun() { + if [[ $(hostname) == login* || $(hostname) == nid* ]]; then + export NHOSTS="${SLURM_NNODES:-1}" + export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" + export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + export SRUN_EXEC="srun -N ${NHOSTS} -n ${NGPUS} -l -u" + else + echo "Skipping setupSrun() on $(hostname)" + fi +} + # ┏━━━━━━━┓ # ┃ NERSC ┃ # ┗━━━━━━━┛ function setupPerlmutter() { if [[ $(hostname) == login* || $(hostname) == nid* ]]; then module load libfabric cudatoolkit pytorch/2.0.1 - if [[ $(hostname) == login* ]]; then - export MACHINE="NERSC" - module load pytorch/2.0.1 - export NHOSTS=1 - export NGPU_PER_HOST=1 - export NGPUS=1 - # echo "$(hostname)" > "${HERE}/hostfile" - elif [[ $(hostname) == nid* ]]; then - export NODELIST="${SLURM_JOB_NODELIST:-$(hostname)}" - export NODE_RANK=0 - export CUDA_DEVICE_MAX_CONNECTIONS=1 - export MACHINE="PERLMUTTER" - export NHOSTS="${SLURM_NNODES:-1}" - export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" - export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" - else - echo "Unexpected $(hostname) on NERSC" - fi + [ $SLURM_JOB_ID ] \ + && echo "Caught SLURM_JOB_ID: ${SLURM_JOB_ID}" \ + || echo "!!!!!! Running without SLURM allocation !!!!!!!!" + # if [[ $(hostname) == login* ]]; then + # export MACHINE="NERSC" + # module load pytorch/2.0.1 + # export NHOSTS=1 + # export NGPU_PER_HOST=1 + # export NGPUS=1 + # # echo "$(hostname)" > "${HERE}/hostfile" + # elif [[ $(hostname) == nid* ]]; then + # export NODE_RANK=0 + export NODELIST="${SLURM_JOB_NODELIST:-$(hostname)}" + # export CUDA_DEVICE_MAX_CONNECTIONS=1 + export MACHINE="Perlmutter" + export NHOSTS="${SLURM_NNODES:-1}" + export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" + export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + # else + # echo "Unexpected $(hostname) on NERSC" + # fi echo "+++++++++++++++++++++++++++++++++++" echo "Using python: $(which python3)" echo "+++++++++++++++++++++++++++++++++++" @@ -228,9 +242,10 @@ function setupMachine() { [ "${HOSTNAME}==x3*" ] && condaPolaris elif [[ $(hostname) == nid* || $(hostname) == login* ]]; then export LAB="NERSC" + setupSrun setupPerlmutter - [ "${HOSTNAME}==login*" ] && setupPerlmutter - [ "${HOSTNAME}==nid*" ] && setupPerlmutter + # [ "${HOSTNAME}==login*" ] && setupPerlmutter + # [ "${HOSTNAME}==nid*" ] && setupPerlmutter else echo "Unexpected hostname: $(hostname)" fi From 3108af8c2b2d6d7e741e9c08950d2bfff1a51b32 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 22:13:24 -0500 Subject: [PATCH 015/268] Respect `WANDB_MODE=disabled` --- ALCF/args.sh | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/ALCF/args.sh b/ALCF/args.sh index 62b4c6494f..b5f018de98 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -279,6 +279,10 @@ CPU_OPTIM=" --cpu-optimizer" # OFFLOAD_DEVICE="none" # CPU_OPTIM=" " + +[ "${WANDB_MODE}" == "disabled" ] && WANDB_ENABLE="false" || WANDB_ENABLE="true" +echo "WANDB_ENABLE: ${WANDB_ENABLE}" + # ┏━━━━━━━━━━━━━━━━━━┓ # ┃ DeepSpeed Config ┃ # ┗━━━━━━━━━━━━━━━━━━┛ @@ -346,7 +350,7 @@ if [[ $ZERO_STAGE == "3" ]] ; then "debug": false }, "wandb": { -"enabled": true, +"enabled": $WANDB_ENABLE, "project": "GenSLM-Megatron-DS" } } @@ -403,7 +407,7 @@ else "debug": false }, "wandb": { -"enabled": true, +"enabled": $WANDB_ENABLE, "project": "GenSLM-Megatron-DS" } } From ba38d103bf342d78a75f061d189d7885f859d09d Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 22:13:48 -0500 Subject: [PATCH 016/268] Fix `hostname` check in `ALCF/setup.sh` --- ALCF/setup.sh | 19 ++++++++++++++----- 1 file changed, 14 insertions(+), 5 deletions(-) diff --git a/ALCF/setup.sh b/ALCF/setup.sh index 47b2d17667..d0fe4dadf9 100755 --- a/ALCF/setup.sh +++ b/ALCF/setup.sh @@ -175,17 +175,26 @@ function setupPolaris() { fi } + function setupALCF() { if [[ $(hostname) == theta* || $(hostname) == x3* ]]; then setupMPI - [ $(hostname) == theta* ] && setupThetaGPU || echo "Skipping setupThetaGPU from $(hostname)" - [ $(hostname) == x3* ] && setupPolaris || echo "Skipping setupPolaris from $(hostname)" + if [[ $(hostname) == theta* ]]; then + echo "Setting up ThetaGPU from $(hostname)" + setupThetaGPU + elif [[ $(hostname) == x3* ]]; then + echo "Setting up Polaris from $(hostname)" + setupPolaris + else + echo "Unknown hostname $(hostname) in setupALCF()" + fi else echo "Skipping setupALCF() on $(hostname)" fi } + function setupSrun() { if [[ $(hostname) == login* || $(hostname) == nid* ]]; then export NHOSTS="${SLURM_NNODES:-1}" @@ -238,8 +247,8 @@ function setupMachine() { if [[ $(hostname) == theta* || $(hostname) == x3* ]]; then export LAB="ALCF" setupALCF - [ "${HOSTNAME}==theta*" ] && condaThetaGPU - [ "${HOSTNAME}==x3*" ] && condaPolaris + # [ "${HOSTNAME}==theta*" ] && condaThetaGPU + # [ "${HOSTNAME}==x3*" ] && condaPolaris elif [[ $(hostname) == nid* || $(hostname) == login* ]]; then export LAB="NERSC" setupSrun @@ -255,7 +264,7 @@ function setupMachine() { # ┃ SETUP CONDA + MPI ENVIRONMENT @ ALCF ┃ # ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ function setup() { - export NCCL_DEBUG=warn + export NCCL_DEBUG=info # TORCH_EXTENSIONS_DIR="${HERE}/.cache/torch_extensions" export WANDB_CACHE_DIR="./cache/wandb" setupMachine From 3fb5c8c99355b8e64f490ff4ba26dbc8c1fbd067 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 15 Oct 2023 22:14:18 -0500 Subject: [PATCH 017/268] Respect `WANDB_MODE=disabled` in `pretrain_gpt.py` --- pretrain_gpt.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/pretrain_gpt.py b/pretrain_gpt.py index 63b46ed0d9..b96cb4e25e 100644 --- a/pretrain_gpt.py +++ b/pretrain_gpt.py @@ -10,6 +10,7 @@ from functools import partial from megatron import get_args from megatron import print_rank_0 +from rich import print from megatron import get_timers from megatron import get_tokenizer from megatron.core import mpu, tensor_parallel @@ -48,8 +49,10 @@ WORLD_SIZE = get_world_size() LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" -if RANK == 0: - print(f"Setting up W&B from: {RANK}") +WANDB_MODE = os.environ.get('WANDB_MODE', None) +DISABLE_WANDB = WANDB_MODE is not None and str(WANDB_MODE).lower() == 'disabled' + +if RANK == 0 and not DISABLE_WANDB: project_name = ( os.environ.get( 'WB_PROJECT', @@ -59,6 +62,9 @@ ), ) ) + print('--------------------------------------------------') + print(f"Setting up W&B from: {RANK} with {project_name}") + print('--------------------------------------------------') setup_wandb(project_name=project_name) From c303a749c1495ee84729a17997421d592e55b796 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 17 Oct 2023 19:29:24 -0500 Subject: [PATCH 018/268] (re-)set `NCCL_DEBUG=warn` --- ALCF/setup.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ALCF/setup.sh b/ALCF/setup.sh index d0fe4dadf9..542e4d2358 100755 --- a/ALCF/setup.sh +++ b/ALCF/setup.sh @@ -264,7 +264,7 @@ function setupMachine() { # ┃ SETUP CONDA + MPI ENVIRONMENT @ ALCF ┃ # ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ function setup() { - export NCCL_DEBUG=info + export NCCL_DEBUG=warn # TORCH_EXTENSIONS_DIR="${HERE}/.cache/torch_extensions" export WANDB_CACHE_DIR="./cache/wandb" setupMachine From 10036071c905d6677052442693509ad2984a153f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 17 Oct 2023 19:30:07 -0500 Subject: [PATCH 019/268] Change `--num-workers` from `1` to `0` --- ALCF/args.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ALCF/args.sh b/ALCF/args.sh index b5f018de98..08d3d8fcd2 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -452,7 +452,7 @@ gpt_args=( "--max-position-embeddings ${SEQ_LEN}" "--train-iters 10" "--lr-decay-iters 320000" - "--num-workers 1" + "--num-workers 0" "$DATA_LOAD_ARGS" "--data-impl mmap" "--split 949,50,1" From 01c57126d02287b35a0ec756bcd882bfdc4bc9d8 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 22 Oct 2023 14:03:48 -0700 Subject: [PATCH 020/268] Update slurm commands in `ALCF/launch.sh` --- ALCF/launch.sh | 30 ++++++++++++------------------ 1 file changed, 12 insertions(+), 18 deletions(-) diff --git a/ALCF/launch.sh b/ALCF/launch.sh index 5790727f7d..f7ba636836 100755 --- a/ALCF/launch.sh +++ b/ALCF/launch.sh @@ -100,7 +100,7 @@ fullNode() { } -function setupSrun() { +function setupSrunOld() { if [[ $(hostname) == login* || $(hostname) == nid* ]]; then export NODELIST="${SLURM_JOB_NODELIST:-$(hostname)}" export MACHINE="Perlmutter" @@ -113,6 +113,17 @@ function setupSrun() { fi } +function setupSrun() { + if [[ $(hostname) == login* || $(hostname) == nid* ]]; then + export NHOSTS="${SLURM_NNODES:-1}" + export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" + export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + export SRUN_EXEC="srun --gpus ${NGPUS} --gpus-per-node ${NGPU_PER_HOST} -N ${NHOSTS} -n ${NGPUS} -l -u --verbose" + else + echo "Skipping setupSrun() on $(hostname)" + fi +} + # ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ # ┃ Use all available GPUs on all available nodes ┃ @@ -150,14 +161,7 @@ elasticDistributed() { setupPerlmutter setupSrun echo "SRUN_EXEC: ${SRUN_EXEC}" - # [ $(hostname) == nid* ] && NHOSTS="$SLURM_NNODES" || NHOSTS=1 - # [ $(hostname) == nid* ] && export MACHINE="perlmutter" || export MACHINE="NERSC" - # NGPU_PER_HOST=$(nvidia-smi -L | wc -l) - # NGPU_PER_HOST="$SLURM_GPUS_ON_NODE" - # NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" - # export MACHINE="perlmutter" export MASTER_ADDR="$SLURMD_NODENAME" - # export MASTER_PORT="5432" EXEC_STR=( "${SRUN_EXEC}" "$(which python3)" @@ -165,16 +169,6 @@ elasticDistributed() { "${gpt_args}" "${ds_args}" ) - # EXEC_STR=( - # "srun" - # "-N ${NHOSTS}" - # "-n ${NGPUS}" - # "-l -u" - # "$(which python3)" - # "${MAIN}" - # "${gpt_args}" - # "${ds_args}" - # ) else echo "Unexpected hostname $(hostname)" fi From beef50c8b0dc03b8c7f495726789ad04967176d1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 22 Oct 2023 16:04:37 -0500 Subject: [PATCH 021/268] Update `ALCF/launch.sh` to respect `HOSTFILE` --- ALCF/launch.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ALCF/launch.sh b/ALCF/launch.sh index f7ba636836..4c1a6ba0e0 100755 --- a/ALCF/launch.sh +++ b/ALCF/launch.sh @@ -132,10 +132,10 @@ elasticDistributed() { if [[ $(hostname) == theta* || $(hostname) == x3* ]]; then if [[ $(hostname) == theta* ]]; then echo "Setting up ThetaGPU from $(hostname)" - HOSTFILE="${COBALT_NODEFILE}" + HOSTFILE="${HOSTFILE:-${COBALT_NODEFILE}}" elif [[ $(hostname) == x3* ]]; then echo "Setting up Polaris from $(hostname)" - HOSTFILE="${PBS_NODEFILE}" + HOSTFILE="${HOSFILE:-${PBS_NODEFILE}}" else echo "Unknown hostname $(hostname)" exit 1 From b6c536c4cfd364395fab4b3cd8ea150d6a325519 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sun, 22 Oct 2023 16:04:53 -0500 Subject: [PATCH 022/268] Update `ALCF/setup.sh` to respect `HOSTFILE` --- ALCF/setup.sh | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/ALCF/setup.sh b/ALCF/setup.sh index 542e4d2358..5259ea03a0 100755 --- a/ALCF/setup.sh +++ b/ALCF/setup.sh @@ -34,8 +34,8 @@ function loadCondaEnv() { function thetagpuMPI() { if [[ $(hostname) == theta* ]]; then - export HOSTFILE="${COBALT_NODEFILE}" - NHOSTS=$(wc -l < "${COBALT_NODEFILE}") + export HOSTFILE="${HOSTFILE:-${COBALT_NODEFILE}}" + NHOSTS=$(wc -l < "${HOSTFILE}") NGPU_PER_HOST=$(nvidia-smi -L | wc -l) NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) NVME_PATH="/raid/scratch/" @@ -78,8 +78,8 @@ function thetagpuMPI() { function polarisMPI() { if [[ $(hostname) == x3* ]]; then - export HOSTFILE="${PBS_NODEFILE}" - export NHOSTS=$(wc -l < "${PBS_NODEFILE}") + export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" + export NHOSTS=$(wc -l < "${HOSTFILE}") export NGPU_PER_HOST=$(nvidia-smi -L | wc -l) export NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) export MPI_COMMAND=$(which mpiexec) From 39a484d2ea04c2b3714adc15ef2fe363f841e77f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 23 Oct 2023 09:55:00 -0500 Subject: [PATCH 023/268] Add `GPT1T_*L` configs to `ALCF/model.sh` --- ALCF/model.sh | 76 +++++++++++++++++++++++++++++++++++++++++++++------ 1 file changed, 67 insertions(+), 9 deletions(-) diff --git a/ALCF/model.sh b/ALCF/model.sh index c41a908203..d69ea8033a 100755 --- a/ALCF/model.sh +++ b/ALCF/model.sh @@ -258,27 +258,85 @@ A_NLAYERS[$MODEL_145B_KEY]=80 A_HIDDEN[$MODEL_145B_KEY]=12288 A_ATEN_HEADS[$MODEL_145B_KEY]=96 + + +MODEL_1T_HIDDEN=25600 +MODEL_1T_ATEN_HEADS=160 MODEL_1T_1L_KEY="GPT1T_1L" A_NLAYERS[$MODEL_1T_1L_KEY]=1 -A_HIDDEN[$MODEL_1T_1L_KEY]=25600 -A_ATEN_HEADS[$MODEL_1T_1L_KEY]=160 +A_HIDDEN[$MODEL_1T_1L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_1L_KEY]="${MODEL_1T_ATEN_HEADS}" MODEL_1T_2L_KEY="GPT1T_2L" A_NLAYERS[$MODEL_1T_2L_KEY]=2 -A_HIDDEN[$MODEL_1T_2L_KEY]=25600 -A_ATEN_HEADS[$MODEL_1T_2L_KEY]=160 +A_HIDDEN[$MODEL_1T_2L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_2L_KEY]="${MODEL_1T_ATEN_HEADS}" MODEL_1T_4L_KEY="GPT1T_4L" A_NLAYERS[$MODEL_1T_4L_KEY]=4 -A_HIDDEN[$MODEL_1T_4L_KEY]=25600 -A_ATEN_HEADS[$MODEL_1T_4L_KEY]=160 +A_HIDDEN[$MODEL_1T_4L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_4L_KEY]="${MODEL_1T_ATEN_HEADS}" MODEL_1T_8L_KEY="GPT1T_8L" A_NLAYERS[$MODEL_1T_8L_KEY]=8 -A_HIDDEN[$MODEL_1T_8L_KEY]=25600 -A_ATEN_HEADS[$MODEL_1T_8L_KEY]=160 - +A_HIDDEN[$MODEL_1T_8L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_8L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_16L_KEY="GPT1T_16L" +A_NLAYERS[$MODEL_1T_16L_KEY]=16 +A_HIDDEN[$MODEL_1T_16L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_16L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_24L_KEY="GPT1T_24L" +A_NLAYERS[$MODEL_1T_24L_KEY]=24 +A_HIDDEN[$MODEL_1T_24L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_24L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_30L_KEY="GPT1T_30L" +A_NLAYERS[$MODEL_1T_30L_KEY]=30 +A_HIDDEN[$MODEL_1T_30L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_30L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_32L_KEY="GPT1T_32L" +A_NLAYERS[$MODEL_1T_32L_KEY]=32 +A_HIDDEN[$MODEL_1T_32L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_32L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_60L_KEY="GPT1T_60L" +A_NLAYERS[$MODEL_1T_60L_KEY]=60 +A_HIDDEN[$MODEL_1T_60L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_60L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_64L_KEY="GPT1T_64L" +A_NLAYERS[$MODEL_1T_64L_KEY]=64 +A_HIDDEN[$MODEL_1T_64L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_64L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_120L_KEY="GPT1T_120L" +A_NLAYERS[$MODEL_1T_120L_KEY]=120 +A_HIDDEN[$MODEL_1T_120L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_120L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_128L_KEY="GPT1T_128L" +A_NLAYERS[$MODEL_1T_128L_KEY]=128 +A_HIDDEN[$MODEL_1T_128L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_128L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_256L_KEY="GPT1T_256L" +A_NLAYERS[$MODEL_1T_256L_KEY]=256 +A_HIDDEN[$MODEL_1T_256L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_256L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_512L_KEY="GPT1T_512L" +A_NLAYERS[$MODEL_1T_512L_KEY]=512 +A_HIDDEN[$MODEL_1T_512L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_512L_KEY]="${MODEL_1T_ATEN_HEADS}" + +MODEL_1T_1024L_KEY="GPT1T_1024L" +A_NLAYERS[$MODEL_1T_1024L_KEY]=1024 +A_HIDDEN[$MODEL_1T_1024L_KEY]="${MODEL_1T_HIDDEN}" +A_ATEN_HEADS[$MODEL_1T_1024L_KEY]="${MODEL_1T_ATEN_HEADS}" export MODEL_SIZE="${MODEL_SIZE_KEY}" export NLAYERS="${A_NLAYERS[$MODEL_SIZE_KEY]}" From 168d28f70ed45ab64efb3590548ef9b8476b5923 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 24 Oct 2023 11:36:54 -0700 Subject: [PATCH 024/268] Adds `train_sbatch_pp64.sh` --- train_sbatch_pp64.sh | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100755 train_sbatch_pp64.sh diff --git a/train_sbatch_pp64.sh b/train_sbatch_pp64.sh new file mode 100755 index 0000000000..b7baf2539e --- /dev/null +++ b/train_sbatch_pp64.sh @@ -0,0 +1,34 @@ +#!/bin/bash --login +#SBATCH -A m3957_g +#SBATCH -C 'gpu&hbm80g' +#SBATCH -q regular +#SBATCH -t 00:30:00 +#SBATCH --nodes 128 +#SBATCH --gpus 512 + + +# TODO:: +# - Add logic for catching / killing hung process at end of run to ensure +# second run starts up (otherwise, it will wait for the hung process, which +# will run until the job is killed) +# - This wll let us try running multiple experiments in a single slurm job +# allocation. +# - Existing (similar implementation) from my `~/bin/kill-match`: +# ```bash +# #!/bin/bash --login +# TO_KILL=$1 +# kill $(ps aux | grep -E "$USER.+($TO_KILL)" | grep -v grep | awk '{print $2}') + + +PPSIZE=64 \ + MODEL_SIZE_KEY="GPT1T_$(( 2 * PPSIZE ))L" \ + SEQ_LEN=2048 \ + MICRO_BATCH=2 \ + GAS=$(( 8 * PPSIZE )) \ + SP_TYPE=megatron \ + ZERO_STAGE=1 \ + USE_SEQUENCE_PARALLEL=0 \ + MPSIZE=8 \ + SPSIZE=1 \ + USE_ACTIVATION_CHECKPOINTING=1 \ + ./ALCF/train-gpt3.sh From cc24a6e7b750e23bc406de35f7cd7250faf4c480 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 20 Dec 2023 19:40:33 -0600 Subject: [PATCH 025/268] Add `ALCF/llama2_vars.sh` --- ALCF/llama2_vars.sh | 168 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 168 insertions(+) create mode 100644 ALCF/llama2_vars.sh diff --git a/ALCF/llama2_vars.sh b/ALCF/llama2_vars.sh new file mode 100644 index 0000000000..b1fa8776f8 --- /dev/null +++ b/ALCF/llama2_vars.sh @@ -0,0 +1,168 @@ +#!/bin/bash +# This example script is contributed by external user https://github.com/nrailgun +# set -ex + +###################################### +# Change the below configurations here +# wget https://the-eye.eu/public/AI/pile_neox/data/BookCorpusDataset_text_document.bin +# wget https://the-eye.eu/public/AI/pile_neox/data/BookCorpusDataset_text_document.idx +MEGATRON_DIR="/home/foremans/datascience/foremans/locations/thetaGPU/projects/argonne-lcf/Megatron-DeepSpeed" +DATA_DIR="~/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DeepSpeed/dataset/" +BASE_PATH="${MEGATRON_DIR}" +DS_CONFIG=${BASE_PATH}/deepspeed.json +DATASET_1="${DATA_DIR}/BookCorpusDataset_text_document" +# DATASET_1="./tmp/data/bookcorpus_train_1m_text_sentence" +DATASET="1 ${DATASET_1}" +CHECKPOINT_PATH=./tmp +TOKENIZER_PATH=./tmp/tokenizer.model # offical llama tokenizer.model + +if [[ $(hostname) == nid* || $(hostname) == login* ]]; then + DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" + DATA_TYPE="BookCorpusDataset_text_document" +elif [[ $(hostname) == theta* || $(hostname) == x3* ]]; then + DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" + DATA_TYPE="genslm_subsample_200k_sequence_document" +else + echo "Unable to determine DATA_PARENT for $(hostname)." + echo "Exiting!" + exit 1 +fi + +DATA_DIR="${DATA_PARENT}/dataset" +DATA_PATH="${DATA_DIR}/${DATA_TYPE}" +VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" +MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" + +DATA_LOAD_ARGS=( + "--data-path $DATA_PATH" + "--vocab-file $VOCAB_FILE" + "--merge-file $MERGE_FILE" +) + +TP=2 +PP=2 +ZERO_STAGE=0 + +GPUS_PER_NODE=$(nvidia-smi -L | wc -l) +MASTER_ADDR=localhost +MASTER_PORT=6000 +NNODES=$(wc -l < "${PBS_NODEFILE:-${COBALT_NODEFILE:-1}}") +NODE_RANK=0 + +HIDDEN_SIZE=2048 # e.g. llama-13b: 5120 +FFN_HIDDEN_SIZE=5504 # e.g. llama-13b: 13824 +NUM_LAYERS=24 # e.g. llama-13b: 40 +NUM_HEADS=16 # e.g. llama-13b: 40 +SEQ_LENGTH=2048 +NUM_KV_HEADS=4 # llama2 70B uses GQA + +MICRO_BATCH_SIZE=4 +GLOBAL_BATCH_SIZE=32 # e.g. llama: 4M tokens +TRAIN_STEPS=250000 # e.g. llama: 1T tokens / 4M tokens_per_batch = 250000 steps +LR=3e-4 +MIN_LR=3e-5 +LR_WARMUP_STEPS=2000 +WEIGHT_DECAY=0.1 +GRAD_CLIP=1 + +## Activation checkpointing saves GPU memory, but reduces training speed +# activation_checkpoint="true" +activation_checkpoint="false" + +# Below configuration required for llama model as per llama paper +# --no-query-key-layer-scaling \ +# --attention-dropout 0 \ +# --hidden-dropout 0 \ +# --use-rotary-position-embeddings \ +# --untie-embeddings-and-output-weights \ +# --swiglu \ +# --normalization rmsnorm \ +# --disable-bias-linear \ +###################################### + + + +cat < $DS_CONFIG +{ + "train_batch_size" : $GLOBAL_BATCH_SIZE, + "train_micro_batch_size_per_gpu": $MICRO_BATCH_SIZE, + "steps_per_print": 1, + "zero_optimization": { + "stage": $ZERO_STAGE + }, + "bf16": { + "enabled": true + } +} +EOT + +ds_args="" +ds_args=" --deepspeed ${ds_args}" +ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" +ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" + +if [ "${activation_checkpoint}" = "true" ]; then + ds_args="--deepspeed-activation-checkpointing ${ds_args}" + + ## old argument for recomputing the transformer layer + # ds_args="--checkpoint-activations ${ds_args}" + + ## new argument for recomputing the transformer layer + ds_args="--recompute-granularity full --recompute-method uniform ${ds_args}" + ## new argument for recomputing only the attention layer + # ds_args="--recompute-granularity selective ${ds_args}" +fi + + +DISTRIBUTED_ARGS="--nproc_per_node $GPUS_PER_NODE --nnodes $NNODES --node_rank $NODE_RANK --master_addr $MASTER_ADDR --master_port $MASTER_PORT" + +# torchrun $DISTRIBUTED_ARGS \ +# pretrain_gpt.py \ +# +MEGATRON_ARGS=( + "--tensor-model-parallel-size $TP" + "--pipeline-model-parallel-size $PP" + "--num-layers $NUM_LAYERS" + "--hidden-size $HIDDEN_SIZE" + "--ffn-hidden-size $FFN_HIDDEN_SIZE" + "--num-attention-heads $NUM_HEADS" + "--micro-batch-size $MICRO_BATCH_SIZE" + "--global-batch-size $GLOBAL_BATCH_SIZE" + "--seq-length $SEQ_LENGTH" + "--max-position-embeddings $SEQ_LENGTH" + "--train-iters $TRAIN_STEPS" + "--save $CHECKPOINT_PATH" + "--load $CHECKPOINT_PATH" + "--data-path $DATASET" + "--data-impl mmap" + "--tokenizer-type GPTSentencePieceTokenizer" + "--tokenizer-model $TOKENIZER_PATH" + "--split 949,50,1" + "--distributed-backend nccl" + "--lr $LR" + "--lr-decay-style cosine" + "--min-lr $MIN_LR" + "--weight-decay $WEIGHT_DECAY" + "--clip-grad $GRAD_CLIP" + "--lr-warmup-iters $LR_WARMUP_STEPS" + "--optimizer adam" + "--adam-beta1 0.9" + "--adam-beta2 0.95" + "--log-interval 1" + "--save-interval 10000" + "--eval-interval 1000" + "--eval-iters 10" + "--bf16" + "--no-query-key-layer-scaling" + "--attention-dropout 0" + "--hidden-dropout 0" + "--use-rotary-position-embeddings" + "--untie-embeddings-and-output-weights" + "--swiglu" + "--normalization rmsnorm" + "--disable-bias-linear" + "--num-key-value-heads $NUM_KV_HEADS" +) + +MEGATRON_ARGS+="${ds_args}" +MEGATRON_ARGS+="${DATA_LOAD_ARGS}" From 1dddf70b300c078eafdac3178616fbd6a48b02a9 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 20 Dec 2023 19:42:46 -0600 Subject: [PATCH 026/268] Add `pretrain_llama.py` --- pretrain_llama.py | 562 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 562 insertions(+) create mode 100644 pretrain_llama.py diff --git a/pretrain_llama.py b/pretrain_llama.py new file mode 100644 index 0000000000..bfc10704e4 --- /dev/null +++ b/pretrain_llama.py @@ -0,0 +1,562 @@ +# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved. + +"""Pretrain GPT""" + +import os +import torch +import math + +# import logging + +from functools import partial +from megatron import get_args +from megatron import print_rank_0 +from rich import print +from megatron import get_timers +from megatron import get_tokenizer +from megatron.core import mpu, tensor_parallel +from megatron.core.enums import ModelType +from megatron.data.gpt_dataset import build_train_valid_test_datasets +from megatron.model import GPTModel, GPTModelPipe +from megatron.training import pretrain +from megatron.utils import get_ltor_masks_and_position_ids +from megatron.utils import ( + average_losses_across_data_parallel_group, + update_rotary_pos_emb, +) +from megatron.arguments import core_transformer_config_from_args + +import deepspeed +from deepspeed.runtime.utils import see_memory_usage +from deepspeed.accelerator.real_accelerator import get_accelerator +import subprocess +import wandb + +from torch import nn +import torch.nn.functional as F + +# from ezpz import get_logger +from ezpz.dist import setup_torch, get_world_size, setup_wandb + +RANK = setup_torch( + backend="deepspeed", + port="5432", +) +WORLD_SIZE = get_world_size() +LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" + +WANDB_MODE = os.environ.get("WANDB_MODE", None) +DISABLE_WANDB = ( + WANDB_MODE is not None and str(WANDB_MODE).lower() == "disabled" +) + +if RANK == 0 and not DISABLE_WANDB: + project_name = os.environ.get( + "WB_PROJECT", + os.environ.get("WANDB_PROJECT", "GenSLM-Megatron-DS"), + ) + print("--------------------------------------------------") + print(f"Setting up W&B from: {RANK} with {project_name}") + print("--------------------------------------------------") + setup_wandb(project_name=project_name) + + +def model_provider(pre_process=True, post_process=True): + """Build the model.""" + print_rank_0("building GPT model ...") + see_memory_usage("Before Building Model", force=True) + args = get_args() + config = core_transformer_config_from_args(args) + # args = get_args() + # timers = get_timers() + if wandb.run is not None: + print(f"Updating WandB run: [{wandb.run.name}]({wandb.run.url})") + wandb.run.config.update({"args": vars(args)}) + if RANK == 0: + git_ds_info() + + with deepspeed.zero.Init( + sequence_data_parallel_group=mpu.get_sequence_data_parallel_group(), + remote_device=( + None if args.remote_device == "none" + else args.remote_device, + ), + config_dict_or_path=args.deepspeed_config, + enabled=args.zero_stage == 3, + mpu=mpu, + ): + if args.deepspeed and not args.no_pipeline_parallel: + model = GPTModelPipe( + config=config, + num_tokentypes=0, + parallel_output=True + ) + # This is a hack to give us a reference to get_batch_pipe from + # within training.py We need to call model.set_batch_fn after + # deepspeed.initialize + model._megatron_batch_fn = get_batch_pipe + + # Predompute the attention mask and store it in args. This avoids + # having to pipeline it as an activation during training. The mask + # is constant, and thus we can reuse it. + attention_mask = torch.tril( + torch.ones( + (1, args.seq_length, args.seq_length), + device=get_accelerator().current_device_name(), + ) + ).view(1, 1, args.seq_length, args.seq_length) + + # Convert attention mask to binary: + attention_mask = attention_mask < 0.5 + if args.fp16: + attention_mask = attention_mask.half() + elif args.bf16: + attention_mask = attention_mask.bfloat16() + + # Attention mask must be bool. + args.attn_mask = attention_mask.to(torch.bool) + + # For prertaining, since sequence length is fixed, cache rotary + # embedding in args, to avoid communicating around + if args.use_rotary_position_embeddings: + update_rotary_pos_emb(args.seq_length) + + else: + model = GPTModel( + config=config, + num_tokentypes=0, + parallel_output=True, + pre_process=pre_process, + post_process=post_process, + ) + num_params = sum(p.numel() for p in model.parameters() if p.requires_grad) + # print_rank_0('\n ------------------------ ') + # print_rank_0(f'num of parameters {num_params}') + # print_rank_0('------------------------\n ') + print_rank_0(80 * "-") + print_rank_0(f"Number of parameters in model: {num_params}") + print_rank_0(80 * "-") + see_memory_usage("After Building Model", force=True) + if wandb.run is not None: + wandb.run.watch( + model, + log="all", + log_graph=True, + ) + wandb.run.config.update({"num_params": num_params}) + return model + + +def get_batch(data_iterator): + """Generate a batch""" + args = get_args() + tokenizer = get_tokenizer() + + # Items and their type. + keys = ["text"] + datatype = torch.int64 + + # Broadcast data. + if data_iterator is not None: + data = next(data_iterator) + else: + data = None + data_b = tensor_parallel.broadcast_data(keys, data, datatype) + + # Unpack. + tokens_ = data_b["text"].long() + labels = tokens_[:, 1:].contiguous() + tokens = tokens_[:, :-1].contiguous() + + # Get the masks and postition ids. + skip_mask = ( + hasattr(args, "use_flash_attn") + or hasattr(args, "flash_attn_triton") + ) + # skip_mask = args.use_flash_attn or args.use_flash_attn_triton + attention_mask, loss_mask, position_ids = get_ltor_masks_and_position_ids( + tokens, + tokenizer.eod, + args.reset_position_ids, + args.reset_attention_mask, + args.eod_mask_loss, + skip_mask, + ) + + # For DS's sequence parallel + seq_parallel_world_size = mpu.get_sequence_parallel_world_size() + seq_parallel_world_rank = mpu.get_sequence_parallel_rank() + + # For Megatron's sequence parallel + if args.sequence_parallel: + seq_parallel_world_size = mpu.get_tensor_model_parallel_world_size() + seq_parallel_world_rank = mpu.get_tensor_model_parallel_rank() + seq_length = tokens.size(1) + + assert seq_length % seq_parallel_world_size == 0 + sub_seq_length = seq_length // seq_parallel_world_size + sub_seq_start = seq_parallel_world_rank * sub_seq_length + sub_seq_end = (seq_parallel_world_rank + 1) * sub_seq_length + + tokens = tokens[:, sub_seq_start:sub_seq_end] + position_ids = position_ids[:, sub_seq_start:sub_seq_end] + # For DS's sequence parallel + if mpu.get_sequence_parallel_world_size() > 1: + labels = labels[:, sub_seq_start:sub_seq_end] + + return tokens, labels, loss_mask, attention_mask, position_ids + + +def data_post_process(data, data_sampler_state_dict): + args = get_args() + if args.data_efficiency_curriculum_learning: + if ( + "seqlen_truncate" in data_sampler_state_dict[ + "current_difficulties" + ] + ): + args.data_efficiency_curriculum_learning_seqlen_type = ( + "seqlen_truncate" + ) + current_seqlen = ( + data_sampler_state_dict["current_difficulties"][ + "seqlen_truncate" + ] + ) + if current_seqlen < args.seq_length: + data["text"] = ( + data["text"][:, : (current_seqlen + 1)].contiguous() + ) + elif ( + "seqlen_reshape" in data_sampler_state_dict["current_difficulties"] + ): + args.data_efficiency_curriculum_learning_seqlen_type = ( + "seqlen_reshape" + ) + current_seqlen = ( + data_sampler_state_dict["current_difficulties"][ + "seqlen_reshape" + ] + ) + if current_seqlen < args.seq_length: + orig_num_token = torch.numel(data["text"]) + reshape_len = ( + (data["text"].size()[1] // (current_seqlen + 1)) + * (current_seqlen + 1) + ) + data["text"] = torch.cat( + ( + data["text"][:, :reshape_len] + .contiguous() + .view(-1, current_seqlen + 1), + data["text"][:, -(current_seqlen + 1):], + ), + 0, + ).contiguous() + num_row = math.ceil(orig_num_token / (current_seqlen + 1)) + num_row = min(num_row, data["text"].size()[0]) + if num_row > 1 and num_row % 2 != 0: + num_row -= 1 + data["text"] = data["text"][:num_row, :].contiguous() + else: + args.data_efficiency_curriculum_learning_seqlen_type = None + return data + + +def get_batch_pipe(data): + """Modification of `get_batch` to work on `next(data_iterator)` instead of + `data_iterator`""" + args = get_args() + tokenizer = get_tokenizer() + + # Items and their type. + keys = ["text"] + datatype = torch.int64 + + # Broadcast data. + data_b = tensor_parallel.broadcast_data(keys, data, datatype) + + # Unpack. + tokens_ = data_b["text"].long() + labels = tokens_[:, 1:].contiguous() + tokens = tokens_[:, :-1].contiguous() + + # Get the masks and postition ids. + attention_mask, loss_mask, position_ids = get_ltor_masks_and_position_ids( + tokens, + tokenizer.eod, + args.reset_position_ids, + args.reset_attention_mask, + args.eod_mask_loss, + ) + if ( + args.curriculum_learning_legacy + and args.curriculum_seqlen < tokens.size()[1] + ): + # seqlen-based curriculum learning + # tokens, position_ids, labels, loss_mask have size: + # [batch size, seqlen] + tokens = tokens[:, : args.curriculum_seqlen].contiguous() + position_ids = position_ids[:, : args.curriculum_seqlen].contiguous() + if labels is not None: + labels = labels[:, : args.curriculum_seqlen].contiguous() + loss_mask = loss_mask[:, : args.curriculum_seqlen].contiguous() + + return (tokens, position_ids, attention_mask), (labels, loss_mask) + + +def loss_func(loss_mask, moe_loss, mos_loss, output_tensor): + args = get_args() + losses = output_tensor.float() + loss_mask = loss_mask.view(-1).float() + loss = torch.sum(losses.view(-1) * loss_mask) / loss_mask.sum() + + # Reduce loss for logging. + averaged_loss = average_losses_across_data_parallel_group([loss]) + if args.mos or args.kd: + # assert max(args.num_experts) >= 1 + loss = loss + moe_loss + mos_loss + if args.mos: + return loss, { + "total loss": loss, + "lm loss": averaged_loss[0], + "moe loss": moe_loss, + "mos loss": mos_loss, + } + elif args.kd: + return loss, { + "total loss": loss, + "lm loss": averaged_loss[0], + "moe loss": moe_loss, + "kd loss": mos_loss, + } + print_rank_0( + ">>> total loss: {}, lm loss {}, kd loss {}".format( + loss, averaged_loss[0], mos_loss + ) + ) + else: + if max(args.num_experts) <= 1: + return loss, {"lm loss": averaged_loss[0]} + else: + loss = loss + moe_loss + return loss, {"lm loss": averaged_loss[0], "moe loss": moe_loss} + + +def calculate_mos_loss( + args, stu_output, teacher_model, tokens, position_ids, attention_mask +): + mos_loss = 0 + alpha = args.kd_alpha_ce + beta = args.kd_beta_ce + kd_temp = args.kd_temp + + if teacher_model: + with torch.no_grad(): + if ( + args.curriculum_learning_legacy + and args.curriculum_seqlen < args.seq_length + ): + assert args.curriculum_seqlen is not None + curriculum_seqlen = args.curriculum_seqlen + tokens = tokens[:, :curriculum_seqlen].contiguous() + position_ids = position_ids[:, :curriculum_seqlen].contiguous() + attention_mask = attention_mask[ + :, :, :curriculum_seqlen, :curriculum_seqlen + ].contiguous() + # No need to truncate labels as we do not need it for the + # teacher logits + tea_output, tea_other_losses = teacher_model( + tokens, position_ids, attention_mask + ) + assert ( + stu_output.size() == tea_output.size() + ), ( + "teacher and student output should match in size. " + f"Student: {stu_output.size()}, " + f"Teacher: {tea_output.size()}, " + f"CL seq length {args.curriculum_seqlen}" + ) + + student_logits = F.log_softmax(stu_output / kd_temp, dim=2) + tea_logits = F.softmax( + tea_output / kd_temp, dim=2 + ) + # The target logits is expected to be probabilities. If we use + # log_softmax, then we need to set target_log to true when initializing + # the KLDivLoss. + mos_loss = ( + kd_temp + * kd_temp + * nn.KLDivLoss(reduction="batchmean")(student_logits, tea_logits) + ) + + mos_loss = mos_loss.div(args.seq_length) * beta + return mos_loss + + +def forward_step(data_iterator, model): + """Forward step.""" + args = get_args() + timers = get_timers() + + # Get the batch. + timers("batch-generator", log_level=2).start() + tokens, labels, loss_mask, attention_mask, position_ids = ( + get_batch(data_iterator) + ) + timers("batch-generator").stop() + + if args.data_efficiency_curriculum_learning: + args.curriculum_seqlen = tokens.size()[1] + if ( + hasattr( + args, + "data_efficiency_curriculum_learning_seqlen_type" + ) + and ( + args.data_efficiency_curriculum_learning_seqlen_type + == "seqlen_reshape" + ) + ): + args.data_efficiency_curriculum_learning_numel = ( + torch.numel(tokens) + ) + + if args.mos or args.kd: + # The forward func can return either the loss or the logits, depending + # on whether passing in the labels or not. + stu_output, other_losses = model(tokens, position_ids, attention_mask) + if ( + args.curriculum_learning_legacy + and args.curriculum_seqlen < args.seq_length + ): + assert args.curriculum_seqlen is not None + labels = labels[:, : args.curriculum_seqlen].contiguous() + output_tensor = tensor_parallel.vocab_parallel_cross_entropy( + stu_output.contiguous().float(), labels + ) + else: + output_tensor, other_losses = model( + tokens, position_ids, attention_mask, labels=labels + ) + if ( + args.curriculum_learning_legacy + and args.curriculum_seqlen < args.seq_length + ): + loss_mask = loss_mask[:, : args.curriculum_seqlen].contiguous() + + moe_losses = [] + for moe_loss in other_losses: + if moe_loss is not None: + moe_losses.append(moe_loss) + moe_loss = sum(moe_losses) * args.moe_loss_coeff + + mos_loss = 0 + if args.mos or args.kd: + assert model.training + if args.teacher_forward and args.teacher_model is not None: + mos_loss = calculate_mos_loss( + args, + stu_output, + args.teacher_model[0], + tokens, + position_ids, + attention_mask, + ) + + # Output_tensor stores the standard loss, loos_func calculates the total + # loss. + return output_tensor, partial(loss_func, loss_mask, moe_loss, mos_loss) + + +def train_valid_test_datasets_provider(train_val_test_num_samples): + """Build train, valid, and test datasets.""" + args = get_args() + + print_rank_0( + "> building train, validation, and test datasets " "for GPT ..." + ) + train_ds, valid_ds, test_ds = build_train_valid_test_datasets( + data_prefix=args.data_path, + data_impl=args.data_impl, + splits_string=args.split, + train_valid_test_num_samples=train_val_test_num_samples, + seq_length=args.seq_length, + seed=args.seed, + skip_warmup=(not args.mmap_warmup), + train_data_prefix=args.train_data_path, + valid_data_prefix=args.valid_data_path, + test_data_prefix=args.test_data_path, + data_cache_path=args.data_cache_path, + ) + print_rank_0("> finished creating GPT datasets ...") + + return train_ds, valid_ds, test_ds + + +def command_exists(cmd): + result = subprocess.Popen( + f"type {cmd}", + stdout=subprocess.PIPE, + shell=True + ) + return result.wait() == 0 + + +def git_ds_info(): + from deepspeed.env_report import main as ds_report + + ds_report() + + # Write out version/git info + git_hash_cmd = "git rev-parse --short HEAD" + git_branch_cmd = "git rev-parse --abbrev-ref HEAD" + if command_exists("git"): + try: + result = subprocess.check_output(git_hash_cmd, shell=True) + git_hash = result.decode("utf-8").strip() + result = subprocess.check_output(git_branch_cmd, shell=True) + git_branch = result.decode("utf-8").strip() + except subprocess.CalledProcessError: + git_hash = "unknown" + git_branch = "unknown" + else: + git_hash = "unknown" + git_branch = "unknown" + print( + f"**** Git info for Megatron: " + f"git_hash={git_hash} git_branch={git_branch} ****" + ) + + +def main(): + model = pretrain( + train_valid_test_datasets_provider, + model_provider, + ModelType.encoder_or_decoder, + forward_step, + args_defaults={"tokenizer_type": "GPT2BPETokenizer"}, + data_post_process=data_post_process, + ) + return model + + +if __name__ == "__main__": + # git_ds_info() + # pretrain(train_valid_test_datasets_provider, + # model_provider, + # ModelType.encoder_or_decoder, + # forward_step, + # args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + # data_post_process=data_post_process) + import sys + import deepspeed.comm as dist + + model = main() + dist.log_summary() + if wandb.run is not None: + print(f"wandb.run.name: {wandb.run.name}") + print(f"wandb.run.url: {wandb.run.url}") + wandb.finish() + sys.exit() From b6fb158e110640cf5a8e387a48c3727f6fd18bde Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 21 Dec 2023 15:26:15 -0600 Subject: [PATCH 027/268] Support Llama2 pretraining --- ALCF/launch.sh | 20 +-- ALCF/llama2_vars.sh | 323 ++++++++++++++++++++++++++++++++++++++++---- ALCF/model.sh | 39 ++++++ pretrain_llama.py | 85 ++++++++---- 4 files changed, 401 insertions(+), 66 deletions(-) mode change 100644 => 100755 ALCF/llama2_vars.sh diff --git a/ALCF/launch.sh b/ALCF/launch.sh index 4c1a6ba0e0..41a620a145 100755 --- a/ALCF/launch.sh +++ b/ALCF/launch.sh @@ -37,14 +37,14 @@ MASTER_PORT=20010 SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )" MPI_WRAPPER="${SCRIPT_DIR}/mpi_wrapper" -sourceFile "${ALCF_DIR}/args.sh" +# sourceFile "${ALCF_DIR}/args.sh" MAIN="${PARENT}/pretrain_${MODEL_TYPE}.py" printJobInfo() { echo "Job started at: ${TSTAMP} on $(hostname)" echo "Job running in: ${DIR}" - echo "Training GPT-3 with ${MODEL_SIZE} parameters" + echo "Training Llama2 with ${MODEL_SIZE} parameters" echo "Writing logs to: ${OUTPUT_DIR}" echo 'to view output: tail -f $(tail -1 logfiles)' echo "i.e. tail -f $(tail -1 "${PARENT}"/logfiles)" @@ -70,7 +70,7 @@ fullNode() { echo "NGPUS ${NGPUS}" echo "hostfile ${DIR}/hostfile" echo "MAIN ${MAIN}" - echo "gpt_args ${gpt_args}" + echo "gpt_args ${ARGS}" NHOSTS=$(wc -l < "${HOSTFILE}") NGPU_PER_HOST=$(nvidia-smi -L | wc -l) NGPUS=$((${NHOSTS}*${NGPU_PER_HOST})) @@ -87,8 +87,8 @@ fullNode() { "${MASTER_ADDR}" "${MASTER_PORT}" "${MAIN}" - "${gpt_args}" - "${ds_args}" + "${ARGS}" + # "${ds_args}" ) # EXEC=$(join_by ' ' "${EXEC[*]}") EXEC="${EXEC[*]}" @@ -151,8 +151,9 @@ elasticDistributed() { "${MPI_ELASTIC}" "$(which python3)" "${MAIN}" - "${gpt_args}" - "${ds_args}" + "${ARGS}" + # "${gpt_args}" + # "${ds_args}" ) elif [[ $(hostname) == nid* || $(hostname) == login* ]]; then echo "Setting up from Perlmutter on $(hostname)" @@ -166,8 +167,9 @@ elasticDistributed() { "${SRUN_EXEC}" "$(which python3)" "${MAIN}" - "${gpt_args}" - "${ds_args}" + "${ARGS}" + # "${gpt_args}" + # "${ds_args}" ) else echo "Unexpected hostname $(hostname)" diff --git a/ALCF/llama2_vars.sh b/ALCF/llama2_vars.sh old mode 100644 new mode 100755 index b1fa8776f8..2fc8c3898a --- a/ALCF/llama2_vars.sh +++ b/ALCF/llama2_vars.sh @@ -1,19 +1,76 @@ #!/bin/bash # This example script is contributed by external user https://github.com/nrailgun +# [2023-12-20]: Modified by [@saforem2](https://github.com/saforem2) # set -ex +# +function WhereAmI() { + python3 -c 'import os; print(os.getcwd())' +} + +function join_by { local d=${1-} f=${2-}; if shift 2; then printf %s "$f" "${@/#/$d}"; fi; } + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source="${FILE}" + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi +} + + +USER=$(whoami) +HERE=$(WhereAmI) +ALCF_DIR="${HERE}/ALCF" +PARENT=$(dirname "${ALCF_DIR}") +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" +echo "ALCF_DIR: ${ALCF_DIR}" +echo "PARENT: ${PARENT}" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" + +HOSTNAME=$(hostname) +sourceFile "${ALCF_DIR}/setup.sh" +sourceFile "${ALCF_DIR}/model.sh" + +WORLD_SIZE="${NGPUS}" +PARALLEL_SIZE="${WORLD_SIZE}" +echo "NHOSTS * (NGPU / HOST) = $NHOSTS * $NGPU_PER_HOST = $NGPUS" + +# MODEL_LLAMA_KEY="LLAMA-24L" +# HIDDEN_SIZE=2048 # e.g. llama-13b: 5120 +# FFN_HIDDEN_SIZE=5504 # e.g. llama-13b: 13824 +# NUM_LAYERS=24 # e.g. llama-13b: 40 +# NUM_HEADS=16 # e.g. llama-13b: 40 +# SEQ_LENGTH=2048 +# NUM_KV_HEADS=4 # llama2 70B uses GQA +# FFN_HIDDEN_SIZE=5504 +# NUM_HEADS=16 # e.g. llama-13b: 40 ###################################### # Change the below configurations here # wget https://the-eye.eu/public/AI/pile_neox/data/BookCorpusDataset_text_document.bin # wget https://the-eye.eu/public/AI/pile_neox/data/BookCorpusDataset_text_document.idx -MEGATRON_DIR="/home/foremans/datascience/foremans/locations/thetaGPU/projects/argonne-lcf/Megatron-DeepSpeed" -DATA_DIR="~/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DeepSpeed/dataset/" + +USER=$(whoami) +HERE=$(WhereAmI) +ALCF_DIR="${HERE}/ALCF" +PARENT=$(dirname "${ALCF_DIR}") +# echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" +# echo "ALCF_DIR: ${ALCF_DIR}" +# # echo "PARENT: ${PARENT}" +# echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" + +MEGATRON_DIR="${HERE}" + +# DATA_DIR="${HOME}/datascience/foremans/locations/thetaGPU/projects/saforem2/Megatron-DeepSpeed/dataset/" BASE_PATH="${MEGATRON_DIR}" DS_CONFIG=${BASE_PATH}/deepspeed.json DATASET_1="${DATA_DIR}/BookCorpusDataset_text_document" # DATASET_1="./tmp/data/bookcorpus_train_1m_text_sentence" DATASET="1 ${DATASET_1}" -CHECKPOINT_PATH=./tmp +# CHECKPOINT_PATH=./tmp TOKENIZER_PATH=./tmp/tokenizer.model # offical llama tokenizer.model if [[ $(hostname) == nid* || $(hostname) == login* ]]; then @@ -33,15 +90,20 @@ DATA_PATH="${DATA_DIR}/${DATA_TYPE}" VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" +echo "ALCF_DIR: ${ALCF_DIR}" +echo "MEGATRON_DIR: ${MEGATRON_DIR}" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" + DATA_LOAD_ARGS=( "--data-path $DATA_PATH" "--vocab-file $VOCAB_FILE" "--merge-file $MERGE_FILE" ) -TP=2 -PP=2 -ZERO_STAGE=0 +# TP=2 +# PP=2 +# ZERO_STAGE=0 GPUS_PER_NODE=$(nvidia-smi -L | wc -l) MASTER_ADDR=localhost @@ -49,15 +111,38 @@ MASTER_PORT=6000 NNODES=$(wc -l < "${PBS_NODEFILE:-${COBALT_NODEFILE:-1}}") NODE_RANK=0 -HIDDEN_SIZE=2048 # e.g. llama-13b: 5120 -FFN_HIDDEN_SIZE=5504 # e.g. llama-13b: 13824 -NUM_LAYERS=24 # e.g. llama-13b: 40 -NUM_HEADS=16 # e.g. llama-13b: 40 -SEQ_LENGTH=2048 +# TP=2 +# PP=2 +# ZERO_STAGE=0 +# +export SEQ_LENGTH=${SEQ_LENGTH:-2048} +export NUM_KV_HEADS=4 # llama2 70B uses GQA +export MODEL_SIZE_KEY="${MODEL_SIZE_KEY:-LLAMA_7B}" +export MODEL_TYPE=${MODEL_TYPE:-llama} +echo "==========================+" +echo "Using ${MODEL_SIZE_KEY}" +echo "==========================+" + + +export DDP_IMPL="local" +export GAS=${GAS:-1} +export MPSIZE=${MPSIZE:-1} +export SPSIZE=${SPSIZE:-1} +export PPSIZE=${PPSIZE:-1} +export SP_TYPE=${SP_TYPE:-"ds"} +export MICRO_BATCH=${MICRO_BATCH:-1} + +# export HIDDEN_SIZE=2048 # e.g. llama-13b: 5120 +# export FFN_HIDDEN_SIZE=5504 # e.g. llama-13b: 13824 +# export NUM_LAYERS=24 # e.g. llama-13b: 40 +# export NUM_HEADS=16 # e.g. llama-13b: 40 +# export SEQ_LENGTH=${SEQ_LENGTH:-2048} +# export NUM_KV_HEADS=4 # llama2 70B uses GQA + NUM_KV_HEADS=4 # llama2 70B uses GQA +FFN_HIDDEN_SIZE=5504 -MICRO_BATCH_SIZE=4 -GLOBAL_BATCH_SIZE=32 # e.g. llama: 4M tokens +# GLOBAL_BATCH=32 # e.g. llama: 4M tokens TRAIN_STEPS=250000 # e.g. llama: 1T tokens / 4M tokens_per_batch = 250000 steps LR=3e-4 MIN_LR=3e-5 @@ -80,18 +165,119 @@ activation_checkpoint="false" # --disable-bias-linear \ ###################################### +# Deal with Sequence Parallel implementation --------------------------------------- +# ---------------------------------------------------------------------------------- +if [[ ${SP_TYPE} == "ds" ]]; then + # NOTE: -------------------------------------------------------------------- + # SP_TYPE="ds" has NO effect, essentially running with no Seq. parallelism + # -------------------------------------------------------------------------- + if [[ "$MPSIZE" == "${WORLD_SIZE}" ]]; then + # hacky workaround to try and use SP_TYPE="ds" + MPSIZE="${WORLD_SIZE}" + # ------------------------------------------------------------------------ + # Update [2023-08-22]: Chengming mentioned that this is an internal issue + # and will NOT work currently + # ------------------------------------------------------------------------ + echo "Caught MPSIZE: $MPSIZE from env. Setting SPSIZE=1" + SPSIZE=1 + MPSIZE="${MPSIZE}" + else + echo "Didn't catch MPSIZE from env. Setting SPSIZE=${WORLD_SIZE}, MPSIZE=1" + MPSIZE=1 + SPSIZE="${WORLD_SIZE}" + fi + if [ -z "${ZERO_STAGE}" ]; then + echo "ZERO_STAGE not set, setting to 3 for ${SP_TYPE}" + ZERO_STAGE=3 + else + echo "Caught ZERO_STAGE=${ZERO_STAGE} with ${SP_TYPE}" + fi + export SPSIZE="${SPSIZE:-$WORLD_SIZE}" + export MPSIZE="${MPSIZE:-1}" + export USE_SEQUENCE_PARALLEL=0 + export ZERO_STAGE="${ZERO_STAGE}" +elif [[ ${SP_TYPE} == "megatron" ]]; then + # NOTE: -------------------------------------------------------------------------- + # SP_TYPE="megatron" will use Megatron's Seq. || implementation with ZERO_STAGE=0 + # -------------------------------------------------------------------------------- + [ "$SPSIZE" ] && echo "Caught SPSIZE: ${SPSIZE} from env" || SPSIZE=1 + [ "$MPSIZE" ] && echo "Caught MPSIZE: ${MPSIZE} from env" || MPSIZE="${WORLD_SIZE}" + [ "$ZERO_STAGE" ] && echo "Caught ${ZERO_STAGE} from env" || ZERO_STAGE=0 + [ "$USE_SEQUENCE_PARALLEL" ] && echo "Caught USE_SP: $USE_SEQUENCE_PARALLEL from env" || USE_SEQUENCE_PARALLEL=1 + if [[ ${PPSIZE} > 1 ]]; then # && ${MPSIZE}==${WORLD_SIZE} ]]; + MPSIZE=$(( WORLD_SIZE / PPSIZE )) + echo "Re-setting MPSIZE to ${WORLD_SIZE} / ${PPSIZE} = $(( WORLD_SIZE / PPSIZE ))" + echo "MPSIZE: $MPSIZE" + # MPSIZE="${WORLD_SIZE}/" + fi + export SPSIZE="${SPSIZE}" + export MPSIZE="${MPSIZE}" + export ZERO_STAGE="${ZERO_STAGE}" + export USE_SEQUENCE_PARALLEL="${USE_SEQUENCE_PARALLEL:-1}" +else + echo "Unexpected SP_TYPE: ${SP_TYPE}" + # exit 1 +fi +# ------------------------------------------------------------------------ +# +echo "####################################################" +echo "USING: ${SP_TYPE}" +echo "SPSIZE: ${SPSIZE}" +echo "PPSIZE: ${SPSIZE}" +echo "MPSIZE: ${MPSIZE}" +echo "ZERO_STAGE: ${ZERO_STAGE}" +echo "WORLD_SIZE: ${WORLD_SIZE}" +echo "USE_SEQUENCE_PARALLEL: ${USE_SEQUENCE_PARALLEL}" +echo "####################################################" + +echo "++++++++++++++++++++++++++++++++++++++++++++++++++++++++" +echo "${SP_TYPE} sequence parallelism, with: " +echo " {MPSIZE: ${MPSIZE}, SPSIZE: ${SPSIZE}, USE_SEQUENCE_PARALLEL: ${USE_SEQUENCE_PARALLEL}} !!" +echo "########################################################" + +GLOBAL_BATCH=$(( NGPUS * MICRO_BATCH * GAS )) + +GLOBAL_BATCH=$(( GLOBAL_BATCH / MPSIZE / PPSIZE / SPSIZE)) + +echo "GB = (NGPUS * MB * GAS) / (MP * PP * SP * DP) = ${NGPUS} * ${MICRO_BATCH} * ${GAS} = ${GLOBAL_BATCH} / (${MPSIZE} * ${PPSIZE} * ${PPSIZE})" +# echo "GB = (NGPUS * MB * GAS) / (MP * PP * SP) = (${NGPUS} * ${MICRO_BATCH} * ${GAS}) / (${MPSIZE} * ${PPSIZE} * ${SPSIZE}) = ${GLOBAL_BATCH}" + +if [[ "${GLOBAL_BATCH}" == 0 ]]; then + GLOBAL_BATCH=1 +fi +# [ "${GLOBAL_BATCH:-${GLOBAL_BATCH}}" == 0 ] && GLOBAL_BATCH=1 || echo "GLOBAL_BATCH: ${GLOBAL_BATCH}" + +DPSIZE=$(( $WORLD_SIZE / $PPSIZE / $MPSIZE )) + +export GLOBAL_BATCH="$(( GLOBAL_BATCH * DPSIZE ))" +# export GLOBAL_BATCH="$GLOBAL_BATCH" +# echo "@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@" +# echo "@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@" + +echo "--------------------------------" +echo "GLOBAL_BATCH=${GLOBAL_BATCH}" +echo "USING DPSIZE: ${DPSIZE}" +echo "--------------------------------" + +# REMAINDER=$(( GLOBAL_BATCH % (MICRO_BATCH * DPSIZE))) +# if [[ "${GLOBAL_BATCH} "]] + + cat < $DS_CONFIG { - "train_batch_size" : $GLOBAL_BATCH_SIZE, - "train_micro_batch_size_per_gpu": $MICRO_BATCH_SIZE, + "train_batch_size" : $GLOBAL_BATCH, + "train_micro_batch_size_per_gpu": $MICRO_BATCH, "steps_per_print": 1, "zero_optimization": { "stage": $ZERO_STAGE }, "bf16": { "enabled": true + }, + "wandb": { + "enabled": true, + "project": "GenSLM-Megatron-DS" } } EOT @@ -118,21 +304,81 @@ DISTRIBUTED_ARGS="--nproc_per_node $GPUS_PER_NODE --nnodes $NNODES --node_rank $ # torchrun $DISTRIBUTED_ARGS \ # pretrain_gpt.py \ -# -MEGATRON_ARGS=( - "--tensor-model-parallel-size $TP" - "--pipeline-model-parallel-size $PP" - "--num-layers $NUM_LAYERS" - "--hidden-size $HIDDEN_SIZE" + + +# ┏━━━━━━━━━━━━━━━━━━━┓ +# ┃ FILE I/O SETTINGS ┃ +# ┗━━━━━━━━━━━━━━━━━━━┛ +RUN_STR="gb${GLOBAL_BATCH}_mb${MICRO_BATCH}" +RUN_STR="nl${NLAYERS}_hs${HIDDEN}_${RUN_STR}" +RUN_STR="mp${MPSIZE}_pp${PPSIZE}_sp${SPSIZE}_${RUN_STR}" +RUN_STR="z${ZERO_STAGE}_seqlen${SEQ_LEN}_${RUN_STR}" +RUN_STR="${MODEL_SIZE_KEY}_${RUN_STR}" + +# if [[ "${USE_FLASH_ATTN}" == 0 ]]; then +# echo "Not using Flash Attention!!" +# else +# +if [[ "${USE_FLASH_ATTN1}" || "${USE_FLASH_ATTN_V1}" ]]; then + # Flash Attention 1 + [ "${USE_FLASH_ATTN}" ] && RUN_STR="flashAttn_v1_${RUN_STR}" + [ "${USE_FLASH_ATTN1}" ] && RUN_STR="flashAttn_v1_${RUN_STR}" + [ "${USE_FLASH_ATTN_V1}" ] && RUN_STR="flashAttn_v1_${RUN_STR}" +elif [[ "${USE_FLASH_ATTN2}" || "${USE_FLASH_ATTN_V2}" ]]; then + # Flash Attention 2 + [ "${USE_FLASH_ATTN2}" ] && RUN_STR="flashAttn_v2_${RUN_STR}" + [ "${USE_FLASH_ATTN_V2}" ] && RUN_STR="flashAttn_v2_${RUN_STR}" +elif [[ "${USE_FLASH_ATTN_TRITON}" ]]; then + # Triton + Flash Attn + # Triton + Flash Attn + [ "${USE_FLASH_ATTN_TRITON}" ] && RUN_STR="flashAttn_triton_${RUN_STR}" +else + echo "Not using Flash Attention!" +fi + +if [[ $DDP_IMPL == 'FSDP' ]]; then + RUN_STR="FSDP_${RUN_STR}" +fi +if [[ $USE_ACTIVATION_CHECKPOINTING == 1 ]]; then + RUN_STR="actCkpt_${RUN_STR}" +fi +if [[ $USE_SEQUENCE_PARALLEL == 1 ]] ; then + RUN_STR="SP_${RUN_STR}" +fi + +RUN_STR="${MODEL_SIZE}_${RUN_STR}" + +OUTPUT_DIR="${PARENT}/outputs/${RUN_STR}" +CHECKPOINT_DIR="${PARENT}/checkpoints/$RUN_STR" +TENSORBOARD_DIR="${PARENT}/outputs/${RUN_STR}/tensorboard" + +DATE=$(date) +export DATE="${DATE}" +export RUN_STR="${RUN_STR}" +export MODEL_SIZE="${MODEL_SIZE:-${MODEL_SIZE_KEY}}" +export MODEL_SIZE="$MODEL_SIZE" +export TENSORBOARD_DIR=$TENSORBOARD_DIR +export OUTPUT_DIR=$OUTPUT_DIR +mkdir -p "$OUTPUT_DIR/tensorboard/wandb" +mkdir -p "$CHECKPOINT_DIR" +mkdir -p "$TENSORBOARD_DIR" +mkdir -p "$OUTPUT_DIR" +echo "OUTPUT TO: ${OUTPUT_DIR}" + +gpt_args=( + "--tensor-model-parallel-size $MPSIZE" + "--pipeline-model-parallel-size $PPSIZE" + "--num-layers $NLAYERS" + "--hidden-size $HIDDEN" "--ffn-hidden-size $FFN_HIDDEN_SIZE" - "--num-attention-heads $NUM_HEADS" - "--micro-batch-size $MICRO_BATCH_SIZE" - "--global-batch-size $GLOBAL_BATCH_SIZE" + "--num-attention-heads $ATEN_HEADS" + "--micro-batch-size $MICRO_BATCH" + "--global-batch-size $GLOBAL_BATCH" "--seq-length $SEQ_LENGTH" "--max-position-embeddings $SEQ_LENGTH" "--train-iters $TRAIN_STEPS" - "--save $CHECKPOINT_PATH" - "--load $CHECKPOINT_PATH" + "--save $CHECKPOINT_DIR" + "--load $CHECKPOINT_DIR" "--data-path $DATASET" "--data-impl mmap" "--tokenizer-type GPTSentencePieceTokenizer" @@ -162,7 +408,28 @@ MEGATRON_ARGS=( "--normalization rmsnorm" "--disable-bias-linear" "--num-key-value-heads $NUM_KV_HEADS" + "--tensorboard-dir ${TENSORBOARD_DIR}" + "--log-timers-to-tensorboard" + "--tensorboard-log-interval 1" + "--data-path $DATA_PATH" + "--vocab-file $VOCAB_FILE" + "--merge-file $MERGE_FILE" ) -MEGATRON_ARGS+="${ds_args}" -MEGATRON_ARGS+="${DATA_LOAD_ARGS}" +# DATA_LOAD_ARGS=( +# "--data-path $DATA_PATH" +# "--vocab-file $VOCAB_FILE" +# "--merge-file $MERGE_FILE" +# ) + +export gpt_args=( + "${gpt_args[*]}" + "${ds_args[*]}" + # "${DATA_LOAD_ARGS[*]}" +) +ARGS="$(join_by ' ' ${gpt_args[*]})" +echo "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" +echo "ARGS: ${ARGS}" +echo "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" +# gpt_args+="${ds_args}" +# gpt_args+="${DATA_LOAD_ARGS}" diff --git a/ALCF/model.sh b/ALCF/model.sh index d69ea8033a..ef01f5541d 100755 --- a/ALCF/model.sh +++ b/ALCF/model.sh @@ -15,6 +15,45 @@ declare -A A_NLAYERS declare -A A_HIDDEN declare -A A_ATEN_HEADS +# | =================== Llama 2 Architecture ==================== | +# | Hidden Size | Inter. Size | Atten Heads | Layers | Model Size | +# |:-----------:|:-----------:|:-----------:|:------:|:----------:| +# | 4096 | 11008 | 32 | 32 | 7b | +# | 5120 | 13824 | 40 | 40 | 13b | +# | 8192 | 28672 | 64 | 80 | 70b | + +MODEL_LLAMA_7B_KEY="LLAMA_7B" +A_NLAYERS[$MODEL_LLAMA_7B_KEY]=32 +A_ATEN_HEADS[$MODEL_LLAMA_7B_KEY]=32 +A_HIDDEN[$MODEL_LLAMA_7B_KEY]=4096 + +MODEL_LLAMA_13B_KEY="LLAMA_13B" +A_NLAYERS[$MODEL_LLAMA_13B_KEY]=40 +A_ATEN_HEADS[$MODEL_LLAMA_13B_KEY]=40 +A_HIDDEN[$MODEL_LLAMA_13B_KEY]=5120 + +MODEL_LLAMA_70B_KEY="LLAMA_70B" +A_NLAYERS[$MODEL_LLAMA_70B_KEY]=80 +A_ATEN_HEADS[$MODEL_LLAMA_70B_KEY]=64 +A_HIDDEN[$MODEL_LLAMA_70B_KEY]=8192 + +# HIDDEN_SIZE=4096 +# NUM_LAYERS=24 # e.g. llama-13b: 40 + + +# ┏━━━━━━━━━━━━━━━━━━━━┓ +# ┃ Llama2 ┃ +# ┗━━━━━━━━━━━━━━━━━━━━┛ +# MODEL_SIZE_KEY="LLAMA_24L" +# HIDDEN_SIZE=2048 # e.g. llama-13b: 5120 +# FFN_HIDDEN_SIZE=5504 # e.g. llama-13b: 13824 +# NUM_LAYERS=24 # e.g. llama-13b: 40 +# NUM_HEADS=16 # e.g. llama-13b: 40 +# SEQ_LENGTH=2048 +# NUM_KV_HEADS=4 # llama2 70B uses GQA +# + + # ┏━━━━━━━━━━━━━━━━━━━━┓ # ┃ GPT-3 Small: 125M ┃ # ┗━━━━━━━━━━━━━━━━━━━━┛ diff --git a/pretrain_llama.py b/pretrain_llama.py index bfc10704e4..67bf925492 100644 --- a/pretrain_llama.py +++ b/pretrain_llama.py @@ -51,6 +51,12 @@ ) if RANK == 0 and not DISABLE_WANDB: + # args = get_args() + # assert args is not None + # tensorboard_dir = args.tensorboard_dir + # if args.tensorboard_dir is not None: + # print(f'Setting (in env): {TENSORBOARD_DIR=}') + # os.environ['TENSORBOARD_DIR'] = args.tensorboard_dir project_name = os.environ.get( "WB_PROJECT", os.environ.get("WANDB_PROJECT", "GenSLM-Megatron-DS"), @@ -58,7 +64,7 @@ print("--------------------------------------------------") print(f"Setting up W&B from: {RANK} with {project_name}") print("--------------------------------------------------") - setup_wandb(project_name=project_name) + setup_wandb(project_name=project_name, sync_tensorboard=True) def model_provider(pre_process=True, post_process=True): @@ -66,6 +72,7 @@ def model_provider(pre_process=True, post_process=True): print_rank_0("building GPT model ...") see_memory_usage("Before Building Model", force=True) args = get_args() + assert args is not None config = core_transformer_config_from_args(args) # args = get_args() # timers = get_timers() @@ -151,23 +158,21 @@ def get_batch(data_iterator): """Generate a batch""" args = get_args() tokenizer = get_tokenizer() - + assert args is not None + assert tokenizer is not None # Items and their type. keys = ["text"] datatype = torch.int64 - # Broadcast data. if data_iterator is not None: data = next(data_iterator) else: data = None data_b = tensor_parallel.broadcast_data(keys, data, datatype) - # Unpack. tokens_ = data_b["text"].long() labels = tokens_[:, 1:].contiguous() tokens = tokens_[:, :-1].contiguous() - # Get the masks and postition ids. skip_mask = ( hasattr(args, "use_flash_attn") @@ -182,33 +187,29 @@ def get_batch(data_iterator): args.eod_mask_loss, skip_mask, ) - # For DS's sequence parallel seq_parallel_world_size = mpu.get_sequence_parallel_world_size() seq_parallel_world_rank = mpu.get_sequence_parallel_rank() - # For Megatron's sequence parallel if args.sequence_parallel: seq_parallel_world_size = mpu.get_tensor_model_parallel_world_size() seq_parallel_world_rank = mpu.get_tensor_model_parallel_rank() seq_length = tokens.size(1) - assert seq_length % seq_parallel_world_size == 0 sub_seq_length = seq_length // seq_parallel_world_size sub_seq_start = seq_parallel_world_rank * sub_seq_length sub_seq_end = (seq_parallel_world_rank + 1) * sub_seq_length - tokens = tokens[:, sub_seq_start:sub_seq_end] position_ids = position_ids[:, sub_seq_start:sub_seq_end] # For DS's sequence parallel if mpu.get_sequence_parallel_world_size() > 1: labels = labels[:, sub_seq_start:sub_seq_end] - return tokens, labels, loss_mask, attention_mask, position_ids def data_post_process(data, data_sampler_state_dict): args = get_args() + assert args is not None if args.data_efficiency_curriculum_learning: if ( "seqlen_truncate" in data_sampler_state_dict[ @@ -268,6 +269,7 @@ def get_batch_pipe(data): `data_iterator`""" args = get_args() tokenizer = get_tokenizer() + assert tokenizer is not None and args is not None # Items and their type. keys = ["text"] @@ -310,25 +312,36 @@ def loss_func(loss_mask, moe_loss, mos_loss, output_tensor): losses = output_tensor.float() loss_mask = loss_mask.view(-1).float() loss = torch.sum(losses.view(-1) * loss_mask) / loss_mask.sum() - # Reduce loss for logging. averaged_loss = average_losses_across_data_parallel_group([loss]) - if args.mos or args.kd: + if args.mos or args.kd: # type:ignore # assert max(args.num_experts) >= 1 loss = loss + moe_loss + mos_loss - if args.mos: - return loss, { + if args.mos: # type:ignore + # return loss, { + # "total loss": loss, + # "lm loss": averaged_loss[0], + # "moe loss": moe_loss, + # "mos loss": mos_loss, + # } + losses = { "total loss": loss, "lm loss": averaged_loss[0], "moe loss": moe_loss, "mos loss": mos_loss, } - elif args.kd: - return loss, { - "total loss": loss, - "lm loss": averaged_loss[0], - "moe loss": moe_loss, - "kd loss": mos_loss, + elif args.kd: # type:ignore + # return loss, { + # "total loss": loss, + # "lm loss": averaged_loss[0], + # "moe loss": moe_loss, + # "kd loss": mos_loss, + # } + losses = { + "total-loss": loss, + "lm-loss": averaged_loss[0], + "moe-loss": moe_loss, + "kd-loss": mos_loss, } print_rank_0( ">>> total loss: {}, lm loss {}, kd loss {}".format( @@ -336,15 +349,27 @@ def loss_func(loss_mask, moe_loss, mos_loss, output_tensor): ) ) else: - if max(args.num_experts) <= 1: - return loss, {"lm loss": averaged_loss[0]} + if max(args.num_experts) <= 1: # type:ignore + losses = {"lm-loss": averaged_loss[0]} + # return loss, {"lm loss": averaged_loss[0]} else: loss = loss + moe_loss - return loss, {"lm loss": averaged_loss[0], "moe loss": moe_loss} + losses = {"lm-loss": averaged_loss[0], "moe loss": moe_loss} + # return loss, {"lm loss": averaged_loss[0], "moe loss": moe_loss} + if wandb is not None and wandb.run is not None: + # wandb.run.log({}) + losses |= {'loss': loss} + wandb.run.log({f"Loss/{k}": v for k, v in losses.items()}) + return loss, losses def calculate_mos_loss( - args, stu_output, teacher_model, tokens, position_ids, attention_mask + args, + stu_output, + teacher_model, + tokens, + position_ids, + attention_mask, ): mos_loss = 0 alpha = args.kd_alpha_ce @@ -399,6 +424,7 @@ def forward_step(data_iterator, model): """Forward step.""" args = get_args() timers = get_timers() + assert timers is not None and args is not None # Get the batch. timers("batch-generator", log_level=2).start() @@ -407,8 +433,8 @@ def forward_step(data_iterator, model): ) timers("batch-generator").stop() - if args.data_efficiency_curriculum_learning: - args.curriculum_seqlen = tokens.size()[1] + if args.data_efficiency_curriculum_learning: # type: ignore + args.curriculum_seqlen = tokens.size()[1] # type: ignore if ( hasattr( args, @@ -423,12 +449,13 @@ def forward_step(data_iterator, model): torch.numel(tokens) ) - if args.mos or args.kd: + assert args is not None + if args.mos or args.kd: # type:ignore # The forward func can return either the loss or the logits, depending # on whether passing in the labels or not. stu_output, other_losses = model(tokens, position_ids, attention_mask) if ( - args.curriculum_learning_legacy + args.curriculum_learning_legacy # type:ignore and args.curriculum_seqlen < args.seq_length ): assert args.curriculum_seqlen is not None @@ -473,7 +500,7 @@ def forward_step(data_iterator, model): def train_valid_test_datasets_provider(train_val_test_num_samples): """Build train, valid, and test datasets.""" args = get_args() - + assert args is not None print_rank_0( "> building train, validation, and test datasets " "for GPT ..." ) From 657bb3e312e793d7b503f475b59e44c1aee44205 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 21 Dec 2023 17:47:44 -0600 Subject: [PATCH 028/268] Add `ALCF/train-llama.sh` --- ALCF/train-llama.sh | 74 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 74 insertions(+) create mode 100755 ALCF/train-llama.sh diff --git a/ALCF/train-llama.sh b/ALCF/train-llama.sh new file mode 100755 index 0000000000..6483b55c54 --- /dev/null +++ b/ALCF/train-llama.sh @@ -0,0 +1,74 @@ +#!/bin/bash --login + +TSTAMP=$(date "+%Y-%m-%d-%H%M%S") + +# HERE=$(python3 -c 'import os; print(os.getcwd())') +# ALCF_DIR="${HERE}/ALCF" +# +function WhereAmI() { + python3 -c 'import os; print(os.getcwd())' +} + +HERE=$(WhereAmI) +# ALCF_DIR=$(find "${HERE}" -name "ALCF") +ALCF_DIR="${HERE}/ALCF" + + +# ALCF_DIR="$(dirname $(dirname $(python3 -c 'import megatron; print(megatron.__file__)' | tail -1)))/ALCF" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" +echo "ALCF_DIR: ${ALCF_DIR}" +echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" + +# SOURCE=${BASH_SOURCE[0]} +# while [ -L "$SOURCE" ]; do # resolve $SOURCE until the file is no longer a symlink +# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +# SOURCE=$(readlink "$SOURCE") +# [[ $SOURCE != /* ]] && SOURCE=$DIR/$SOURCE # if $SOURCE was a relative symlink, we need to resolve it relative to the path where the symlink file was located +# done +# DIR=$( cd -P "$( dirname "$SOURCE" )" >/dev/null 2>&1 && pwd ) +# + +#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +#┃ Make sure we're not already running; if so, exit here ┃ +#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +PIDS=$(ps aux | egrep "$USER.+mpi.+pretrain.+.py" | grep -v grep | awk '{print $2}') +if [ -n "${PIDS}" ]; then + echo "Already running! Exiting!" + exit 1 +fi + +function sourceFile() { + FILE="$1" + echo "source-ing ${FILE}" + if [[ -f "${FILE}" ]]; then + # shellcheck source="${FILE}" + source "${FILE}" + else + echo "ERROR: UNABLE TO SOURCE ${FILE}" + fi +} + +#┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ +#┃ source ./launch.sh ┃ +#┃ which then sources ./{args.sh,setup.sh} ┃ +#┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ +LAUNCH_FILE="${ALCF_DIR}/launch.sh" + +sourceFile "${ALCF_DIR}/setup.sh" +# sourceFile "${ALCF_DIR}/model.sh" +# sourceFile "${ALCF_DIR}/args.sh" +sourceFile "${ALCF_DIR}/llama2_vars.sh" +sourceFile "${LAUNCH_FILE}" + +setup +# singleGPU "$@" 2>&1 & +# fullNode "$@" 2>&1 & +TORCH_VERSION=$(python3 -c 'import torch; print(torch.__version__)') +export TORCH_VERSION=$TORCH_VERSION +export CUDA_DEVICE_MAX_CONNECTIONS=1 +# elasticDistributed "$@" 2>&1 & +# elasticDistributed "$@" +# PID=$! +# wait $PID +elasticDistributed "$@" 2>&1 & + From 94e91d607f7f6ed2d99806c3a1d3491149af2c67 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Jan 2024 09:38:00 -0600 Subject: [PATCH 029/268] Update `DATA_PARENT` in `ALCF/args.sh` --- ALCF/args.sh | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/ALCF/args.sh b/ALCF/args.sh index 08d3d8fcd2..fb66f82b12 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -163,7 +163,12 @@ if [[ $(hostname) == nid* || $(hostname) == login* ]]; then DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" DATA_TYPE="BookCorpusDataset_text_document" elif [[ $(hostname) == theta* || $(hostname) == x3* ]]; then - DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" + # DATA_PARENT="/lus/grand" + DATA_PARENT="/lus/eagle/projects/datasets/Megatron-DeepSpeed/GenSLMSubSample200k" # GenSLMSubSample200k" + # DATA_TYPE="GenSLMSubSample200k" + # DATA_PARENT="/home/foremans/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed" + # DATA_TYPE="books-0001_text_document" + # DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" DATA_TYPE="genslm_subsample_200k_sequence_document" else echo "Unable to determine DATA_PARENT for $(hostname)." From d4545764b4a9d5b9155fc2a11a8f22fb9eeae00a Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Jan 2024 10:48:34 -0600 Subject: [PATCH 030/268] Update `pretrain_llama.py` --- pretrain_llama.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pretrain_llama.py b/pretrain_llama.py index 67bf925492..ab7ffc785c 100644 --- a/pretrain_llama.py +++ b/pretrain_llama.py @@ -64,7 +64,7 @@ print("--------------------------------------------------") print(f"Setting up W&B from: {RANK} with {project_name}") print("--------------------------------------------------") - setup_wandb(project_name=project_name, sync_tensorboard=True) + setup_wandb(project_name=project_name) def model_provider(pre_process=True, post_process=True): From 4ab9532dd094158c1e1dc321a8816d38eb4da1ae Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Jan 2024 10:48:56 -0600 Subject: [PATCH 031/268] Update `ALCF/args.sh` --- ALCF/args.sh | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/ALCF/args.sh b/ALCF/args.sh index fb66f82b12..17e0018110 100755 --- a/ALCF/args.sh +++ b/ALCF/args.sh @@ -163,7 +163,6 @@ if [[ $(hostname) == nid* || $(hostname) == login* ]]; then DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" DATA_TYPE="BookCorpusDataset_text_document" elif [[ $(hostname) == theta* || $(hostname) == x3* ]]; then - # DATA_PARENT="/lus/grand" DATA_PARENT="/lus/eagle/projects/datasets/Megatron-DeepSpeed/GenSLMSubSample200k" # GenSLMSubSample200k" # DATA_TYPE="GenSLMSubSample200k" # DATA_PARENT="/home/foremans/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed" @@ -181,7 +180,7 @@ DATA_PATH="${DATA_DIR}/${DATA_TYPE}" VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" # # -# [ "$(hostname)==login*" ] && DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" +# [ "$(hostname)==login*" ] && DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed"_ # [ "$(hostname)==nid*" ] && DATA_PARENT="/global/homes/f/foremans/m3957/foremans/projects/saforem2/Megatron-DeepSpeed" # # [ "$(hostname)==theta*" ] && DATA_PARENT="/lus/eagle/projects/datasets/BookCorpusDataset" # [ "$(hostname)==theta*" ] && DATA_PARENT="/lus/grand/projects/fallwkshp23/datasets/GenSLMSubSample200k" From d08b868244bd2ce9c49a1cb4dd7a518a9edc8337 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Jan 2024 10:49:23 -0600 Subject: [PATCH 032/268] Update `.gitignore` --- .gitignore | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 64270f0752..fc81539941 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,8 @@ +*.gz +*.txt +*.idx +*.bin +*.log __pycache__ # Distribution / packaging @@ -20,4 +25,4 @@ slurm* logs # Data folder -bookcorpus_data/ \ No newline at end of file +bookcorpus_data/ From e4bac7019db92cfe49d6eeac00b5721652e516fe Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Jan 2024 15:30:31 -0600 Subject: [PATCH 033/268] Create README.md --- ALCF/README.md | 93 ++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 93 insertions(+) create mode 100644 ALCF/README.md diff --git a/ALCF/README.md b/ALCF/README.md new file mode 100644 index 0000000000..89fb639da8 --- /dev/null +++ b/ALCF/README.md @@ -0,0 +1,93 @@ +# Megatron-DeepSpeed (@ [ALCF](https://alcf.anl.gov)) + +![image](https://github.com/argonne-lcf/Megatron-DeepSpeed/assets/5234251/f06df155-30e8-4894-a4c2-c17ff4b34ada) + +We describe below the instructions for launching distributed training with +Microsoft's Megatron-DeepSpeed and briefly describe some parallelism +strategies and various optimizations that are supported. + +> [!IMPORTANT] +> We maintain this (forked) version at +> [`argonne-lcf/Megatron-DeepSpeed`](https://github.com/argonne-lcf/Megatron-DeepSpeed) +> that has some [helper scripts](#helper-scripts) for launching and setting +> various training options. +> +> These changes are entirely self-contained **HERE** in [`ALCF/`](.) + +## Setup + +1. Load `conda` and activate base environment: + + ```bash + # load conda + activate base env + module load conda/2023-10-04 ; conda activate base + ``` + +1. Clone + [`argonne-lcf/Megatron-DeepSpeed`](https://github.com/argonne-lcf/Megatron-DeepSpeed) + and navigate into it: + + ```bash + # clone + navigate into Megatron-DeepSpeed repo + git clone https://github.com/argonne-lcf/Megatron-DeepSpeed + cd Megatron-DeepSpeed + ``` + +1. Make virtual environment (on top of base conda): + + ```bash + # make virtual environment (on top of base conda) + mkdir -p venvs/polaris/2023-10-04 + python3 -m venv venvs/polaris/2023-10-04 --system-site-packages + source venvs/polaris/2023-10-04/bin/activate + ``` + +1. Install missing dependency: + + ```bash + # install *missing dependency + python3 -m pip install "git+https://github.com/saforem2/ezpz" + ``` + +1. Launch training: + + ```bash + # ---- launch training ----------------------- + # - MODEL_SIZE_KEY: defined in ALCF/model.sh + # - other args: defined in ALCF/args.sh + # --------------------------------------------- + MODEL_SIZE_KEY="GPT25B" \ + SEQ_LEN=4096 \ + USE_FLASH_ATTN_V2=1 \ + MICRO_BATCH=1 \ + GAS=1 \ + SP_TYPE="megatron" \ + ZERO_STAGE=1 \ + ./ALCF/train-gpt3.sh + ``` + + +## Helper Scripts + +- 📂 [`ALCF/`](https://github.com/argonne-lcf/Megatron-DeepSpeed/tree/main/ALCF) + `├──` [`args.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/models.sh) + `├──` [`launch.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/launch.sh) + `├──` [`model.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/model.sh) + `├──` [`setup.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/setup.sh) + `├──` [`submit-pbs.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/submit-pbs.sh) + `├──` [`submit.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/submit.sh) + `└──` [`train-gpt3.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/train-gpt3.sh) + + +
+
ALCF/train-gpt3.sh +
Main entry point for training. This script will automatically source the rest of the required ALCF/*.sh scripts below
+
ALCF/model.sh
+
Contains some example model architectures for GPT3-style models
+
ALCF/args.sh
+
Logic for parsing / setting up runtime options for Megatron and DeepSpeed.
+
ALCF/setup.sh
+
Locate and activate virtual environment to be used, ensure MPI variables are set properly
+
ALCF/launch.sh
+
Identify available resources and build the command to be ran i.e. figure out how many: `{nodes, GPUs per node, GPUs total}`, to pass to `mpi{run,exec}` then, use this to build `mpiexec {mpiexec-args} python3 pretrain_gpt.py`
+
From aa7a580108ced77c0dd0335542bc228c008e3d87 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Thu, 1 Feb 2024 00:41:41 -0600 Subject: [PATCH 034/268] added support for training with multiple files --- megatron/arguments.py | 6 ++- megatron/tokenizer/tokenizer.py | 79 ++++++++++++++++++++++++--------- pretrain_gpt.py | 45 ++++++++++++++----- 3 files changed, 96 insertions(+), 34 deletions(-) diff --git a/megatron/arguments.py b/megatron/arguments.py index 30a95266b2..083bf30f6a 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -1203,6 +1203,9 @@ def _add_data_args(parser): 'single dataset used for all three: train, valid ' 'and test. It is exclusive to the other ' '--*-data-path args') + group.add_argument('--data-file-list', type=str, default=None, + help='The file with the list of dataset and weights') + group.add_argument('--split', type=str, default='969, 30, 1', help='Comma-separated list of proportions for training,' ' validation, and test split. For example the split ' @@ -1264,7 +1267,8 @@ def _add_data_args(parser): 'SentencePieceTokenizer', 'GPTSentencePieceTokenizer', 'HFTokenizer', - 'NullTokenizer'], + 'NullTokenizer', + 'Llama2Tokenizer'], help='What type of tokenizer to use.') group.add_argument('--tokenizer-model', type=str, default=None, help='Sentencepiece tokenizer model.') diff --git a/megatron/tokenizer/tokenizer.py b/megatron/tokenizer/tokenizer.py index 43c251bab1..023c2f756c 100644 --- a/megatron/tokenizer/tokenizer.py +++ b/megatron/tokenizer/tokenizer.py @@ -8,6 +8,8 @@ from transformers import AutoTokenizer from .bert_tokenization import FullTokenizer as FullBertTokenizer from .gpt2_tokenization import GPT2Tokenizer + + def build_tokenizer(args): """Initialize tokenizer.""" if args.rank == 0: @@ -35,12 +37,15 @@ def build_tokenizer(args): elif args.tokenizer_type == 'GPTSentencePieceTokenizer': assert args.tokenizer_model is not None tokenizer = _GPTSentencePieceTokenizer(args.tokenizer_model) + elif args.tokenizer_type == 'Llama2Tokenizer': + assert args.tokenizer_model is not None + tokenizer = _Llama2Tokenizer(args.tokenizer_model) elif args.tokenizer_type == 'NullTokenizer': assert args.vocab_size is not None tokenizer = _NullTokenizer(args.vocab_size) elif args.tokenizer_type == 'HFTokenizer': assert args.tokenizer_model is not None - tokenizer = _HFTokenizer(args.tokenizer_model,args.seq_length) + tokenizer = _HFTokenizer(args.tokenizer_model) else: raise NotImplementedError('{} tokenizer is not ' 'implemented.'.format(args.tokenizer_type)) @@ -504,6 +509,56 @@ def eod(self): def additional_special_tokens_ids(self): return None + +class _Llama2Tokenizer(_SentencePieceTokenizer): + """SentencePieceTokenizer-Megatron wrapper""" + + def __init__(self, model_file,): + super().__init__(model_file, vocab_extra_ids=0) + + def _initalize(self, vocab_extra_ids): + self._populate_vocab() + + # BOS / EOS token IDs + self.n_words: int = self.tokenizer.vocab_size() + self.bos_id: int = self.tokenizer.bos_id() + self.eos_id: int = self.tokenizer.eos_id() + self.pad_id: int = self.tokenizer.pad_id() + assert self.tokenizer.vocab_size() == self.tokenizer.get_piece_size() + + def tokenize(self, s: str, bos=True, eos=False): + '''Default args for text completion, not chat/dialog.''' + assert type(s) is str + t = self.tokenizer.encode(s) + if bos: + t = [self.bos_id] + t + if eos: + t = t + [self.eos_id] + return t + + def detokenize(self, ids): + return self.tokenizer.decode_ids(ids) + + @property + def cls(self): + return -1 + + @property + def sep(self): + return -1 + + @property + def mask(self): + return -1 + + @property + def eod(self): + return self.eos_id + + @property + def additional_special_tokens_ids(self): + return None + class _NullTokenizer: def __init__(self, vocab_size): vocab_size = int(vocab_size) @@ -540,28 +595,10 @@ def additional_special_tokens_ids(self): class _HFTokenizer(AbstractTokenizer): """HF Tokenizer""" - def __init__(self, tokenizer_name_or_path,max_seq_len): + def __init__(self, tokenizer_name_or_path): name = tokenizer_name_or_path super().__init__(name) - self.tokenizer = AutoTokenizer.from_pretrained(tokenizer_name_or_path,padding_side="right",use_fast=False) - - DEFAULT_PAD_TOKEN = "[PAD]" - DEFAULT_EOS_TOKEN = "" - DEFAULT_BOS_TOKEN = "" - DEFAULT_UNK_TOKEN = "" - special_tokens_dict = dict() - if self.tokenizer.pad_token is None: - special_tokens_dict["pad_token"] = DEFAULT_PAD_TOKEN - if self.tokenizer.eos_token is None: - special_tokens_dict["eos_token"] = DEFAULT_EOS_TOKEN - if self.tokenizer.bos_token is None: - special_tokens_dict["bos_token"] = DEFAULT_BOS_TOKEN - if self.tokenizer.unk_token is None: - special_tokens_dict["unk_token"] = DEFAULT_UNK_TOKEN - self.tokenizer.add_special_tokens(special_tokens_dict) - # if self.tokenizer.pad_token == None: - # self.tokenizer.pad_token= "[PAD]" - self.tokenizer.model_max_length = max_seq_len + self.tokenizer = AutoTokenizer.from_pretrained(tokenizer_name_or_path) self.encoder = self.tokenizer.get_vocab() self.decoder = {v: k for k, v in self.encoder.items()} diff --git a/pretrain_gpt.py b/pretrain_gpt.py index 86bfb74713..0c82e0ff0e 100644 --- a/pretrain_gpt.py +++ b/pretrain_gpt.py @@ -143,7 +143,6 @@ # if model_size is not None: # wandb.run.config.update({'MODEL_SIZE': model_size}) - def model_provider(pre_process=True, post_process=True): """Build the model.""" print_rank_0('building GPT model ...') @@ -219,7 +218,6 @@ def model_provider(pre_process=True, post_process=True): wandb.run.config.update({'num_params': num_params}) return model - def get_batch(data_iterator): """Generate a batch""" args = get_args() @@ -275,6 +273,7 @@ def get_batch(data_iterator): return tokens, labels, loss_mask, attention_mask, position_ids + def data_post_process(data, data_sampler_state_dict): args = get_args() if args.data_efficiency_curriculum_learning: @@ -300,6 +299,7 @@ def data_post_process(data, data_sampler_state_dict): args.data_efficiency_curriculum_learning_seqlen_type = None return data + def get_batch_pipe(data): """Modification of `get_batch` to work on `next(data_iterator)` instead of `data_iterator`""" args = get_args() @@ -385,6 +385,7 @@ def calculate_mos_loss(args, stu_output, teacher_model, tokens, position_ids, at mos_loss = mos_loss.div(args.seq_length) * beta return mos_loss + def forward_step(data_iterator, model): """Forward step.""" args = get_args() @@ -438,8 +439,24 @@ def train_valid_test_datasets_provider(train_val_test_num_samples): print_rank_0('> building train, validation, and test datasets ' 'for GPT ...') + files = [] + if args.data_file_list is not None: + with open(args.data_file_list, 'r') as flist: + for f in flist.readlines(): + w, fname = f.split() + files.append(float(w)) + files.append(fname) + elif len(args.data_path)==1 and os.path.isdir(args.data_path[0]): + path=args.data_path[0] + "/" + for f in os.listdir(path): + if (os.path.isfile(path + f) and f.find(".bin")!=-1): + files.append(1) + files.append(path + f.split(".bin")[0]) + else: + files = args.data_path + print_rank_0(f"file list {files}") train_ds, valid_ds, test_ds = build_train_valid_test_datasets( - data_prefix=args.data_path, + data_prefix=files, data_impl=args.data_impl, splits_string=args.split, train_valid_test_num_samples=train_val_test_num_samples, @@ -485,15 +502,19 @@ def git_ds_info(): def main(): # if RANK == 0: # setup_wandb() - - model = pretrain( - train_valid_test_datasets_provider, - model_provider, - ModelType.encoder_or_decoder, - forward_step, - args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, - data_post_process=data_post_process - ) + from torch.profiler import profile, record_function, ProfilerActivity + with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: + model = pretrain( + train_valid_test_datasets_provider, + model_provider, + ModelType.encoder_or_decoder, + forward_step, + args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + data_post_process=data_post_process + ) + args = get_args() + prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") + # # from megatron.training import get_model # if wandb.run is not None: # args = get_args() From 258269c08c7b429a59ac9c7d09289f686aab9f52 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Thu, 1 Feb 2024 00:44:21 -0600 Subject: [PATCH 035/268] added training script --- llama.sh | 64 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 64 insertions(+) create mode 100755 llama.sh diff --git a/llama.sh b/llama.sh new file mode 100755 index 0000000000..323a5f4730 --- /dev/null +++ b/llama.sh @@ -0,0 +1,64 @@ +#!/bin/bashOA +#PBS -l walltime=0:30:00 +#PBS -A datascience +#PBS -q debug-scaling +#PBS -l select=6 +#PBS -l filesystems=eagle:grand:home +export PPN=4 +export MD=/home/hzheng/ALCF-Megatron-DeepSpeed +module load conda/2023-10-04 +#conda activate /soft/datascience/megatron-deepspeed/2023-10-04 +conda activate $HOME/PolarisAT/pyenvs/megatron/2023-10-04 +cd ${PBS_O_WORKDIR} +export PBS_JOBSIZE=$(cat $PBS_NODEFILE | uniq | wc -l) +export TP=1 +export PP=1 +export MBS=1 +export BS=$((MBS*PBS_JOBSIZE*PPN/PP/TP)) +#export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/" +export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/wiki-en-simple/" +export DATA_FILE_LIST="/eagle/datasets//dolma//data_file_list_small.txt" +echo "BS: $BS\n PP:$PP \n TP: $TP, PBS_JOBSIZE: $PBS_JOBSIZE" +MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --hostfile $PBS_NODEFILE python3 ./pretrain_gpt.py \ + --tensor-model-parallel-size ${TP} \ + --pipeline-model-parallel-size ${PP} \ + --num-layers 32 \ + --hidden-size 4096 \ + --ffn-hidden-size 5504 \ + --num-attention-heads 32 \ + --micro-batch-size ${MBS} \ + --global-batch-size ${BS} \ + --seq-length 2048 \ + --max-position-embeddings 2048 \ + --train-iters 10 \ + --save ${MD}/checkpoints/LLAMA_7B_LLAMA_7B_z2_seqlen_mp1_pp1_sp24_nl32_hs4096_gb${BS}_mb1 \ + --load ${MD}/checkpoints/LLAMA_7B_LLAMA_7B_z2_seqlen_mp1_pp1_sp24_nl32_hs4096_gb${BS}_mb1 \ + --data-impl mmap \ + --tokenizer-type Llama2Tokenizer \ + --split 949,50,1 \ + --distributed-backend nccl \ + --lr 3e-4 \ + --lr-decay-style cosine \ + --min-lr 3e-5 \ + --weight-decay 0.1 \ + --clip-grad 1 \ + --lr-warmup-iters 2 \ + --optimizer adam \ + --adam-beta1 0.9 \ + --adam-beta2 0.95 \ + --log-interval 1 \ + --cpu-optimizer \ + --save-interval 10000 \ + --eval-interval 1000 \ + --eval-iters 10 --fp16 \ + --no-query-key-layer-scaling \ + --attention-dropout 0 \ + --hidden-dropout 0 \ + --use-rotary-position-embeddings \ + --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ + --untie-embeddings-and-output-weights \ + --swiglu --normalization layernorm --disable-bias-linear --num-key-value-heads 4 --tensorboard-dir ${MD}/outputs/LLAMA_7B_LLAMA_7B_z3_seqlen_mp1_pp1_sp24_nl32_hs4096_gb24_mb1/tensorboard --log-timers-to-tensorboard --tensorboard-log-interval 1 \ + --data-file-list ${DATA_FILE_LIST} \ + --data-path ${DATA_PATH} \ + --vocab-file ${MD}/dataset/gpt2-vocab.json --merge-file ${MD}/dataset/gpt2-merges.txt \ + --zero-stage=2 --deepspeed_config=${MD}/ds_config-gpt.json --deepspeed From d320cefaf5ba7dc23ee0fc032ef81304c7edc8fd Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 1 Feb 2024 13:10:43 -0600 Subject: [PATCH 036/268] Update `pretrain_gpt.py` --- pretrain_gpt.py | 251 ++++-------------------------------------------- 1 file changed, 20 insertions(+), 231 deletions(-) diff --git a/pretrain_gpt.py b/pretrain_gpt.py index 86bfb74713..785a129156 100644 --- a/pretrain_gpt.py +++ b/pretrain_gpt.py @@ -2,15 +2,11 @@ """Pretrain GPT""" -import os import torch import math -# import logging - from functools import partial from megatron import get_args from megatron import print_rank_0 -from rich import print from megatron import get_timers from megatron import get_tokenizer from megatron.core import mpu, tensor_parallel @@ -21,144 +17,32 @@ from megatron.utils import get_ltor_masks_and_position_ids from megatron.utils import average_losses_across_data_parallel_group, update_rotary_pos_emb from megatron.arguments import core_transformer_config_from_args -from megatron.utils import ( - report_memory, - throughput_calculator, - checkpoint_throughput_calculator -) -from pathlib import Path import deepspeed from deepspeed.runtime.utils import see_memory_usage from deepspeed.accelerator.real_accelerator import get_accelerator +import os import subprocess -import wandb -import time from torch import nn import torch.nn.functional as F -# from ezpz import get_logger -from ezpz.dist import setup_torch, get_world_size, setup_wandb - -RANK = setup_torch( - backend='deepspeed', - port='5432', -) -WORLD_SIZE = get_world_size() -LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" - -WANDB_MODE = os.environ.get('WANDB_MODE', None) -DISABLE_WANDB = WANDB_MODE is not None and str(WANDB_MODE).lower() == 'disabled' - -if RANK == 0 and not DISABLE_WANDB: - project_name = ( - os.environ.get( - 'WB_PROJECT', - os.environ.get( - 'WANDB_PROJECT', - 'GenSLM-Megatron-DS' - ), - ) - ) - print('--------------------------------------------------') - print(f"Setting up W&B from: {RANK} with {project_name}") - print('--------------------------------------------------') - setup_wandb(project_name=project_name) - - -# os.environ[''] -# wblogger = logging.getLogger("wandb") -# wblogger.setLevel(logging.DEBUG) - -# log = get_logger(__name__, level=LEVEL) -# -# log.critical(f"Hello from rank: {RANK} / {WORLD_SIZE} !") - -import socket -from typing import Optional -# log.critical(f"Setting up W&B from rank: {RANK} with {wb_project_name}") - - -# def setup_wandb(project_name: Optional[str] = None): -# print(f"Setting up W&B from: {RANK}") -# project_name = ( -# os.environ.get('WB_PROJECT', 'GenSLM-Megatron-DS') -# if project_name is None else project_name -# ) -# print(f"Setting up wandb from rank: {RANK}") -# print(f"Using: WB PROJECT: {project_name}") -# # if get_rank() == 0: -# # tensorboard_dir = args.tensorboard_dir -# tensorboard_dir = None -# # if config is None: -# tensorboard_dir = os.environ.get('TENSORBOARD_DIR', None) -# # else: -# # tensorboard_dir = ( -# # config.get( -# # 'tensorboard_dir', -# # None, # os.getcwd() -# # ) -# # ) -# if tensorboard_dir is not None: -# print(f'Patching tensorboard from {tensorboard_dir}') -# wandb.tensorboard.patch(root_logdir=tensorboard_dir) -# # wbrun_id = wandb.util.generate_id() -# current_time = time.time() -# # local_time = time.localtime(current_time) -# # if wandb.run is None: -# wandb.init( -# resume='allow', -# sync_tensorboard=(tensorboard_dir is not None), # True, -# project=(project_name if project_name is not None else None), -# # dir=(tensorboard_dir if tensorboard_dir is not None else None), -# ) -# assert wandb.run is not None -# print(f"W&B RUN: [{wandb.run.name}]({wandb.run.url})") -# wandb.run.config.update({'current_time': current_time}) -# model_size = os.environ.get('MODEL_SIZE', None) -# wandb.run.config.update({'world_size': get_world_size()}) -# # if config is not None: -# # wandb.run.config.update(config) -# env = { -# k: v for k, v in dict(os.environ).items() -# if not k.startswith('_ModuleTable') -# } -# _ = env.pop('LS_COLORS', None) -# _ = env.pop('PS1', None) -# wandb.run.config.update({'env': env}) -# hostname = socket.gethostbyaddr(socket.gethostname())[0] -# if hostname.startswith('theta'): -# wandb.run.config.update({'machine': 'ThetaGPU'}) -# elif hostname.startswith('x3'): -# wandb.run.config.update({'machine': 'Polaris'}) -# elif hostname.startswith('x1'): -# wandb.run.config.update({'machine': 'Sunspot'}) -# elif hostname.startswith('nid'): -# wandb.run.config.update({'machine': 'Perlmutter'}) -# elif hostname.startswith('login'): -# wandb.run.config.update({'machine': 'NERSC'}) -# else: -# wandb.run.config.update({'machine': hostname}) -# if model_size is not None: -# wandb.run.config.update({'MODEL_SIZE': model_size}) - def model_provider(pre_process=True, post_process=True): """Build the model.""" + print_rank_0('building GPT model ...') - see_memory_usage("Before Building Model", force=True) + see_memory_usage(f"Before Building Model", force=True) + args = get_args() config = core_transformer_config_from_args(args) - # args = get_args() - # timers = get_timers() - if wandb.run is not None: - print(f"Updating WandB run: [{wandb.run.name}]({wandb.run.url})") - wandb.run.config.update({"args": vars(args)}) - if RANK == 0: - git_ds_info() - - with deepspeed.zero.Init(sequence_data_parallel_group=mpu.get_sequence_data_parallel_group(), + if hasattr(mpu, 'get_sequence_parallel_group'): + dpg = mpu.get_sequence_parallel_group() + elif hasattr(mpu, 'get_data_parallel_group'): + dpg = mpu.get_data_parallel_group() + else: + dpg = None + with deepspeed.zero.Init(data_parallel_group=dpg, remote_device=None if args.remote_device == 'none' else args.remote_device, config_dict_or_path=args.deepspeed_config_dict, enabled=args.zero_stage == 3, @@ -202,21 +86,7 @@ def model_provider(pre_process=True, post_process=True): pre_process=pre_process, post_process=post_process ) - num_params = sum(p.numel() for p in model.parameters() if p.requires_grad) - # print_rank_0('\n ------------------------ ') - # print_rank_0(f'num of parameters {num_params}') - # print_rank_0('------------------------\n ') - print_rank_0(80 * '-') - print_rank_0(f"Number of parameters in model: {num_params}") - print_rank_0(80 * '-') - see_memory_usage("After Building Model", force=True) - if wandb.run is not None: - wandb.run.watch( - model, - log='all', - log_graph=True, - ) - wandb.run.config.update({'num_params': num_params}) + see_memory_usage(f"After Building Model", force=True) return model @@ -242,8 +112,7 @@ def get_batch(data_iterator): tokens = tokens_[:, :-1].contiguous() # Get the masks and postition ids. - skip_mask = hasattr(args, 'use_flash_attn') or hasattr(args, 'flash_attn_triton') - # skip_mask = args.use_flash_attn or args.use_flash_attn_triton + skip_mask = args.use_flash_attn or args.use_flash_attn_triton attention_mask, loss_mask, position_ids = get_ltor_masks_and_position_ids( tokens, tokenizer.eod, @@ -482,91 +351,11 @@ def git_ds_info(): print(f'**** Git info for Megatron: git_hash={git_hash} git_branch={git_branch} ****') -def main(): - # if RANK == 0: - # setup_wandb() - - model = pretrain( - train_valid_test_datasets_provider, - model_provider, - ModelType.encoder_or_decoder, - forward_step, - args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, - data_post_process=data_post_process - ) - # # from megatron.training import get_model - # if wandb.run is not None: - # args = get_args() - # timers = get_timers() - # # model = get_model(model_provider, ModelType.encoder_or_decoder) - # elapsed_time = timers('interval-time').elapsed(barrier=True) - # total_iterations = os.environ.get( - # "TOTAL_ITERATIONS", - # (args.train_iters + args.eval_iters) - # ) - # seq_len = args.seq_length - # elapsed_time_per_iteration = elapsed_time / total_iterations - # if model is not None: - # samples_per_sec, tflops, approx_params_in_billions = throughput_calculator( - # model, - # args, - # elapsed_time, - # total_iterations, - # ) - # # Compute throughput. - # samples_per_sec_per_replica = samples_per_sec / args.data_parallel_size - # tokens_per_sec = samples_per_sec * seq_len - # tokens_per_sec_per_replica = tokens_per_sec / args.data_parallel_size - # sample_consumption_rate = args.consumed_train_samples / elapsed_time - # token_consumption_rate = args.consumed_train_tokens / elapsed_time - # # Tensorboard values. - # tdata = { - # # 'iteration': iteration, - # 'consumed_train_samples': args.consumed_train_samples, - # 'consumed_train_tokens': args.consumed_train_tokens, - # # 'learning_rate': learning_rate, - # # 'batch_size': batch_size, - # # 'loss_scale': loss_scale, - # # 'grad_norm': grad_norm, - # } - # # for key in loss_dict: - # # tdata[f'lm-loss/{key}'] = loss_dict[key] - # - # tdata = {f'train/{k}': v for k, v in tdata.items()} - # # if wbrun is not None and wbrun is wandb.run: - # if wandb.run is not None: - # wandb.run.log(tdata, commit=False) - # tput = { - # 'throughput/iteration-time': elapsed_time_per_iteration, # 1000 ms / s - # 'throughput/samples_per_sec': samples_per_sec, - # 'throughput/samples_per_sec_per_replica': samples_per_sec_per_replica, - # 'throughput/tokens_per_sec': tokens_per_sec, - # 'throughput/tokens_per_sec_per_replica': tokens_per_sec_per_replica, - # 'throughput/tflops': tflops, - # 'throughput/approx_params_in_billions': approx_params_in_billions, - # 'throughput/sample_consumption_rate': sample_consumption_rate, - # 'throughput/token_consumption_rate': token_consumption_rate, - # 'throughput/elapsed_ms_per_iteration': elapsed_time_per_iteration, - # } - # wandb.run.log(tput) - return model - - - if __name__ == "__main__": - # git_ds_info() - # pretrain(train_valid_test_datasets_provider, - # model_provider, - # ModelType.encoder_or_decoder, - # forward_step, - # args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, - # data_post_process=data_post_process) - import sys - import deepspeed.comm as dist - model = main() - dist.log_summary() - if wandb.run is not None: - print(f"wandb.run.name: {wandb.run.name}") - print(f"wandb.run.url: {wandb.run.url}") - wandb.finish() - sys.exit() + git_ds_info() + pretrain(train_valid_test_datasets_provider, + model_provider, + ModelType.encoder_or_decoder, + forward_step, + args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + data_post_process=data_post_process) From 080003144a529f588c9f8b9d2d37472ae6d725d3 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 1 Feb 2024 13:12:02 -0600 Subject: [PATCH 037/268] Add `set_params.sh` --- set_params.sh | 110 ++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 110 insertions(+) create mode 100644 set_params.sh diff --git a/set_params.sh b/set_params.sh new file mode 100644 index 0000000000..40682a9fe3 --- /dev/null +++ b/set_params.sh @@ -0,0 +1,110 @@ +#!/bin/bash login +# echo "!!!please use generate_hostfile.sh to set hostfile for 18 nodes before training" +export WORLD_SIZE=${WORLD_SIZE:-216} +export MICRO_BATCH=${MICRO_BATCH:-1} +export NLAYERS=${NLAYERS:-96} +export HIDDEN=${HIDDEN:-12288} +export HEADS=${HEADS:-96} +export SEQ=${SEQ:-2048} +export TRAIN_ITER=${TRAIN_ITER:-20} +export ZERO_STAGE=${ZERO_STAGE:-3} +export DTYPE=${DTYPE:-fp16} +export TP=${TP:-1} +export PP=${PP:-1} +export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} +export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) + + +# bash $LLM_DK_DIR/intel-extension-for-deepspeed/examples/gpt.sh $@ + +# Disabling tensor/pipeline parallelism +TP=${TP:-1} +PP=${PP:-1} + +export DATA_PARENT="/home/foremans/polaris/projects/saforem2/Megatron-DeepSpeed" +export DATA_TYPE="BookCorpusDataset_text_document" +# export DATA_PARENT="/lus/eagle/projects/datasets/Megatron-DeepSpeed/GenSLMSubSample200k" +# export DATA_TYPE="genslm_subsample_200k_sequence_document" +export DATA_DIR="${DATA_PARENT}/dataset" +export DATA_PATH="${DATA_DIR}/${DATA_TYPE}" +export VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" +export MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" + + +DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" +bash ./generate_config.sh ${DS_CONFIG} || exit 1 + +OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} +mkdir -p $OUTPUT_DIR +echo "!!!Please see logs at ${OUTPUT_DIR}" + +# Hostfile path +hostfile_deepspeed=./hostfile_deepspeed +hostfile_mpich=./hostfile_mpich +cat $PBS_NODEFILE > hostfile_mpich +cat $PBS_NODEFILE > hostfile_deepspeed ; sed -e 's/$/ slots=4/' -i hostfile_deepspeed + +ds_args=" " +ds_args=" --deepspeed ${ds_args}" +if [ $PP == 1 ]; then + ds_args=" --no-pipeline-parallel ${ds_args}" +fi +ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" +ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" +# we are now using activation checkpoint provided by megatron, see below. +# ds_args=" --deepspeed-activation-checkpointing ${ds_args}" + +# take custom args +custom_args=" $@" + +# launcher setting +LAUNCHER=${LAUNCHER:-MPICH} +if [[ $LAUNCHER == "deepspeed" ]]; then + launcher="" +else + launcher="--force_multi --hostfile $hostfile_deepspeed --launcher=${LAUNCHER} --launcher_args='-hostfile ${hostfile_mpich}'" +fi + +NCCL=${NCCL:-nccl} + +run_cmd=" + deepspeed $launcher pretrain_gpt.py \ + --tensor-model-parallel-size $TP \ + --pipeline-model-parallel-size $PP \ + --num-layers $NLAYERS \ + --hidden-size $HIDDEN \ + --num-attention-heads $HEADS \ + --seq-length $SEQ \ + --max-position-embeddings $SEQ \ + --micro-batch-size $MICRO_BATCH \ + --global-batch-size $GLOBAL_BATCH \ + --train-iters $TRAIN_ITER \ + --lr 0.00015 \ + --lr-warmup-fraction .01 \ + --lr-decay-iters 320000 \ + --lr-decay-style cosine \ + --log-interval 1 \ + --eval-iters 100 \ + --eval-interval 100 \ + --data-path $DATA_PATH \ + --vocab-file $VOCAB_FILE \ + --merge-file $MERGE_FILE \ + --save-interval 500 \ + --split 100,0,0 \ + --$DTYPE \ + --checkpoint-activations \ + --deepspeed-activation-checkpointing + $ds_args \ + --no-masked-softmax-fusion \ + --no-bias-gelu-fusion \ + --no-bias-dropout-fusion \ + --no-gradient-accumulation-fusion \ + --distributed-backend $NCCL \ + --num-workers 0 \ + $custom_args \ + |& tee $OUTPUT_DIR/output.log + " + +echo ${run_cmd} +eval ${run_cmd} +set +x From a5eabe5fbf6ffa99ab03769d9dd81c657fa721ac Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 1 Feb 2024 13:12:11 -0600 Subject: [PATCH 038/268] Add `generate_config.sh` --- generate_config.sh | 133 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 133 insertions(+) create mode 100644 generate_config.sh diff --git a/generate_config.sh b/generate_config.sh new file mode 100644 index 0000000000..210220e192 --- /dev/null +++ b/generate_config.sh @@ -0,0 +1,133 @@ +#!/bin/bash --login + +for v in "$GLOBAL_BATCH" "$MICRO_BATCH" "$GRAD_ACC_STEPS" "$ZERO_STAGE" \ + "$PP" "$DTYPE" +do + if [ -z $v ]; then + echo "Please export required envs before execute $0" + exit 1 + fi +done + +if [ $# -ne 1 ]; then + echo "Usage: $0 config_file" + exit 1 +fi + +extra="" +common="\ + \"train_batch_size\": $GLOBAL_BATCH, + \"train_micro_batch_size_per_gpu\": $MICRO_BATCH, + \"steps_per_print\": 1, + \"gradient_accumulation_steps\": $GRAD_ACC_STEPS, + \"optimizer\": { + \"type\": \"Adam\", + \"params\": { + \"lr\": 0.00015, + \"weight_decay\": 1e-2 + } + }, + \"zero_allow_untested_optimizer\": true, + \"gradient_clipping\": 1.0, + \"activation_checkpointing\": { + \"partition_activations\": true, + \"contiguous_memory_optimization\": false + }, + \"wall_clock_breakdown\": false," + +flops_profiler="\ + \"flops_profiler\": { + \"enabled\": false, + \"profile_step\": 45, + \"module_depth\": -1, + \"top_modules\": 1, + \"detailed\": true, + \"output_file\": null + }" + +if [[ $DTYPE == "bf16" ]]; then +dtype="\ + \"communication_data_type\": \"bfp16\", + \"fp16\": { + \"enabled\": false, + \"loss_scale\": 0, + \"loss_scale_window\": 1000, + \"hysteresis\": 2, + \"min_loss_scale\": 1 + }, + \"bfloat16\": { + \"enabled\": true, + \"loss_scale\": 1.0 + }," +else +dtype="\ + \"communication_data_type\": \"fp16\", + \"fp16\": { + \"enabled\": true, + \"loss_scale\": 0, + \"loss_scale_window\": 1000, + \"hysteresis\": 2, + \"min_loss_scale\": 1 + }, + \"bfloat16\": { + \"enabled\": false, + \"loss_scale\": 1.0 + }," +fi + +if [ $ZERO_STAGE == 3 ]; then +zero="\ + \"zero_optimization\": { + \"stage\": 3, + \"reduce_scatter\": false, + \"stage3_max_live_parameters\": 3e9, + \"stage3_max_reuse_distance\": 3e9, + \"stage3_param_persistence_threshold\": 1e5, + \"stage3_prefetch_bucket_size\": 5e7, + \"contiguous_gradients\": true, + \"overlap_comm\": true, + \"reduce_bucket_size\": 90000000, + \"sub_group_size\": 1e9, + \"offload_optimizer\": { + \"device\": \"none\", + \"buffer_count\": 4, + \"pipeline_read\": false, + \"pipeline_write\": false, + \"pin_memory\": true + } + }," +elif [ $ZERO_STAGE == 2 ] || [ $ZERO_STAGE == 1 ]; then +zero="\ + \"zero_optimization\": { + \"stage\": $ZERO_STAGE + }," + if [ $ZERO_STAGE == 1 ]; then + if [ $PP > 1 ]; then + extra="\ + \"data_types\": { + \"grad_accum_dtype\": \"fp32\" + }, + \"comms_logger\": { + \"enabled\": true, + \"verbose\": false, + \"prof_all\": true, + \"debug\": false + }," + else + echo 'please add the config for zero_stage 1 without pipeline-parallelism' + fi + fi +else + echo 'Please add the correct config set!!!' +fi + +# flops_profiler must at the end because no ',' is allowed at the end +cat < $1 +{ +$common +$zero +$dtype +$extra +$flops_profiler +} +EOT From 3baad6fddedc32337b5f9d4065f2cc2b3625ac1f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 1 Feb 2024 13:25:07 -0600 Subject: [PATCH 039/268] Add `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 387 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 387 insertions(+) create mode 100644 pretrain_gpt_alcf.py diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py new file mode 100644 index 0000000000..708a3b7864 --- /dev/null +++ b/pretrain_gpt_alcf.py @@ -0,0 +1,387 @@ +# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved. + +"""Pretrain GPT""" + +import torch +import math +from functools import partial +from megatron import get_args +from megatron import print_rank_0 +from megatron import get_timers +from megatron import get_tokenizer +from megatron.core import mpu, tensor_parallel +from megatron.core.enums import ModelType +from megatron.data.gpt_dataset import build_train_valid_test_datasets +from megatron.model import GPTModel, GPTModelPipe +from megatron.training import pretrain +from megatron.utils import get_ltor_masks_and_position_ids +from megatron.utils import average_losses_across_data_parallel_group, update_rotary_pos_emb +from megatron.arguments import core_transformer_config_from_args + +import deepspeed +from deepspeed.runtime.utils import see_memory_usage +from deepspeed.accelerator.real_accelerator import get_accelerator +import os +import subprocess + +from torch import nn +import torch.nn.functional as F + +# from ezpz.configs import get_logging_config +from ezpz.dist import get_rank, get_world_size, setup_wandb # , setup_torch + +RANK = get_rank() +WORLD_SIZE = get_world_size() + +if RANK == 0 and not ( + (wbmode := os.environ.get('WANDB_MODE')) + and (wbmode is not None and str(wbmode).lower() == 'disabled') +): + project_name = ( + os.environ.get( + 'WB_PROJECT', + os.environ.get( + 'WANDB_PROJECT', + 'GenSLM-Megatron-DS' + ), + ) + ) + print('--------------------------------------------------') + print(f"Setting up W&B from: {RANK} with {project_name}") + print('--------------------------------------------------') + setup_wandb(project_name=project_name) + + +def model_provider(pre_process=True, post_process=True): + """Build the model.""" + + print_rank_0('building GPT model ...') + see_memory_usage(f"Before Building Model", force=True) + + args = get_args() + config = core_transformer_config_from_args(args) + if hasattr(mpu, 'get_sequence_parallel_group'): + dpg = mpu.get_sequence_parallel_group() + elif hasattr(mpu, 'get_data_parallel_group'): + dpg = mpu.get_data_parallel_group() + else: + dpg = None + with deepspeed.zero.Init(data_parallel_group=dpg, + remote_device=None if args.remote_device == 'none' else args.remote_device, + config_dict_or_path=args.deepspeed_config_dict, + enabled=args.zero_stage == 3, + mpu=mpu): + if args.deepspeed and not args.no_pipeline_parallel: + model = GPTModelPipe( + config=config, + num_tokentypes=0, + parallel_output=True + ) + # This is a hack to give us a reference to get_batch_pipe from within training.py + # We need to call model.set_batch_fn after deepspeed.initialize + model._megatron_batch_fn = get_batch_pipe + + # Predompute the attention mask and store it in args. This avoids having to + # pipeline it as an activation during training. The mask is constant, and thus + # we can reuse it. + attention_mask = torch.tril(torch.ones( + (1, args.seq_length, args.seq_length), device=get_accelerator().current_device_name())).view( + 1, 1, args.seq_length, args.seq_length) + + # Convert attention mask to binary: + attention_mask = (attention_mask < 0.5) + if args.fp16: + attention_mask = attention_mask.half() + elif args.bf16: + attention_mask = attention_mask.bfloat16() + + # Attention mask must be bool. + args.attn_mask = attention_mask.to(torch.bool) + + # For prertaining, since sequence length is fixed, cache rotary embedding in args, to avoid communicating around + if args.use_rotary_position_embeddings: + update_rotary_pos_emb(args.seq_length) + + else: + model = GPTModel( + config=config, + num_tokentypes=0, + parallel_output=True, + pre_process=pre_process, + post_process=post_process + ) + see_memory_usage(f"After Building Model", force=True) + return model + + +def get_batch(data_iterator): + """Generate a batch""" + args = get_args() + tokenizer = get_tokenizer() + + # Items and their type. + keys = ['text'] + datatype = torch.int64 + + # Broadcast data. + if data_iterator is not None: + data = next(data_iterator) + else: + data = None + data_b = tensor_parallel.broadcast_data(keys, data, datatype) + + # Unpack. + tokens_ = data_b['text'].long() + labels = tokens_[:, 1:].contiguous() + tokens = tokens_[:, :-1].contiguous() + + # Get the masks and postition ids. + skip_mask = args.use_flash_attn or args.use_flash_attn_triton + attention_mask, loss_mask, position_ids = get_ltor_masks_and_position_ids( + tokens, + tokenizer.eod, + args.reset_position_ids, + args.reset_attention_mask, + args.eod_mask_loss, + skip_mask) + + # For DS's sequence parallel + seq_parallel_world_size = mpu.get_sequence_parallel_world_size() + seq_parallel_world_rank = mpu.get_sequence_parallel_rank() + + # For Megatron's sequence parallel + if args.sequence_parallel: + seq_parallel_world_size = mpu.get_tensor_model_parallel_world_size() + seq_parallel_world_rank = mpu.get_tensor_model_parallel_rank() + seq_length = tokens.size(1) + + assert seq_length % seq_parallel_world_size == 0 + sub_seq_length = seq_length // seq_parallel_world_size + sub_seq_start = seq_parallel_world_rank * sub_seq_length + sub_seq_end = (seq_parallel_world_rank + 1) * sub_seq_length + + tokens = tokens[:, sub_seq_start:sub_seq_end] + position_ids = position_ids[:, sub_seq_start:sub_seq_end] + # For DS's sequence parallel + if mpu.get_sequence_parallel_world_size() > 1: + labels = labels[:, sub_seq_start:sub_seq_end] + + return tokens, labels, loss_mask, attention_mask, position_ids + +def data_post_process(data, data_sampler_state_dict): + args = get_args() + if args.data_efficiency_curriculum_learning: + if 'seqlen_truncate' in data_sampler_state_dict['current_difficulties']: + args.data_efficiency_curriculum_learning_seqlen_type = 'seqlen_truncate' + current_seqlen = data_sampler_state_dict['current_difficulties']['seqlen_truncate'] + if current_seqlen < args.seq_length: + data['text'] = data['text'][:, :(current_seqlen+1)].contiguous() + elif 'seqlen_reshape' in data_sampler_state_dict['current_difficulties']: + args.data_efficiency_curriculum_learning_seqlen_type = 'seqlen_reshape' + current_seqlen = data_sampler_state_dict['current_difficulties']['seqlen_reshape'] + if current_seqlen < args.seq_length: + orig_num_token = torch.numel(data['text']) + reshape_len = (data['text'].size()[1] // (current_seqlen+1)) * (current_seqlen+1) + data['text'] = torch.cat((data['text'][:, :reshape_len].contiguous().view(-1, current_seqlen+1), + data['text'][:, -(current_seqlen+1):]), 0).contiguous() + num_row = math.ceil(orig_num_token / (current_seqlen+1)) + num_row = min(num_row, data['text'].size()[0]) + if num_row > 1 and num_row % 2 != 0: + num_row -= 1 + data['text'] = data['text'][:num_row, :].contiguous() + else: + args.data_efficiency_curriculum_learning_seqlen_type = None + return data + +def get_batch_pipe(data): + """Modification of `get_batch` to work on `next(data_iterator)` instead of `data_iterator`""" + args = get_args() + tokenizer = get_tokenizer() + + # Items and their type. + keys = ['text'] + datatype = torch.int64 + + # Broadcast data. + data_b = tensor_parallel.broadcast_data(keys, data, datatype) + + # Unpack. + tokens_ = data_b['text'].long() + labels = tokens_[:, 1:].contiguous() + tokens = tokens_[:, :-1].contiguous() + + # Get the masks and postition ids. + attention_mask, loss_mask, position_ids = get_ltor_masks_and_position_ids( + tokens, + tokenizer.eod, + args.reset_position_ids, + args.reset_attention_mask, + args.eod_mask_loss) + if args.curriculum_learning_legacy and args.curriculum_seqlen < tokens.size()[1]: + # seqlen-based curriculum learning + # tokens, position_ids, labels, loss_mask have size [batch size, seqlen] + tokens = tokens[:, :args.curriculum_seqlen].contiguous() + position_ids = position_ids[:, :args.curriculum_seqlen].contiguous() + if labels is not None: + labels = labels[:, :args.curriculum_seqlen].contiguous() + loss_mask = loss_mask[:, :args.curriculum_seqlen].contiguous() + + return (tokens, position_ids, attention_mask), (labels, loss_mask) + + +def loss_func(loss_mask, moe_loss, mos_loss, output_tensor): + args = get_args() + losses = output_tensor.float() + loss_mask = loss_mask.view(-1).float() + loss = torch.sum(losses.view(-1) * loss_mask) / loss_mask.sum() + + # Reduce loss for logging. + averaged_loss = average_losses_across_data_parallel_group([loss]) + if args.mos or args.kd: + # assert max(args.num_experts) >= 1 + loss = loss + moe_loss + mos_loss + if args.mos: + return loss, {'total loss': loss, 'lm loss': averaged_loss[0], 'moe loss': moe_loss, 'mos loss': mos_loss} + elif args.kd: + return loss, {'total loss': loss, 'lm loss': averaged_loss[0], 'moe loss': moe_loss, 'kd loss': mos_loss} + print_rank_0('>>> total loss: {}, lm loss {}, kd loss {}'.format(loss, averaged_loss[0], mos_loss)) + else: + if max(args.num_experts) <= 1: + return loss, {'lm loss': averaged_loss[0]} + else: + loss = loss + moe_loss + return loss, {'lm loss': averaged_loss[0], 'moe loss': moe_loss} + +def calculate_mos_loss(args, stu_output, teacher_model, tokens, position_ids, attention_mask): + mos_loss = 0 + alpha = args.kd_alpha_ce + beta = args.kd_beta_ce + kd_temp = args.kd_temp + + if teacher_model: + with torch.no_grad(): + if args.curriculum_learning_legacy and args.curriculum_seqlen < args.seq_length: + assert args.curriculum_seqlen is not None + curriculum_seqlen = args.curriculum_seqlen + tokens = tokens[:, :curriculum_seqlen].contiguous() + position_ids = position_ids[:, :curriculum_seqlen].contiguous() + attention_mask = attention_mask[:, :, :curriculum_seqlen, :curriculum_seqlen].contiguous() + # No need to truncate labels as we do not need it for the teacher logits + tea_output, tea_other_losses = teacher_model(tokens, position_ids, attention_mask) + assert stu_output.size() == tea_output.size(), 'teacher and student output should match in size. Student: {}, Teacher: {}, CL seq length {}'.format(stu_output.size(), tea_output.size(), args.curriculum_seqlen) + + student_logits = F.log_softmax(stu_output / kd_temp, dim=2) + tea_logits = F.softmax(tea_output / kd_temp, dim=2) # The target logits is expected to be probabilities. If we use log_softmax, then we need to set target_log to true when initializing the KLDivLoss. + + mos_loss = kd_temp * kd_temp * nn.KLDivLoss(reduction='batchmean')(student_logits, tea_logits) + + mos_loss = mos_loss.div(args.seq_length) * beta + return mos_loss + +def forward_step(data_iterator, model): + """Forward step.""" + args = get_args() + timers = get_timers() + + # Get the batch. + timers('batch-generator', log_level=2).start() + tokens, labels, loss_mask, attention_mask, position_ids = get_batch( + data_iterator) + timers('batch-generator').stop() + + if args.data_efficiency_curriculum_learning: + args.curriculum_seqlen = tokens.size()[1] + if hasattr(args, 'data_efficiency_curriculum_learning_seqlen_type') and \ + args.data_efficiency_curriculum_learning_seqlen_type == 'seqlen_reshape': + args.data_efficiency_curriculum_learning_numel = torch.numel(tokens) + + if args.mos or args.kd: + # The forward func can return either the loss or the logits, depending on whether passing in the labels or not. + stu_output, other_losses = model(tokens, position_ids, attention_mask) + if args.curriculum_learning_legacy and args.curriculum_seqlen < args.seq_length: + assert args.curriculum_seqlen is not None + labels = labels[:, :args.curriculum_seqlen].contiguous() + output_tensor = tensor_parallel.vocab_parallel_cross_entropy(stu_output.contiguous().float(), labels) + else: + output_tensor, other_losses = model(tokens, position_ids, attention_mask, + labels=labels) + if args.curriculum_learning_legacy and args.curriculum_seqlen < args.seq_length: + loss_mask = loss_mask[:, :args.curriculum_seqlen].contiguous() + + moe_losses = [] + for moe_loss in other_losses: + if moe_loss is not None: + moe_losses.append(moe_loss) + moe_loss = sum(moe_losses) * args.moe_loss_coeff + + mos_loss = 0 + if args.mos or args.kd: + assert model.training + if args.teacher_forward and args.teacher_model is not None: + mos_loss = calculate_mos_loss(args, stu_output, + args.teacher_model[0], tokens, position_ids, attention_mask) + + # Output_tensor stores the standard loss, loos_func calculates the total loss. + return output_tensor, partial(loss_func, loss_mask, moe_loss, mos_loss) + + +def train_valid_test_datasets_provider(train_val_test_num_samples): + """Build train, valid, and test datasets.""" + args = get_args() + + print_rank_0('> building train, validation, and test datasets ' + 'for GPT ...') + train_ds, valid_ds, test_ds = build_train_valid_test_datasets( + data_prefix=args.data_path, + data_impl=args.data_impl, + splits_string=args.split, + train_valid_test_num_samples=train_val_test_num_samples, + seq_length=args.seq_length, + seed=args.seed, + skip_warmup=(not args.mmap_warmup), + train_data_prefix=args.train_data_path, + valid_data_prefix=args.valid_data_path, + test_data_prefix=args.test_data_path, + data_cache_path=args.data_cache_path) + print_rank_0("> finished creating GPT datasets ...") + + return train_ds, valid_ds, test_ds + + +def command_exists(cmd): + result = subprocess.Popen(f'type {cmd}', stdout=subprocess.PIPE, shell=True) + return result.wait() == 0 + + +def git_ds_info(): + if RANK != 0: + return + from deepspeed.env_report import main as ds_report + ds_report() + + # Write out version/git info + git_hash_cmd = "git rev-parse --short HEAD" + git_branch_cmd = "git rev-parse --abbrev-ref HEAD" + if command_exists('git'): + try: + result = subprocess.check_output(git_hash_cmd, shell=True) + git_hash = result.decode('utf-8').strip() + result = subprocess.check_output(git_branch_cmd, shell=True) + git_branch = result.decode('utf-8').strip() + except subprocess.CalledProcessError: + git_hash = "unknown" + git_branch = "unknown" + else: + git_hash = "unknown" + git_branch = "unknown" + print(f'**** Git info for Megatron: git_hash={git_hash} git_branch={git_branch} ****') + + +if __name__ == "__main__": + git_ds_info() + pretrain(train_valid_test_datasets_provider, + model_provider, + ModelType.encoder_or_decoder, + forward_step, + args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + data_post_process=data_post_process) From f51f1fa15126ee0e7599b265ce3de274cf17e5b6 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 1 Feb 2024 13:31:56 -0600 Subject: [PATCH 040/268] Rename `pretrain_gpt.py` -> `pretrain_gpt_alcf.py` in `ALCF/*.sh` --- ALCF/README.md | 5 ++++- ALCF/launch.sh | 3 ++- ALCF/submit.sh | 2 +- ALCF/train-gpt3.sh | 2 +- 4 files changed, 8 insertions(+), 4 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 89fb639da8..e8f4127876 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -57,7 +57,7 @@ strategies and various optimizations that are supported. # - other args: defined in ALCF/args.sh # --------------------------------------------- MODEL_SIZE_KEY="GPT25B" \ - SEQ_LEN=4096 \ + SEQ_LEN=4096 \ USE_FLASH_ATTN_V2=1 \ MICRO_BATCH=1 \ GAS=1 \ @@ -69,6 +69,7 @@ strategies and various optimizations that are supported. ## Helper Scripts +- [`pretrain_gpt_alcf.py`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/pretrain_gpt_alcf.py) - 📂 [`ALCF/`](https://github.com/argonne-lcf/Megatron-DeepSpeed/tree/main/ALCF) `├──` [`args.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/models.sh) `├──` [`launch.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/launch.sh) @@ -80,6 +81,8 @@ strategies and various optimizations that are supported.
+
pretrain_gpt_alcf.py +
Python module to be launched. Running `./ALCF/train-gpt3.sh` will automaticall build an `mpiexec` command and launch this module.
ALCF/train-gpt3.sh
Main entry point for training. This script will automatically source the rest of the required ALCF/*.sh scripts below
ALCF/model.sh
diff --git a/ALCF/launch.sh b/ALCF/launch.sh index 41a620a145..2dd834f568 100755 --- a/ALCF/launch.sh +++ b/ALCF/launch.sh @@ -39,7 +39,8 @@ MPI_WRAPPER="${SCRIPT_DIR}/mpi_wrapper" # sourceFile "${ALCF_DIR}/args.sh" -MAIN="${PARENT}/pretrain_${MODEL_TYPE}.py" +# MAIN="${PARENT}/pretrain_${MODEL_TYPE}.py" +MAIN="${PARENT}/pretrain_gpt_alcf.py" printJobInfo() { echo "Job started at: ${TSTAMP} on $(hostname)" diff --git a/ALCF/submit.sh b/ALCF/submit.sh index cc308b5be5..6842eb66b6 100755 --- a/ALCF/submit.sh +++ b/ALCF/submit.sh @@ -22,7 +22,7 @@ echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" #┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ #┃ Make sure we're not already running; if so, exit here ┃ #┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ -PIDS=$(ps aux | grep pretrain_gpt.py | grep -v grep | awk '{print $2}') +PIDS=$(ps aux | grep pretrain_gpt_alcf.py | grep -v grep | awk '{print $2}') if [ -n "${PIDS}" ]; then echo "Already running! Exiting!" exit 1 diff --git a/ALCF/train-gpt3.sh b/ALCF/train-gpt3.sh index bb054b0386..79e2661d16 100755 --- a/ALCF/train-gpt3.sh +++ b/ALCF/train-gpt3.sh @@ -31,7 +31,7 @@ echo "+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+" #┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ #┃ Make sure we're not already running; if so, exit here ┃ #┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ -PIDS=$(ps aux | egrep "$USER.+mpi.+pretrain_gpt.py" | grep -v grep | awk '{print $2}') +PIDS=$(ps aux | grep -E "$USER.+mpi.+pretrain_gpt_alcf.py" | grep -v grep | awk '{print $2}') if [ -n "${PIDS}" ]; then echo "Already running! Exiting!" exit 1 From 7c8029af74401d17b964e11c34644c443bb2aeed Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 1 Feb 2024 13:32:41 -0600 Subject: [PATCH 041/268] Update `set_params.sh` --- set_params.sh | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/set_params.sh b/set_params.sh index 40682a9fe3..8d6cd1ce91 100644 --- a/set_params.sh +++ b/set_params.sh @@ -21,10 +21,10 @@ export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP TP=${TP:-1} PP=${PP:-1} -export DATA_PARENT="/home/foremans/polaris/projects/saforem2/Megatron-DeepSpeed" -export DATA_TYPE="BookCorpusDataset_text_document" -# export DATA_PARENT="/lus/eagle/projects/datasets/Megatron-DeepSpeed/GenSLMSubSample200k" -# export DATA_TYPE="genslm_subsample_200k_sequence_document" +# export DATA_PARENT="/home/foremans/polaris/projects/saforem2/Megatron-DeepSpeed" +# export DATA_TYPE="BookCorpusDataset_text_document" +export DATA_PARENT="/lus/eagle/projects/datasets/Megatron-DeepSpeed/GenSLMSubSample200k" +export DATA_TYPE="genslm_subsample_200k_sequence_document" export DATA_DIR="${DATA_PARENT}/dataset" export DATA_PATH="${DATA_DIR}/${DATA_TYPE}" export VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" @@ -41,7 +41,7 @@ echo "!!!Please see logs at ${OUTPUT_DIR}" # Hostfile path hostfile_deepspeed=./hostfile_deepspeed hostfile_mpich=./hostfile_mpich -cat $PBS_NODEFILE > hostfile_mpich +cat $PBS_NODEFILE > hostfile_mpich cat $PBS_NODEFILE > hostfile_deepspeed ; sed -e 's/$/ slots=4/' -i hostfile_deepspeed ds_args=" " From 1152aad4ceafed167cddafc4df7fd2e2f7fc4aca Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 1 Feb 2024 13:40:07 -0600 Subject: [PATCH 042/268] Update `set_params.sh` --- set_params.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/set_params.sh b/set_params.sh index 8d6cd1ce91..b6bd36038d 100644 --- a/set_params.sh +++ b/set_params.sh @@ -68,7 +68,7 @@ fi NCCL=${NCCL:-nccl} run_cmd=" - deepspeed $launcher pretrain_gpt.py \ + deepspeed $launcher pretrain_gpt_alcf.py \ --tensor-model-parallel-size $TP \ --pipeline-model-parallel-size $PP \ --num-layers $NLAYERS \ From 91cf7b1b8746e564b072cbf975301d172c8a6291 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Fri, 2 Feb 2024 10:20:30 -0600 Subject: [PATCH 043/268] added pretrain_gpt_alcf.py --- llama.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/llama.sh b/llama.sh index 323a5f4730..b62fe794ef 100755 --- a/llama.sh +++ b/llama.sh @@ -1,4 +1,4 @@ -#!/bin/bashOA +#!/bin/bash #PBS -l walltime=0:30:00 #PBS -A datascience #PBS -q debug-scaling From e1f9e300531cf747454f6a26af6539818fd73f12 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Fri, 2 Feb 2024 10:20:46 -0600 Subject: [PATCH 044/268] added pretrain_gpt_alcf.py --- pretrain_gpt_alcf.py | 593 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 593 insertions(+) create mode 100644 pretrain_gpt_alcf.py diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py new file mode 100644 index 0000000000..0c82e0ff0e --- /dev/null +++ b/pretrain_gpt_alcf.py @@ -0,0 +1,593 @@ +# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved. + +"""Pretrain GPT""" + +import os +import torch +import math +# import logging + +from functools import partial +from megatron import get_args +from megatron import print_rank_0 +from rich import print +from megatron import get_timers +from megatron import get_tokenizer +from megatron.core import mpu, tensor_parallel +from megatron.core.enums import ModelType +from megatron.data.gpt_dataset import build_train_valid_test_datasets +from megatron.model import GPTModel, GPTModelPipe +from megatron.training import pretrain +from megatron.utils import get_ltor_masks_and_position_ids +from megatron.utils import average_losses_across_data_parallel_group, update_rotary_pos_emb +from megatron.arguments import core_transformer_config_from_args +from megatron.utils import ( + report_memory, + throughput_calculator, + checkpoint_throughput_calculator +) +from pathlib import Path + +import deepspeed +from deepspeed.runtime.utils import see_memory_usage +from deepspeed.accelerator.real_accelerator import get_accelerator +import subprocess +import wandb + +import time +from torch import nn +import torch.nn.functional as F + +# from ezpz import get_logger +from ezpz.dist import setup_torch, get_world_size, setup_wandb + +RANK = setup_torch( + backend='deepspeed', + port='5432', +) +WORLD_SIZE = get_world_size() +LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" + +WANDB_MODE = os.environ.get('WANDB_MODE', None) +DISABLE_WANDB = WANDB_MODE is not None and str(WANDB_MODE).lower() == 'disabled' + +if RANK == 0 and not DISABLE_WANDB: + project_name = ( + os.environ.get( + 'WB_PROJECT', + os.environ.get( + 'WANDB_PROJECT', + 'GenSLM-Megatron-DS' + ), + ) + ) + print('--------------------------------------------------') + print(f"Setting up W&B from: {RANK} with {project_name}") + print('--------------------------------------------------') + setup_wandb(project_name=project_name) + + +# os.environ[''] +# wblogger = logging.getLogger("wandb") +# wblogger.setLevel(logging.DEBUG) + +# log = get_logger(__name__, level=LEVEL) +# +# log.critical(f"Hello from rank: {RANK} / {WORLD_SIZE} !") + +import socket +from typing import Optional +# log.critical(f"Setting up W&B from rank: {RANK} with {wb_project_name}") + + +# def setup_wandb(project_name: Optional[str] = None): +# print(f"Setting up W&B from: {RANK}") +# project_name = ( +# os.environ.get('WB_PROJECT', 'GenSLM-Megatron-DS') +# if project_name is None else project_name +# ) +# print(f"Setting up wandb from rank: {RANK}") +# print(f"Using: WB PROJECT: {project_name}") +# # if get_rank() == 0: +# # tensorboard_dir = args.tensorboard_dir +# tensorboard_dir = None +# # if config is None: +# tensorboard_dir = os.environ.get('TENSORBOARD_DIR', None) +# # else: +# # tensorboard_dir = ( +# # config.get( +# # 'tensorboard_dir', +# # None, # os.getcwd() +# # ) +# # ) +# if tensorboard_dir is not None: +# print(f'Patching tensorboard from {tensorboard_dir}') +# wandb.tensorboard.patch(root_logdir=tensorboard_dir) +# # wbrun_id = wandb.util.generate_id() +# current_time = time.time() +# # local_time = time.localtime(current_time) +# # if wandb.run is None: +# wandb.init( +# resume='allow', +# sync_tensorboard=(tensorboard_dir is not None), # True, +# project=(project_name if project_name is not None else None), +# # dir=(tensorboard_dir if tensorboard_dir is not None else None), +# ) +# assert wandb.run is not None +# print(f"W&B RUN: [{wandb.run.name}]({wandb.run.url})") +# wandb.run.config.update({'current_time': current_time}) +# model_size = os.environ.get('MODEL_SIZE', None) +# wandb.run.config.update({'world_size': get_world_size()}) +# # if config is not None: +# # wandb.run.config.update(config) +# env = { +# k: v for k, v in dict(os.environ).items() +# if not k.startswith('_ModuleTable') +# } +# _ = env.pop('LS_COLORS', None) +# _ = env.pop('PS1', None) +# wandb.run.config.update({'env': env}) +# hostname = socket.gethostbyaddr(socket.gethostname())[0] +# if hostname.startswith('theta'): +# wandb.run.config.update({'machine': 'ThetaGPU'}) +# elif hostname.startswith('x3'): +# wandb.run.config.update({'machine': 'Polaris'}) +# elif hostname.startswith('x1'): +# wandb.run.config.update({'machine': 'Sunspot'}) +# elif hostname.startswith('nid'): +# wandb.run.config.update({'machine': 'Perlmutter'}) +# elif hostname.startswith('login'): +# wandb.run.config.update({'machine': 'NERSC'}) +# else: +# wandb.run.config.update({'machine': hostname}) +# if model_size is not None: +# wandb.run.config.update({'MODEL_SIZE': model_size}) + +def model_provider(pre_process=True, post_process=True): + """Build the model.""" + print_rank_0('building GPT model ...') + see_memory_usage("Before Building Model", force=True) + args = get_args() + config = core_transformer_config_from_args(args) + # args = get_args() + # timers = get_timers() + if wandb.run is not None: + print(f"Updating WandB run: [{wandb.run.name}]({wandb.run.url})") + wandb.run.config.update({"args": vars(args)}) + if RANK == 0: + git_ds_info() + + with deepspeed.zero.Init(sequence_data_parallel_group=mpu.get_sequence_data_parallel_group(), + remote_device=None if args.remote_device == 'none' else args.remote_device, + config_dict_or_path=args.deepspeed_config_dict, + enabled=args.zero_stage == 3, + mpu=mpu): + if args.deepspeed and not args.no_pipeline_parallel: + model = GPTModelPipe( + config=config, + num_tokentypes=0, + parallel_output=True + ) + # This is a hack to give us a reference to get_batch_pipe from within training.py + # We need to call model.set_batch_fn after deepspeed.initialize + model._megatron_batch_fn = get_batch_pipe + + # Predompute the attention mask and store it in args. This avoids having to + # pipeline it as an activation during training. The mask is constant, and thus + # we can reuse it. + attention_mask = torch.tril(torch.ones( + (1, args.seq_length, args.seq_length), device=get_accelerator().current_device_name())).view( + 1, 1, args.seq_length, args.seq_length) + + # Convert attention mask to binary: + attention_mask = (attention_mask < 0.5) + if args.fp16: + attention_mask = attention_mask.half() + elif args.bf16: + attention_mask = attention_mask.bfloat16() + + # Attention mask must be bool. + args.attn_mask = attention_mask.to(torch.bool) + + # For prertaining, since sequence length is fixed, cache rotary embedding in args, to avoid communicating around + if args.use_rotary_position_embeddings: + update_rotary_pos_emb(args.seq_length) + + else: + model = GPTModel( + config=config, + num_tokentypes=0, + parallel_output=True, + pre_process=pre_process, + post_process=post_process + ) + num_params = sum(p.numel() for p in model.parameters() if p.requires_grad) + # print_rank_0('\n ------------------------ ') + # print_rank_0(f'num of parameters {num_params}') + # print_rank_0('------------------------\n ') + print_rank_0(80 * '-') + print_rank_0(f"Number of parameters in model: {num_params}") + print_rank_0(80 * '-') + see_memory_usage("After Building Model", force=True) + if wandb.run is not None: + wandb.run.watch( + model, + log='all', + log_graph=True, + ) + wandb.run.config.update({'num_params': num_params}) + return model + +def get_batch(data_iterator): + """Generate a batch""" + args = get_args() + tokenizer = get_tokenizer() + + # Items and their type. + keys = ['text'] + datatype = torch.int64 + + # Broadcast data. + if data_iterator is not None: + data = next(data_iterator) + else: + data = None + data_b = tensor_parallel.broadcast_data(keys, data, datatype) + + # Unpack. + tokens_ = data_b['text'].long() + labels = tokens_[:, 1:].contiguous() + tokens = tokens_[:, :-1].contiguous() + + # Get the masks and postition ids. + skip_mask = hasattr(args, 'use_flash_attn') or hasattr(args, 'flash_attn_triton') + # skip_mask = args.use_flash_attn or args.use_flash_attn_triton + attention_mask, loss_mask, position_ids = get_ltor_masks_and_position_ids( + tokens, + tokenizer.eod, + args.reset_position_ids, + args.reset_attention_mask, + args.eod_mask_loss, + skip_mask) + + # For DS's sequence parallel + seq_parallel_world_size = mpu.get_sequence_parallel_world_size() + seq_parallel_world_rank = mpu.get_sequence_parallel_rank() + + # For Megatron's sequence parallel + if args.sequence_parallel: + seq_parallel_world_size = mpu.get_tensor_model_parallel_world_size() + seq_parallel_world_rank = mpu.get_tensor_model_parallel_rank() + seq_length = tokens.size(1) + + assert seq_length % seq_parallel_world_size == 0 + sub_seq_length = seq_length // seq_parallel_world_size + sub_seq_start = seq_parallel_world_rank * sub_seq_length + sub_seq_end = (seq_parallel_world_rank + 1) * sub_seq_length + + tokens = tokens[:, sub_seq_start:sub_seq_end] + position_ids = position_ids[:, sub_seq_start:sub_seq_end] + # For DS's sequence parallel + if mpu.get_sequence_parallel_world_size() > 1: + labels = labels[:, sub_seq_start:sub_seq_end] + + return tokens, labels, loss_mask, attention_mask, position_ids + + +def data_post_process(data, data_sampler_state_dict): + args = get_args() + if args.data_efficiency_curriculum_learning: + if 'seqlen_truncate' in data_sampler_state_dict['current_difficulties']: + args.data_efficiency_curriculum_learning_seqlen_type = 'seqlen_truncate' + current_seqlen = data_sampler_state_dict['current_difficulties']['seqlen_truncate'] + if current_seqlen < args.seq_length: + data['text'] = data['text'][:, :(current_seqlen+1)].contiguous() + elif 'seqlen_reshape' in data_sampler_state_dict['current_difficulties']: + args.data_efficiency_curriculum_learning_seqlen_type = 'seqlen_reshape' + current_seqlen = data_sampler_state_dict['current_difficulties']['seqlen_reshape'] + if current_seqlen < args.seq_length: + orig_num_token = torch.numel(data['text']) + reshape_len = (data['text'].size()[1] // (current_seqlen+1)) * (current_seqlen+1) + data['text'] = torch.cat((data['text'][:, :reshape_len].contiguous().view(-1, current_seqlen+1), + data['text'][:, -(current_seqlen+1):]), 0).contiguous() + num_row = math.ceil(orig_num_token / (current_seqlen+1)) + num_row = min(num_row, data['text'].size()[0]) + if num_row > 1 and num_row % 2 != 0: + num_row -= 1 + data['text'] = data['text'][:num_row, :].contiguous() + else: + args.data_efficiency_curriculum_learning_seqlen_type = None + return data + + +def get_batch_pipe(data): + """Modification of `get_batch` to work on `next(data_iterator)` instead of `data_iterator`""" + args = get_args() + tokenizer = get_tokenizer() + + # Items and their type. + keys = ['text'] + datatype = torch.int64 + + # Broadcast data. + data_b = tensor_parallel.broadcast_data(keys, data, datatype) + + # Unpack. + tokens_ = data_b['text'].long() + labels = tokens_[:, 1:].contiguous() + tokens = tokens_[:, :-1].contiguous() + + # Get the masks and postition ids. + attention_mask, loss_mask, position_ids = get_ltor_masks_and_position_ids( + tokens, + tokenizer.eod, + args.reset_position_ids, + args.reset_attention_mask, + args.eod_mask_loss) + if args.curriculum_learning_legacy and args.curriculum_seqlen < tokens.size()[1]: + # seqlen-based curriculum learning + # tokens, position_ids, labels, loss_mask have size [batch size, seqlen] + tokens = tokens[:, :args.curriculum_seqlen].contiguous() + position_ids = position_ids[:, :args.curriculum_seqlen].contiguous() + if labels is not None: + labels = labels[:, :args.curriculum_seqlen].contiguous() + loss_mask = loss_mask[:, :args.curriculum_seqlen].contiguous() + + return (tokens, position_ids, attention_mask), (labels, loss_mask) + + +def loss_func(loss_mask, moe_loss, mos_loss, output_tensor): + args = get_args() + losses = output_tensor.float() + loss_mask = loss_mask.view(-1).float() + loss = torch.sum(losses.view(-1) * loss_mask) / loss_mask.sum() + + # Reduce loss for logging. + averaged_loss = average_losses_across_data_parallel_group([loss]) + if args.mos or args.kd: + # assert max(args.num_experts) >= 1 + loss = loss + moe_loss + mos_loss + if args.mos: + return loss, {'total loss': loss, 'lm loss': averaged_loss[0], 'moe loss': moe_loss, 'mos loss': mos_loss} + elif args.kd: + return loss, {'total loss': loss, 'lm loss': averaged_loss[0], 'moe loss': moe_loss, 'kd loss': mos_loss} + print_rank_0('>>> total loss: {}, lm loss {}, kd loss {}'.format(loss, averaged_loss[0], mos_loss)) + else: + if max(args.num_experts) <= 1: + return loss, {'lm loss': averaged_loss[0]} + else: + loss = loss + moe_loss + return loss, {'lm loss': averaged_loss[0], 'moe loss': moe_loss} + +def calculate_mos_loss(args, stu_output, teacher_model, tokens, position_ids, attention_mask): + mos_loss = 0 + alpha = args.kd_alpha_ce + beta = args.kd_beta_ce + kd_temp = args.kd_temp + + if teacher_model: + with torch.no_grad(): + if args.curriculum_learning_legacy and args.curriculum_seqlen < args.seq_length: + assert args.curriculum_seqlen is not None + curriculum_seqlen = args.curriculum_seqlen + tokens = tokens[:, :curriculum_seqlen].contiguous() + position_ids = position_ids[:, :curriculum_seqlen].contiguous() + attention_mask = attention_mask[:, :, :curriculum_seqlen, :curriculum_seqlen].contiguous() + # No need to truncate labels as we do not need it for the teacher logits + tea_output, tea_other_losses = teacher_model(tokens, position_ids, attention_mask) + assert stu_output.size() == tea_output.size(), 'teacher and student output should match in size. Student: {}, Teacher: {}, CL seq length {}'.format(stu_output.size(), tea_output.size(), args.curriculum_seqlen) + + student_logits = F.log_softmax(stu_output / kd_temp, dim=2) + tea_logits = F.softmax(tea_output / kd_temp, dim=2) # The target logits is expected to be probabilities. If we use log_softmax, then we need to set target_log to true when initializing the KLDivLoss. + + mos_loss = kd_temp * kd_temp * nn.KLDivLoss(reduction='batchmean')(student_logits, tea_logits) + + mos_loss = mos_loss.div(args.seq_length) * beta + return mos_loss + + +def forward_step(data_iterator, model): + """Forward step.""" + args = get_args() + timers = get_timers() + + # Get the batch. + timers('batch-generator', log_level=2).start() + tokens, labels, loss_mask, attention_mask, position_ids = get_batch( + data_iterator) + timers('batch-generator').stop() + + if args.data_efficiency_curriculum_learning: + args.curriculum_seqlen = tokens.size()[1] + if hasattr(args, 'data_efficiency_curriculum_learning_seqlen_type') and \ + args.data_efficiency_curriculum_learning_seqlen_type == 'seqlen_reshape': + args.data_efficiency_curriculum_learning_numel = torch.numel(tokens) + + if args.mos or args.kd: + # The forward func can return either the loss or the logits, depending on whether passing in the labels or not. + stu_output, other_losses = model(tokens, position_ids, attention_mask) + if args.curriculum_learning_legacy and args.curriculum_seqlen < args.seq_length: + assert args.curriculum_seqlen is not None + labels = labels[:, :args.curriculum_seqlen].contiguous() + output_tensor = tensor_parallel.vocab_parallel_cross_entropy(stu_output.contiguous().float(), labels) + else: + output_tensor, other_losses = model(tokens, position_ids, attention_mask, + labels=labels) + if args.curriculum_learning_legacy and args.curriculum_seqlen < args.seq_length: + loss_mask = loss_mask[:, :args.curriculum_seqlen].contiguous() + + moe_losses = [] + for moe_loss in other_losses: + if moe_loss is not None: + moe_losses.append(moe_loss) + moe_loss = sum(moe_losses) * args.moe_loss_coeff + + mos_loss = 0 + if args.mos or args.kd: + assert model.training + if args.teacher_forward and args.teacher_model is not None: + mos_loss = calculate_mos_loss(args, stu_output, + args.teacher_model[0], tokens, position_ids, attention_mask) + + # Output_tensor stores the standard loss, loos_func calculates the total loss. + return output_tensor, partial(loss_func, loss_mask, moe_loss, mos_loss) + + +def train_valid_test_datasets_provider(train_val_test_num_samples): + """Build train, valid, and test datasets.""" + args = get_args() + + print_rank_0('> building train, validation, and test datasets ' + 'for GPT ...') + files = [] + if args.data_file_list is not None: + with open(args.data_file_list, 'r') as flist: + for f in flist.readlines(): + w, fname = f.split() + files.append(float(w)) + files.append(fname) + elif len(args.data_path)==1 and os.path.isdir(args.data_path[0]): + path=args.data_path[0] + "/" + for f in os.listdir(path): + if (os.path.isfile(path + f) and f.find(".bin")!=-1): + files.append(1) + files.append(path + f.split(".bin")[0]) + else: + files = args.data_path + print_rank_0(f"file list {files}") + train_ds, valid_ds, test_ds = build_train_valid_test_datasets( + data_prefix=files, + data_impl=args.data_impl, + splits_string=args.split, + train_valid_test_num_samples=train_val_test_num_samples, + seq_length=args.seq_length, + seed=args.seed, + skip_warmup=(not args.mmap_warmup), + train_data_prefix=args.train_data_path, + valid_data_prefix=args.valid_data_path, + test_data_prefix=args.test_data_path, + data_cache_path=args.data_cache_path) + print_rank_0("> finished creating GPT datasets ...") + + return train_ds, valid_ds, test_ds + + +def command_exists(cmd): + result = subprocess.Popen(f'type {cmd}', stdout=subprocess.PIPE, shell=True) + return result.wait() == 0 + + +def git_ds_info(): + from deepspeed.env_report import main as ds_report + ds_report() + + # Write out version/git info + git_hash_cmd = "git rev-parse --short HEAD" + git_branch_cmd = "git rev-parse --abbrev-ref HEAD" + if command_exists('git'): + try: + result = subprocess.check_output(git_hash_cmd, shell=True) + git_hash = result.decode('utf-8').strip() + result = subprocess.check_output(git_branch_cmd, shell=True) + git_branch = result.decode('utf-8').strip() + except subprocess.CalledProcessError: + git_hash = "unknown" + git_branch = "unknown" + else: + git_hash = "unknown" + git_branch = "unknown" + print(f'**** Git info for Megatron: git_hash={git_hash} git_branch={git_branch} ****') + + +def main(): + # if RANK == 0: + # setup_wandb() + from torch.profiler import profile, record_function, ProfilerActivity + with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: + model = pretrain( + train_valid_test_datasets_provider, + model_provider, + ModelType.encoder_or_decoder, + forward_step, + args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + data_post_process=data_post_process + ) + args = get_args() + prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") + + # # from megatron.training import get_model + # if wandb.run is not None: + # args = get_args() + # timers = get_timers() + # # model = get_model(model_provider, ModelType.encoder_or_decoder) + # elapsed_time = timers('interval-time').elapsed(barrier=True) + # total_iterations = os.environ.get( + # "TOTAL_ITERATIONS", + # (args.train_iters + args.eval_iters) + # ) + # seq_len = args.seq_length + # elapsed_time_per_iteration = elapsed_time / total_iterations + # if model is not None: + # samples_per_sec, tflops, approx_params_in_billions = throughput_calculator( + # model, + # args, + # elapsed_time, + # total_iterations, + # ) + # # Compute throughput. + # samples_per_sec_per_replica = samples_per_sec / args.data_parallel_size + # tokens_per_sec = samples_per_sec * seq_len + # tokens_per_sec_per_replica = tokens_per_sec / args.data_parallel_size + # sample_consumption_rate = args.consumed_train_samples / elapsed_time + # token_consumption_rate = args.consumed_train_tokens / elapsed_time + # # Tensorboard values. + # tdata = { + # # 'iteration': iteration, + # 'consumed_train_samples': args.consumed_train_samples, + # 'consumed_train_tokens': args.consumed_train_tokens, + # # 'learning_rate': learning_rate, + # # 'batch_size': batch_size, + # # 'loss_scale': loss_scale, + # # 'grad_norm': grad_norm, + # } + # # for key in loss_dict: + # # tdata[f'lm-loss/{key}'] = loss_dict[key] + # + # tdata = {f'train/{k}': v for k, v in tdata.items()} + # # if wbrun is not None and wbrun is wandb.run: + # if wandb.run is not None: + # wandb.run.log(tdata, commit=False) + # tput = { + # 'throughput/iteration-time': elapsed_time_per_iteration, # 1000 ms / s + # 'throughput/samples_per_sec': samples_per_sec, + # 'throughput/samples_per_sec_per_replica': samples_per_sec_per_replica, + # 'throughput/tokens_per_sec': tokens_per_sec, + # 'throughput/tokens_per_sec_per_replica': tokens_per_sec_per_replica, + # 'throughput/tflops': tflops, + # 'throughput/approx_params_in_billions': approx_params_in_billions, + # 'throughput/sample_consumption_rate': sample_consumption_rate, + # 'throughput/token_consumption_rate': token_consumption_rate, + # 'throughput/elapsed_ms_per_iteration': elapsed_time_per_iteration, + # } + # wandb.run.log(tput) + return model + + + +if __name__ == "__main__": + # git_ds_info() + # pretrain(train_valid_test_datasets_provider, + # model_provider, + # ModelType.encoder_or_decoder, + # forward_step, + # args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + # data_post_process=data_post_process) + import sys + import deepspeed.comm as dist + model = main() + dist.log_summary() + if wandb.run is not None: + print(f"wandb.run.name: {wandb.run.name}") + print(f"wandb.run.url: {wandb.run.url}") + wandb.finish() + sys.exit() From c861a0b67593460a88eadd2f5d8184d287daa718 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Fri, 2 Feb 2024 10:40:21 -0600 Subject: [PATCH 045/268] llama alcf --- llama.sh => llama_alcf.sh | 0 pretrain_gpt.py | 207 +------------------------------------- 2 files changed, 2 insertions(+), 205 deletions(-) rename llama.sh => llama_alcf.sh (100%) diff --git a/llama.sh b/llama_alcf.sh similarity index 100% rename from llama.sh rename to llama_alcf.sh diff --git a/pretrain_gpt.py b/pretrain_gpt.py index 6922fb80c9..785a129156 100644 --- a/pretrain_gpt.py +++ b/pretrain_gpt.py @@ -27,113 +27,6 @@ from torch import nn import torch.nn.functional as F -<<<<<<< HEAD -# from ezpz import get_logger -from ezpz.dist import setup_torch, get_world_size, setup_wandb - -RANK = setup_torch( - backend='deepspeed', - port='5432', -) -WORLD_SIZE = get_world_size() -LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" - -WANDB_MODE = os.environ.get('WANDB_MODE', None) -DISABLE_WANDB = WANDB_MODE is not None and str(WANDB_MODE).lower() == 'disabled' - -if RANK == 0 and not DISABLE_WANDB: - project_name = ( - os.environ.get( - 'WB_PROJECT', - os.environ.get( - 'WANDB_PROJECT', - 'GenSLM-Megatron-DS' - ), - ) - ) - print('--------------------------------------------------') - print(f"Setting up W&B from: {RANK} with {project_name}") - print('--------------------------------------------------') - setup_wandb(project_name=project_name) - - -# os.environ[''] -# wblogger = logging.getLogger("wandb") -# wblogger.setLevel(logging.DEBUG) - -# log = get_logger(__name__, level=LEVEL) -# -# log.critical(f"Hello from rank: {RANK} / {WORLD_SIZE} !") - -import socket -from typing import Optional -# log.critical(f"Setting up W&B from rank: {RANK} with {wb_project_name}") - - -# def setup_wandb(project_name: Optional[str] = None): -# print(f"Setting up W&B from: {RANK}") -# project_name = ( -# os.environ.get('WB_PROJECT', 'GenSLM-Megatron-DS') -# if project_name is None else project_name -# ) -# print(f"Setting up wandb from rank: {RANK}") -# print(f"Using: WB PROJECT: {project_name}") -# # if get_rank() == 0: -# # tensorboard_dir = args.tensorboard_dir -# tensorboard_dir = None -# # if config is None: -# tensorboard_dir = os.environ.get('TENSORBOARD_DIR', None) -# # else: -# # tensorboard_dir = ( -# # config.get( -# # 'tensorboard_dir', -# # None, # os.getcwd() -# # ) -# # ) -# if tensorboard_dir is not None: -# print(f'Patching tensorboard from {tensorboard_dir}') -# wandb.tensorboard.patch(root_logdir=tensorboard_dir) -# # wbrun_id = wandb.util.generate_id() -# current_time = time.time() -# # local_time = time.localtime(current_time) -# # if wandb.run is None: -# wandb.init( -# resume='allow', -# sync_tensorboard=(tensorboard_dir is not None), # True, -# project=(project_name if project_name is not None else None), -# # dir=(tensorboard_dir if tensorboard_dir is not None else None), -# ) -# assert wandb.run is not None -# print(f"W&B RUN: [{wandb.run.name}]({wandb.run.url})") -# wandb.run.config.update({'current_time': current_time}) -# model_size = os.environ.get('MODEL_SIZE', None) -# wandb.run.config.update({'world_size': get_world_size()}) -# # if config is not None: -# # wandb.run.config.update(config) -# env = { -# k: v for k, v in dict(os.environ).items() -# if not k.startswith('_ModuleTable') -# } -# _ = env.pop('LS_COLORS', None) -# _ = env.pop('PS1', None) -# wandb.run.config.update({'env': env}) -# hostname = socket.gethostbyaddr(socket.gethostname())[0] -# if hostname.startswith('theta'): -# wandb.run.config.update({'machine': 'ThetaGPU'}) -# elif hostname.startswith('x3'): -# wandb.run.config.update({'machine': 'Polaris'}) -# elif hostname.startswith('x1'): -# wandb.run.config.update({'machine': 'Sunspot'}) -# elif hostname.startswith('nid'): -# wandb.run.config.update({'machine': 'Perlmutter'}) -# elif hostname.startswith('login'): -# wandb.run.config.update({'machine': 'NERSC'}) -# else: -# wandb.run.config.update({'machine': hostname}) -# if model_size is not None: -# wandb.run.config.update({'MODEL_SIZE': model_size}) -======= ->>>>>>> 9c3a73dfebb812e7a494eaaa0a0dc1138dd0f922 def model_provider(pre_process=True, post_process=True): """Build the model.""" @@ -196,6 +89,7 @@ def model_provider(pre_process=True, post_process=True): see_memory_usage(f"After Building Model", force=True) return model + def get_batch(data_iterator): """Generate a batch""" args = get_args() @@ -250,7 +144,6 @@ def get_batch(data_iterator): return tokens, labels, loss_mask, attention_mask, position_ids - def data_post_process(data, data_sampler_state_dict): args = get_args() if args.data_efficiency_curriculum_learning: @@ -276,7 +169,6 @@ def data_post_process(data, data_sampler_state_dict): args.data_efficiency_curriculum_learning_seqlen_type = None return data - def get_batch_pipe(data): """Modification of `get_batch` to work on `next(data_iterator)` instead of `data_iterator`""" args = get_args() @@ -362,7 +254,6 @@ def calculate_mos_loss(args, stu_output, teacher_model, tokens, position_ids, at mos_loss = mos_loss.div(args.seq_length) * beta return mos_loss - def forward_step(data_iterator, model): """Forward step.""" args = get_args() @@ -416,24 +307,8 @@ def train_valid_test_datasets_provider(train_val_test_num_samples): print_rank_0('> building train, validation, and test datasets ' 'for GPT ...') - files = [] - if args.data_file_list is not None: - with open(args.data_file_list, 'r') as flist: - for f in flist.readlines(): - w, fname = f.split() - files.append(float(w)) - files.append(fname) - elif len(args.data_path)==1 and os.path.isdir(args.data_path[0]): - path=args.data_path[0] + "/" - for f in os.listdir(path): - if (os.path.isfile(path + f) and f.find(".bin")!=-1): - files.append(1) - files.append(path + f.split(".bin")[0]) - else: - files = args.data_path - print_rank_0(f"file list {files}") train_ds, valid_ds, test_ds = build_train_valid_test_datasets( - data_prefix=files, + data_prefix=args.data_path, data_impl=args.data_impl, splits_string=args.split, train_valid_test_num_samples=train_val_test_num_samples, @@ -476,84 +351,6 @@ def git_ds_info(): print(f'**** Git info for Megatron: git_hash={git_hash} git_branch={git_branch} ****') -<<<<<<< HEAD -def main(): - # if RANK == 0: - # setup_wandb() - from torch.profiler import profile, record_function, ProfilerActivity - with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: - model = pretrain( - train_valid_test_datasets_provider, - model_provider, - ModelType.encoder_or_decoder, - forward_step, - args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, - data_post_process=data_post_process - ) - args = get_args() - prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") - - # # from megatron.training import get_model - # if wandb.run is not None: - # args = get_args() - # timers = get_timers() - # # model = get_model(model_provider, ModelType.encoder_or_decoder) - # elapsed_time = timers('interval-time').elapsed(barrier=True) - # total_iterations = os.environ.get( - # "TOTAL_ITERATIONS", - # (args.train_iters + args.eval_iters) - # ) - # seq_len = args.seq_length - # elapsed_time_per_iteration = elapsed_time / total_iterations - # if model is not None: - # samples_per_sec, tflops, approx_params_in_billions = throughput_calculator( - # model, - # args, - # elapsed_time, - # total_iterations, - # ) - # # Compute throughput. - # samples_per_sec_per_replica = samples_per_sec / args.data_parallel_size - # tokens_per_sec = samples_per_sec * seq_len - # tokens_per_sec_per_replica = tokens_per_sec / args.data_parallel_size - # sample_consumption_rate = args.consumed_train_samples / elapsed_time - # token_consumption_rate = args.consumed_train_tokens / elapsed_time - # # Tensorboard values. - # tdata = { - # # 'iteration': iteration, - # 'consumed_train_samples': args.consumed_train_samples, - # 'consumed_train_tokens': args.consumed_train_tokens, - # # 'learning_rate': learning_rate, - # # 'batch_size': batch_size, - # # 'loss_scale': loss_scale, - # # 'grad_norm': grad_norm, - # } - # # for key in loss_dict: - # # tdata[f'lm-loss/{key}'] = loss_dict[key] - # - # tdata = {f'train/{k}': v for k, v in tdata.items()} - # # if wbrun is not None and wbrun is wandb.run: - # if wandb.run is not None: - # wandb.run.log(tdata, commit=False) - # tput = { - # 'throughput/iteration-time': elapsed_time_per_iteration, # 1000 ms / s - # 'throughput/samples_per_sec': samples_per_sec, - # 'throughput/samples_per_sec_per_replica': samples_per_sec_per_replica, - # 'throughput/tokens_per_sec': tokens_per_sec, - # 'throughput/tokens_per_sec_per_replica': tokens_per_sec_per_replica, - # 'throughput/tflops': tflops, - # 'throughput/approx_params_in_billions': approx_params_in_billions, - # 'throughput/sample_consumption_rate': sample_consumption_rate, - # 'throughput/token_consumption_rate': token_consumption_rate, - # 'throughput/elapsed_ms_per_iteration': elapsed_time_per_iteration, - # } - # wandb.run.log(tput) - return model - - - -======= ->>>>>>> 9c3a73dfebb812e7a494eaaa0a0dc1138dd0f922 if __name__ == "__main__": git_ds_info() pretrain(train_valid_test_datasets_provider, From bb2bdc6c294165f8cc3cfc113043a0c1c56b5fbd Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Mon, 5 Feb 2024 11:12:18 -0600 Subject: [PATCH 046/268] update submission script --- llama_alcf.sh | 19 ++++++++++++++++--- 1 file changed, 16 insertions(+), 3 deletions(-) diff --git a/llama_alcf.sh b/llama_alcf.sh index b62fe794ef..17e4afd713 100755 --- a/llama_alcf.sh +++ b/llama_alcf.sh @@ -15,10 +15,22 @@ export TP=1 export PP=1 export MBS=1 export BS=$((MBS*PBS_JOBSIZE*PPN/PP/TP)) +export SP=$((PBS_JOBSIZE*PPN/PP/TP)) #export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/" + +export export DATE_TAG=$(date +"%Y-%m-%d-%H-%M-%S") export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/wiki-en-simple/" export DATA_FILE_LIST="/eagle/datasets//dolma//data_file_list_small.txt" echo "BS: $BS\n PP:$PP \n TP: $TP, PBS_JOBSIZE: $PBS_JOBSIZE" + +HIDDEN_SIZE=4096 +NUM_LAYERS=32 +SEQ_LENGTH=2048 +EMBEDDINGS=2048 +TRAIN_ITERS=10 +ZERO_STAGE=2 +MODEL=LLAMA_7B +OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --hostfile $PBS_NODEFILE python3 ./pretrain_gpt.py \ --tensor-model-parallel-size ${TP} \ --pipeline-model-parallel-size ${PP} \ @@ -31,8 +43,8 @@ MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --seq-length 2048 \ --max-position-embeddings 2048 \ --train-iters 10 \ - --save ${MD}/checkpoints/LLAMA_7B_LLAMA_7B_z2_seqlen_mp1_pp1_sp24_nl32_hs4096_gb${BS}_mb1 \ - --load ${MD}/checkpoints/LLAMA_7B_LLAMA_7B_z2_seqlen_mp1_pp1_sp24_nl32_hs4096_gb${BS}_mb1 \ + --save ${MD}/checkpoints/${OUTPUT_PREFIX} \ + --load ${MD}/checkpoints/${OUTPUT_PREFIX} \ --data-impl mmap \ --tokenizer-type Llama2Tokenizer \ --split 949,50,1 \ @@ -57,7 +69,8 @@ MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --use-rotary-position-embeddings \ --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ --untie-embeddings-and-output-weights \ - --swiglu --normalization layernorm --disable-bias-linear --num-key-value-heads 4 --tensorboard-dir ${MD}/outputs/LLAMA_7B_LLAMA_7B_z3_seqlen_mp1_pp1_sp24_nl32_hs4096_gb24_mb1/tensorboard --log-timers-to-tensorboard --tensorboard-log-interval 1 \ + --swiglu --normalization layernorm --disable-bias-linear --num-key-value-heads 4 \ + --tensorboard-dir ${MD}/outputs/${OUTPUT_PREFIX}/tensorboard --log-timers-to-tensorboard --tensorboard-log-interval 1 \ --data-file-list ${DATA_FILE_LIST} \ --data-path ${DATA_PATH} \ --vocab-file ${MD}/dataset/gpt2-vocab.json --merge-file ${MD}/dataset/gpt2-merges.txt \ From 5dd69bf8ed169525aaf034b77167acd7e19fe99d Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Mon, 5 Feb 2024 13:11:50 -0600 Subject: [PATCH 047/268] fixed zero_stage input in llama_alcf.sh --- llama_alcf.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/llama_alcf.sh b/llama_alcf.sh index 17e4afd713..a102c492fb 100755 --- a/llama_alcf.sh +++ b/llama_alcf.sh @@ -31,7 +31,7 @@ TRAIN_ITERS=10 ZERO_STAGE=2 MODEL=LLAMA_7B OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} -MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --hostfile $PBS_NODEFILE python3 ./pretrain_gpt.py \ +MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --hostfile $PBS_NODEFILE python3 ./pretrain_gpt_alcf.py \ --tensor-model-parallel-size ${TP} \ --pipeline-model-parallel-size ${PP} \ --num-layers 32 \ @@ -74,4 +74,4 @@ MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --data-file-list ${DATA_FILE_LIST} \ --data-path ${DATA_PATH} \ --vocab-file ${MD}/dataset/gpt2-vocab.json --merge-file ${MD}/dataset/gpt2-merges.txt \ - --zero-stage=2 --deepspeed_config=${MD}/ds_config-gpt.json --deepspeed + --zero-stage=${ZERO_STAGE} --deepspeed_config=${MD}/ds_config-gpt.json --deepspeed From 82555c8ed745ba8f92c4fa1515bd34ccdd743266 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 5 Feb 2024 16:45:58 -0600 Subject: [PATCH 048/268] Update `set_params.sh` --- set_params.sh | 54 ++++++++++++++++++++++++++++++++++++++++----------- 1 file changed, 43 insertions(+), 11 deletions(-) diff --git a/set_params.sh b/set_params.sh index b6bd36038d..696c0eb4aa 100644 --- a/set_params.sh +++ b/set_params.sh @@ -13,6 +13,7 @@ export TP=${TP:-1} export PP=${PP:-1} export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) +export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} # bash $LLM_DK_DIR/intel-extension-for-deepspeed/examples/gpt.sh $@ @@ -21,20 +22,25 @@ export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP TP=${TP:-1} PP=${PP:-1} -# export DATA_PARENT="/home/foremans/polaris/projects/saforem2/Megatron-DeepSpeed" +export DATA_PARENT="/home/foremans/polaris/projects/saforem2/Megatron-DeepSpeed" # export DATA_TYPE="BookCorpusDataset_text_document" -export DATA_PARENT="/lus/eagle/projects/datasets/Megatron-DeepSpeed/GenSLMSubSample200k" -export DATA_TYPE="genslm_subsample_200k_sequence_document" +# export DATA_PARENT="/lus/eagle/projects/datasets/Megatron-DeepSpeed/GenSLMSubSample200k" +# export DATA_TYPE="genslm_subsample_200k_sequence_document" export DATA_DIR="${DATA_PARENT}/dataset" -export DATA_PATH="${DATA_DIR}/${DATA_TYPE}" +# export DATA_PATH="${DATA_DIR}/${DATA_TYPE}" export VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" export MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" +export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/wiki-en-simple/" +export DATA_FILE_LIST="/eagle/datasets//dolma//data_file_list_small.txt" + DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" bash ./generate_config.sh ${DS_CONFIG} || exit 1 -OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} +OUTPUT_PREFIX="logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" +# OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} +OUTPUT_DIR="${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" mkdir -p $OUTPUT_DIR echo "!!!Please see logs at ${OUTPUT_DIR}" @@ -51,8 +57,27 @@ if [ $PP == 1 ]; then fi ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" + +if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" + ds_args=" --deepspeed-activation-checkpointing ${ds_args}" + # --checkpoint-activations \ + # --deepspeed-activation-checkpointing +fi + +gpt_args=() + +if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" + gpt_args+=( + "--checkpoint-activations" + "--checkpoint-num-layers 1" + ) +fi # we are now using activation checkpoint provided by megatron, see below. # ds_args=" --deepspeed-activation-checkpointing ${ds_args}" +# NUM_KV_HEADS="${NUM_KV_HEADS:-0}" +# if [[ $NUM_KV_HEADS -]] # take custom args custom_args=" $@" @@ -67,6 +92,9 @@ fi NCCL=${NCCL:-nccl} +# MODEL=LLAMA_7B +# OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_tp${TP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} + run_cmd=" deepspeed $launcher pretrain_gpt_alcf.py \ --tensor-model-parallel-size $TP \ @@ -86,14 +114,9 @@ run_cmd=" --log-interval 1 \ --eval-iters 100 \ --eval-interval 100 \ - --data-path $DATA_PATH \ - --vocab-file $VOCAB_FILE \ - --merge-file $MERGE_FILE \ - --save-interval 500 \ + --save-interval 50 \ --split 100,0,0 \ --$DTYPE \ - --checkpoint-activations \ - --deepspeed-activation-checkpointing $ds_args \ --no-masked-softmax-fusion \ --no-bias-gelu-fusion \ @@ -101,6 +124,15 @@ run_cmd=" --no-gradient-accumulation-fusion \ --distributed-backend $NCCL \ --num-workers 0 \ + --tokenizer-type Llama2Tokenizer \ + --save checkpoints/${OUTPUT_PREFIX} \ + --load checkpoints/${OUTPUT_PREFIX} \ + --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ + --data-file-list ${DATA_FILE_LIST} \ + --data-path $DATA_PATH \ + --vocab-file $VOCAB_FILE \ + --merge-file $MERGE_FILE \ + ${gpt_args[*]} \ $custom_args \ |& tee $OUTPUT_DIR/output.log " From 9dc348290affa5b5f0c86e2484e42aabe824ef7e Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 5 Feb 2024 16:47:21 -0600 Subject: [PATCH 049/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 43 +++++++++++++++++++++++++------------------ 1 file changed, 25 insertions(+), 18 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 6937bbdf2c..9737477a9e 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -37,17 +37,20 @@ import torch.nn.functional as F # from ezpz import get_logger -from ezpz.dist import setup_torch, get_world_size, setup_wandb +from ezpz.dist import get_world_size, setup_wandb, get_rank -RANK = setup_torch( - backend='deepspeed', - port='5432', -) +# RANK = setup_torch( +# backend='deepspeed', +# port='5432', +# ) +RANK = get_rank() WORLD_SIZE = get_world_size() LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" WANDB_MODE = os.environ.get('WANDB_MODE', None) -DISABLE_WANDB = WANDB_MODE is not None and str(WANDB_MODE).lower() == 'disabled' +DISABLE_WANDB = ( + WANDB_MODE is not None and str(WANDB_MODE).lower() == 'disabled' +) if RANK == 0 and not DISABLE_WANDB: project_name = ( @@ -64,6 +67,7 @@ print('--------------------------------------------------') setup_wandb(project_name=project_name) + def model_provider(pre_process=True, post_process=True): """Build the model.""" @@ -83,6 +87,10 @@ def model_provider(pre_process=True, post_process=True): dpg = mpu.get_data_parallel_group() else: dpg = None + if wandb is not None and wandb.run is not None: + assert wandb is not None and wandb.run is not None + print(f'Updating {wandb.run.name=} at {wandb.run.url=}') + wandb.run.config.update({'args': vars(args)}) with deepspeed.zero.Init(data_parallel_group=dpg, remote_device=None if args.remote_device == 'none' else args.remote_device, config_dict_or_path=args.deepspeed_config_dict, @@ -427,18 +435,17 @@ def main(): # if RANK == 0: # setup_wandb() from torch.profiler import profile, record_function, ProfilerActivity - with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: - model = pretrain( - train_valid_test_datasets_provider, - model_provider, - ModelType.encoder_or_decoder, - forward_step, - args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, - data_post_process=data_post_process - ) - args = get_args() - prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") - + # with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: + model = pretrain( + train_valid_test_datasets_provider, + model_provider, + ModelType.encoder_or_decoder, + forward_step, + args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + data_post_process=data_post_process + ) + # args = get_args() + # prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") # # from megatron.training import get_model # if wandb.run is not None: # args = get_args() From 41208b4b99e40f6e930ed76c76d7cfd1254fe4a9 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 6 Feb 2024 00:35:02 -0600 Subject: [PATCH 050/268] Update `.gitignore` --- .gitignore | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/.gitignore b/.gitignore index fc81539941..610af67ac3 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,8 @@ +outputs/ +venvs/ +wandb/ +llama-logs/ +checkpoints/ *.gz *.txt *.idx From 42f5eb93265922bde57d02d33f61ac55311b74c1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 7 Feb 2024 11:22:24 -0600 Subject: [PATCH 051/268] Update `set_params.sh` --- set_params.sh | 45 +++++++++++++++++++++++++++++---------------- 1 file changed, 29 insertions(+), 16 deletions(-) diff --git a/set_params.sh b/set_params.sh index 696c0eb4aa..41ef9b4908 100644 --- a/set_params.sh +++ b/set_params.sh @@ -1,12 +1,16 @@ #!/bin/bash login # echo "!!!please use generate_hostfile.sh to set hostfile for 18 nodes before training" -export WORLD_SIZE=${WORLD_SIZE:-216} +export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${PBS_NODEFILE}")} export MICRO_BATCH=${MICRO_BATCH:-1} export NLAYERS=${NLAYERS:-96} export HIDDEN=${HIDDEN:-12288} export HEADS=${HEADS:-96} -export SEQ=${SEQ:-2048} +export LR=${LR:-0.0003} +export SEQ=${SEQ:-4096} export TRAIN_ITER=${TRAIN_ITER:-20} +export EVAL_ITERS=${EVAL_ITERS:-100} +export SAVE_INTERVAL=${SAVE_INTERVAL:-50} +export EVAL_INTERVAL=${EVAL_INTERVAL:-50} export ZERO_STAGE=${ZERO_STAGE:-3} export DTYPE=${DTYPE:-fp16} export TP=${TP:-1} @@ -22,17 +26,20 @@ export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} TP=${TP:-1} PP=${PP:-1} -export DATA_PARENT="/home/foremans/polaris/projects/saforem2/Megatron-DeepSpeed" +# export DATA_PARENT="/home/foremans/polaris/projects/saforem2/Megatron-DeepSpeed" # export DATA_TYPE="BookCorpusDataset_text_document" # export DATA_PARENT="/lus/eagle/projects/datasets/Megatron-DeepSpeed/GenSLMSubSample200k" # export DATA_TYPE="genslm_subsample_200k_sequence_document" -export DATA_DIR="${DATA_PARENT}/dataset" +# export DATA_DIR="${DATA_PARENT}/dataset" # export DATA_PATH="${DATA_DIR}/${DATA_TYPE}" -export VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" -export MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" +# export VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" +# export MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" -export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/wiki-en-simple/" -export DATA_FILE_LIST="/eagle/datasets//dolma//data_file_list_small.txt" +export DATA_PATH="/eagle/datasets/dolma/data_Llama2Tokenizer/wiki-en-simple/" +# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select.txt" +export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_only_rust.txt" +# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_modified.txt" +# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_small.txt" DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" @@ -41,7 +48,7 @@ bash ./generate_config.sh ${DS_CONFIG} || exit 1 OUTPUT_PREFIX="logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" # OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} OUTPUT_DIR="${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" -mkdir -p $OUTPUT_DIR +mkdir -p "${OUTPUT_DIR}" echo "!!!Please see logs at ${OUTPUT_DIR}" # Hostfile path @@ -95,6 +102,9 @@ NCCL=${NCCL:-nccl} # MODEL=LLAMA_7B # OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_tp${TP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} +# --vocab-file $VOCAB_FILE \ +# --merge-file $MERGE_FILE \ +# --lr-decay-iters 320000 \ run_cmd=" deepspeed $launcher pretrain_gpt_alcf.py \ --tensor-model-parallel-size $TP \ @@ -107,15 +117,16 @@ run_cmd=" --micro-batch-size $MICRO_BATCH \ --global-batch-size $GLOBAL_BATCH \ --train-iters $TRAIN_ITER \ - --lr 0.00015 \ + --lr ${LR} \ + --min-lr 1.0e-5 \ --lr-warmup-fraction .01 \ --lr-decay-iters 320000 \ --lr-decay-style cosine \ --log-interval 1 \ - --eval-iters 100 \ - --eval-interval 100 \ - --save-interval 50 \ - --split 100,0,0 \ + --eval-iters ${EVAL_ITERS} \ + --eval-interval ${EVAL_INTERVAL} \ + --save-interval ${SAVE_INTERVAL} \ + --split 90,5,5 \ --$DTYPE \ $ds_args \ --no-masked-softmax-fusion \ @@ -127,16 +138,18 @@ run_cmd=" --tokenizer-type Llama2Tokenizer \ --save checkpoints/${OUTPUT_PREFIX} \ --load checkpoints/${OUTPUT_PREFIX} \ + --use-checkpoint-opt_param-scheduler \ --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ --data-file-list ${DATA_FILE_LIST} \ --data-path $DATA_PATH \ - --vocab-file $VOCAB_FILE \ - --merge-file $MERGE_FILE \ ${gpt_args[*]} \ $custom_args \ |& tee $OUTPUT_DIR/output.log " +echo "Using $(which deepspeed)" +ds_report + echo ${run_cmd} eval ${run_cmd} set +x From 8b6d8bfef60932de31f9b02eccb0d18709e6e46e Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Thu, 8 Feb 2024 15:44:38 -0600 Subject: [PATCH 052/268] adding master_addr in case it doesn --- llama_alcf.sh | 11 +++++------ pretrain_gpt_alcf.py | 12 ++++++++++++ 2 files changed, 17 insertions(+), 6 deletions(-) diff --git a/llama_alcf.sh b/llama_alcf.sh index a102c492fb..dcfa41d109 100755 --- a/llama_alcf.sh +++ b/llama_alcf.sh @@ -20,7 +20,7 @@ export SP=$((PBS_JOBSIZE*PPN/PP/TP)) export export DATE_TAG=$(date +"%Y-%m-%d-%H-%M-%S") export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/wiki-en-simple/" -export DATA_FILE_LIST="/eagle/datasets//dolma//data_file_list_small.txt" +export DATA_FILE_LIST="/eagle/datasets//dolma//data_file_list_select.txt" echo "BS: $BS\n PP:$PP \n TP: $TP, PBS_JOBSIZE: $PBS_JOBSIZE" HIDDEN_SIZE=4096 @@ -34,18 +34,17 @@ OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAY MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --hostfile $PBS_NODEFILE python3 ./pretrain_gpt_alcf.py \ --tensor-model-parallel-size ${TP} \ --pipeline-model-parallel-size ${PP} \ - --num-layers 32 \ - --hidden-size 4096 \ + --num-layers ${NUM_LAYERS} \ + --hidden-size ${HIDDEN_SIZE} \ --ffn-hidden-size 5504 \ --num-attention-heads 32 \ --micro-batch-size ${MBS} \ --global-batch-size ${BS} \ - --seq-length 2048 \ - --max-position-embeddings 2048 \ + --seq-length ${SEQ_LENGTH} \ + --max-position-embeddings ${EMBEDDINGS} \ --train-iters 10 \ --save ${MD}/checkpoints/${OUTPUT_PREFIX} \ --load ${MD}/checkpoints/${OUTPUT_PREFIX} \ - --data-impl mmap \ --tokenizer-type Llama2Tokenizer \ --split 949,50,1 \ --distributed-backend nccl \ diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 6937bbdf2c..70c656f9f1 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -426,6 +426,18 @@ def git_ds_info(): def main(): # if RANK == 0: # setup_wandb() + from mpi4py import MPI + rank = MPI.COMM_WORLD.rank + + if rank == 0: + master_addr = socket.gethostname() + else: + master_addr = None + + master_addr = MPI.COMM_WORLD.bcast(master_addr, root=0) + os.environ["MASTER_ADDR"] = master_addr + os.environ["MASTER_PORT"] = str(2345) + from torch.profiler import profile, record_function, ProfilerActivity with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: model = pretrain( From 9030d779686d83dc41106620b04b739a2130fda4 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Thu, 8 Feb 2024 16:08:08 -0600 Subject: [PATCH 053/268] added socket --- pretrain_gpt_alcf.py | 1 + 1 file changed, 1 insertion(+) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 70c656f9f1..536bdca110 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -426,6 +426,7 @@ def git_ds_info(): def main(): # if RANK == 0: # setup_wandb() + import socket from mpi4py import MPI rank = MPI.COMM_WORLD.rank From 7797c2f930166470c77fae258c89bce474dd28e7 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 9 Feb 2024 11:03:35 -0600 Subject: [PATCH 054/268] Update `generate_config.sh` --- generate_config.sh | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/generate_config.sh b/generate_config.sh index 210220e192..6a676fa1b1 100644 --- a/generate_config.sh +++ b/generate_config.sh @@ -21,9 +21,12 @@ common="\ \"steps_per_print\": 1, \"gradient_accumulation_steps\": $GRAD_ACC_STEPS, \"optimizer\": { - \"type\": \"Adam\", + \"type\": \"AdamW\", \"params\": { - \"lr\": 0.00015, + \"lr\": ${LR}, + \"beta1\": 0.9, + \"beta2\": 0.95, + \"eps\": 1e-5, \"weight_decay\": 1e-2 } }, From d1367d43b2461743a3faec501d9e258afce00f6e Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 10 Feb 2024 20:23:08 -0600 Subject: [PATCH 055/268] Update `set_params.sh,generate_config.sh` --- generate_config.sh | 10 +++++++++- set_params.sh | 23 +++++++++++++---------- 2 files changed, 22 insertions(+), 11 deletions(-) diff --git a/generate_config.sh b/generate_config.sh index 6a676fa1b1..6bea420a2a 100644 --- a/generate_config.sh +++ b/generate_config.sh @@ -27,7 +27,15 @@ common="\ \"beta1\": 0.9, \"beta2\": 0.95, \"eps\": 1e-5, - \"weight_decay\": 1e-2 + \"weight_decay\": 1e-1 + } + }, + \"scheduler\": { + \"type\": \"WarmupLR\", + \"params\": { + \"warmup_min_lr\": 0.00003, + \"warmup_max_lr\": 0.0003, + \"warmup_num_steps\": 5000 } }, \"zero_allow_untested_optimizer\": true, diff --git a/set_params.sh b/set_params.sh index 41ef9b4908..c87524db13 100644 --- a/set_params.sh +++ b/set_params.sh @@ -7,13 +7,13 @@ export HIDDEN=${HIDDEN:-12288} export HEADS=${HEADS:-96} export LR=${LR:-0.0003} export SEQ=${SEQ:-4096} -export TRAIN_ITER=${TRAIN_ITER:-20} -export EVAL_ITERS=${EVAL_ITERS:-100} -export SAVE_INTERVAL=${SAVE_INTERVAL:-50} -export EVAL_INTERVAL=${EVAL_INTERVAL:-50} -export ZERO_STAGE=${ZERO_STAGE:-3} +export TRAIN_ITER=${TRAIN_ITER:-300000} +export EVAL_ITERS=${EVAL_ITERS:-50} +export SAVE_INTERVAL=${SAVE_INTERVAL:-1000} +export EVAL_INTERVAL=${EVAL_INTERVAL:-50000} +export ZERO_STAGE=${ZERO_STAGE:-2} export DTYPE=${DTYPE:-fp16} -export TP=${TP:-1} +export TP=${TP:-2} export PP=${PP:-1} export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) @@ -36,8 +36,9 @@ PP=${PP:-1} # export MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" export DATA_PATH="/eagle/datasets/dolma/data_Llama2Tokenizer/wiki-en-simple/" +export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_3280.txt" # export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select.txt" -export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_only_rust.txt" +# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_only_rust.txt" # export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_modified.txt" # export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_small.txt" @@ -118,10 +119,11 @@ run_cmd=" --global-batch-size $GLOBAL_BATCH \ --train-iters $TRAIN_ITER \ --lr ${LR} \ - --min-lr 1.0e-5 \ - --lr-warmup-fraction .01 \ - --lr-decay-iters 320000 \ + --lr-warmup-iters 5000 \ + --lr-decay-iters 10000 \ + --ffn-hidden-size 11008 \ --lr-decay-style cosine \ + --data-impl mmap \ --log-interval 1 \ --eval-iters ${EVAL_ITERS} \ --eval-interval ${EVAL_INTERVAL} \ @@ -139,6 +141,7 @@ run_cmd=" --save checkpoints/${OUTPUT_PREFIX} \ --load checkpoints/${OUTPUT_PREFIX} \ --use-checkpoint-opt_param-scheduler \ + --accumulate-allreduce-grads-in-fp32 \ --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ --data-file-list ${DATA_FILE_LIST} \ --data-path $DATA_PATH \ From 615faa46cde9e2a5ecbae3cccb8dcab9ee3a8af8 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 13 Feb 2024 09:25:23 -0600 Subject: [PATCH 056/268] Add `train_llama_alcf_chunk_00_of_20.sh` --- train_llama_alcf_chunk_00_of_20.sh | 53 ++++++++++++++++++++++++++++++ 1 file changed, 53 insertions(+) create mode 100755 train_llama_alcf_chunk_00_of_20.sh diff --git a/train_llama_alcf_chunk_00_of_20.sh b/train_llama_alcf_chunk_00_of_20.sh new file mode 100755 index 0000000000..15e4e789aa --- /dev/null +++ b/train_llama_alcf_chunk_00_of_20.sh @@ -0,0 +1,53 @@ +#!/bin/bash --login +#PBS -l walltime=06:00:00 +#PBS -A argonne_tpc +#PBS -q prod +#PBS -l select=48 +#PBS -l filesystems=eagle:home + +cd "${PBS_O_WORKDIR}" || exit +if [[ ! -d ezpz ]]; then + git clone https://github.com/saforem2/ezpz +else + echo "Found ezpz!" +fi +source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit +source ezpz/src/ezpz/bin/getjobenv || exit + +module load conda/2023-10-04; conda activate base +echo "WORLD_SIZE:${WORLD_SIZE}" +echo "NCCL: ${NCCL:-nccl}" + +export PP=1 +export TP=2 + +export HEADS=32 +export NLAYERS=32 +export HIDDEN=4096 +export NUM_KV_HEAD=8 + +export ZERO_STAGE=2 +export MICRO_BATCH=8 +export GRAD_ACC_STEPS=1 +export SEQ=4096 +export DTYPE=fp16 + +export EVAL_ITERS=20 +export TRAIN_ITER=317892 +export SAVE_INTERVAL=5000 +export EVAL_INTERVAL=50000 + +export DATA_PATH="/eagle/datasets/dolma/data_Llama2Tokenizer/wiki-en-simple/" +export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/data_file_list_chunk_0_of_20.txt" + +echo "++++++++++++++++++++++++++++++++++++++++++++++++++" +echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST}" +echo "++++++++++++++++++++++++++++++++++++++++++++++++++" + +export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" +echo "MODEL_TYPE: ${MODEL_TYPE}" + +export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" +export USE_ACTIVATION_CHECKPOINTING=1 ; [ -n "${MODEL_TYPE}" ] + +bash set_params.sh "$LLAMA_ARGS" --use-flash-attn-v2 --num-key-value-heads $NUM_KV_HEAD |& tee "train-${MODEL_TYPE}-mbs-${MICRO_BATCH}-zs${ZERO_STAGE}-kvh${NUM_KV_HEAD}-$(tstamp).log" From ce5d89611f673582786f95cb3cd5660c41367a68 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Wed, 14 Feb 2024 12:49:30 -0600 Subject: [PATCH 057/268] added profile as an option --- megatron/arguments.py | 1 + pretrain_gpt_alcf.py | 22 ++++++++++++++++------ 2 files changed, 17 insertions(+), 6 deletions(-) diff --git a/megatron/arguments.py b/megatron/arguments.py index 083bf30f6a..39326218e0 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -952,6 +952,7 @@ def _add_training_args(parser): dest='gradient_accumulation_fusion') group.add_argument('--use-dataset-only', type=bool, required=False, default=False, help='If set to True, only use the megatron dataset for external trainer ') + group.add_argument('--profile', action='store_true', help='Enable Torch Profiler') return parser diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 536bdca110..0f1fcb1ad1 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -438,9 +438,22 @@ def main(): master_addr = MPI.COMM_WORLD.bcast(master_addr, root=0) os.environ["MASTER_ADDR"] = master_addr os.environ["MASTER_PORT"] = str(2345) - - from torch.profiler import profile, record_function, ProfilerActivity - with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: + args = get_args() + + if (args.profile): + from torch.profiler import profile, record_function, ProfilerActivity + with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: + model = pretrain( + train_valid_test_datasets_provider, + model_provider, + ModelType.encoder_or_decoder, + forward_step, + args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + data_post_process=data_post_process + ) + + prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") + else: model = pretrain( train_valid_test_datasets_provider, model_provider, @@ -449,9 +462,6 @@ def main(): args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, data_post_process=data_post_process ) - args = get_args() - prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") - # # from megatron.training import get_model # if wandb.run is not None: # args = get_args() From 8280d0172863f6c1e0aad22b08091cbe204f24cf Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 19 Feb 2024 09:54:26 -0600 Subject: [PATCH 058/268] Update `train_llama_alcf_chunk-00-of-20.sh` --- ...0.sh => train_llama_alcf_chunk_00-of-20.sh | 37 +++++++++++-------- 1 file changed, 22 insertions(+), 15 deletions(-) rename train_llama_alcf_chunk_00_of_20.sh => train_llama_alcf_chunk_00-of-20.sh (52%) diff --git a/train_llama_alcf_chunk_00_of_20.sh b/train_llama_alcf_chunk_00-of-20.sh similarity index 52% rename from train_llama_alcf_chunk_00_of_20.sh rename to train_llama_alcf_chunk_00-of-20.sh index 15e4e789aa..46a00aea52 100755 --- a/train_llama_alcf_chunk_00_of_20.sh +++ b/train_llama_alcf_chunk_00-of-20.sh @@ -6,18 +6,15 @@ #PBS -l filesystems=eagle:home cd "${PBS_O_WORKDIR}" || exit +module load conda/2023-10-04; conda activate base if [[ ! -d ezpz ]]; then git clone https://github.com/saforem2/ezpz else echo "Found ezpz!" fi -source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit +source ezpz/src/ezpz/bin/savejobenv || exit source ezpz/src/ezpz/bin/getjobenv || exit -module load conda/2023-10-04; conda activate base -echo "WORLD_SIZE:${WORLD_SIZE}" -echo "NCCL: ${NCCL:-nccl}" - export PP=1 export TP=2 @@ -34,20 +31,30 @@ export DTYPE=fp16 export EVAL_ITERS=20 export TRAIN_ITER=317892 -export SAVE_INTERVAL=5000 -export EVAL_INTERVAL=50000 +export SAVE_INTERVAL=200 +# export EVAL_INTERVAL=1000 export DATA_PATH="/eagle/datasets/dolma/data_Llama2Tokenizer/wiki-en-simple/" -export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/data_file_list_chunk_0_of_20.txt" - -echo "++++++++++++++++++++++++++++++++++++++++++++++++++" -echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST}" -echo "++++++++++++++++++++++++++++++++++++++++++++++++++" +export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/20/data_file_list_chunk_0_of_20.txt" +# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_5.txt" +# export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/40/data_file_list_chunk_0_of_40.txt" +# export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/data_file_list_chunk_0_of_20.txt" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" -echo "MODEL_TYPE: ${MODEL_TYPE}" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" -export USE_ACTIVATION_CHECKPOINTING=1 ; [ -n "${MODEL_TYPE}" ] +export USE_ACTIVATION_CHECKPOINTING=1 ; +export EXTRA_ARGS="--use-flash-attn-v2 --num-key-value-heads ${NUM_KV_HEAD}" + +echo "++++++++++++++++++++++++++++++++++++++++++++++++++" +echo "- WORLD_SIZE:${WORLD_SIZE}" +echo "- NCCL: ${NCCL:-nccl}" +echo "- MODEL_TYPE: ${MODEL_TYPE}" +echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" +echo "++++++++++++++++++++++++++++++++++++++++++++++++++" + + # [ -n "${MODEL_TYPE}" ] && + EXEC="./set_params.sh" + OUTPUT="train-${MODEL_TYPE}-mbs-${MICRO_BATCH}-zs${ZERO_STAGE}-kvh${NUM_KV_HEAD}-$(tstamp).log" -bash set_params.sh "$LLAMA_ARGS" --use-flash-attn-v2 --num-key-value-heads $NUM_KV_HEAD |& tee "train-${MODEL_TYPE}-mbs-${MICRO_BATCH}-zs${ZERO_STAGE}-kvh${NUM_KV_HEAD}-$(tstamp).log" + [ -f "${EXEC}" ] && bash "${EXEC}" "${LLAMA_ARGS}" "${EXTRA_ARGS}" |& tee "${OUTPUT}" From 63385a8c4a4114ecb81483b5997409977c064ee4 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 19 Feb 2024 10:03:02 -0600 Subject: [PATCH 059/268] Update `megatron/data/blendable_dataset.py` --- megatron/data/blendable_dataset.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/megatron/data/blendable_dataset.py b/megatron/data/blendable_dataset.py index 2516e58415..78ab7cb005 100644 --- a/megatron/data/blendable_dataset.py +++ b/megatron/data/blendable_dataset.py @@ -34,8 +34,8 @@ def __init__(self, datasets, weights, size, *, # Build indicies. def _build_indices(): start_time = time.time() - assert num_datasets < 255 - dataset_index = np.zeros(self.size, dtype=np.uint8) + # assert num_datasets < 255 + dataset_index = np.zeros(self.size, dtype=np.int64) dataset_sample_index = np.zeros(self.size, dtype=np.int64) from megatron.data import helpers From 74e403f7432e452a4b10a925786a4abf9428f6a0 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 19 Feb 2024 10:31:40 -0600 Subject: [PATCH 060/268] Update `set_params.sh` --- set_params.sh | 25 ++++--------------------- 1 file changed, 4 insertions(+), 21 deletions(-) diff --git a/set_params.sh b/set_params.sh index c87524db13..c57eea34cb 100644 --- a/set_params.sh +++ b/set_params.sh @@ -26,25 +26,8 @@ export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} TP=${TP:-1} PP=${PP:-1} -# export DATA_PARENT="/home/foremans/polaris/projects/saforem2/Megatron-DeepSpeed" -# export DATA_TYPE="BookCorpusDataset_text_document" -# export DATA_PARENT="/lus/eagle/projects/datasets/Megatron-DeepSpeed/GenSLMSubSample200k" -# export DATA_TYPE="genslm_subsample_200k_sequence_document" -# export DATA_DIR="${DATA_PARENT}/dataset" -# export DATA_PATH="${DATA_DIR}/${DATA_TYPE}" -# export VOCAB_FILE="${DATA_DIR}/gpt2-vocab.json" -# export MERGE_FILE="${DATA_DIR}/gpt2-merges.txt" - -export DATA_PATH="/eagle/datasets/dolma/data_Llama2Tokenizer/wiki-en-simple/" -export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_3280.txt" -# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select.txt" -# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_only_rust.txt" -# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_modified.txt" -# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_small.txt" - - DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" -bash ./generate_config.sh ${DS_CONFIG} || exit 1 +bash ./generate_config.sh "${DS_CONFIG}" || exit 1 OUTPUT_PREFIX="logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" # OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} @@ -55,12 +38,12 @@ echo "!!!Please see logs at ${OUTPUT_DIR}" # Hostfile path hostfile_deepspeed=./hostfile_deepspeed hostfile_mpich=./hostfile_mpich -cat $PBS_NODEFILE > hostfile_mpich -cat $PBS_NODEFILE > hostfile_deepspeed ; sed -e 's/$/ slots=4/' -i hostfile_deepspeed +cat "$PBS_NODEFILE" > hostfile_mpich +cat "$PBS_NODEFILE" > hostfile_deepspeed ; sed -e 's/$/ slots=4/' -i hostfile_deepspeed ds_args=" " ds_args=" --deepspeed ${ds_args}" -if [ $PP == 1 ]; then +if [ "$PP" == 1 ]; then ds_args=" --no-pipeline-parallel ${ds_args}" fi ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" From cc6c8805452f4a8185736003ba64bd4648eec170 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 19 Feb 2024 10:31:56 -0600 Subject: [PATCH 061/268] Update `megatron/training.py` --- megatron/training.py | 32 +++++++++++++++++--------------- 1 file changed, 17 insertions(+), 15 deletions(-) diff --git a/megatron/training.py b/megatron/training.py index 29d2181d46..ef32cd3856 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -1066,21 +1066,6 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, elapsed_time_per_iteration, args.consumed_train_samples) writer.add_scalar('iteration-time/iteration-time vs tokens', elapsed_time_per_iteration, args.consumed_train_tokens) - if wandb is not None and getattr(wandb, 'run', None) is not None: - wandb_metrics |= { - 'iteration': iteration, - 'iteration_time': elapsed_time_per_iteration, - 'iteration_time_vs_tokens': ( - (elapsed_time_per_iteration - / args.consumed_train_tokens) - ), - 'iteration_time_vs_samples': ( - (elapsed_time_per_iteration - / args.consumed_train_samples), - ), - } - if wandb is not None and getattr(wandb, 'run', None) is not None: - wandb.log(wandb_metrics) log_string = ' iteration {:8d}/{:8d} |'.format( iteration, args.train_iters) log_string += ' consumed samples: {:12d} |'.format( @@ -1091,6 +1076,21 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, elapsed_time_per_iteration * 1000.0) log_string += ' learning rate: {:.3E} |'.format(learning_rate) log_string += ' global batch size: {:5d} |'.format(batch_size) + if wandb is not None and getattr(wandb, 'run', None) is not None: + wandb_metrics |= { + 'training/iteration': iteration, + 'training/iteration_time': elapsed_time_per_iteration, + 'training/iteration_time_vs_tokens': ( + (elapsed_time_per_iteration + / args.consumed_train_tokens) + ), + 'training/iteration_time_vs_samples': ( + (elapsed_time_per_iteration + / args.consumed_train_samples), + ), + 'training/consumed_samples': args.consumed_train_samples, + 'training/consumed_tokens': args.consumed_train_tokens, + } for key in total_loss_dict: if key not in [advanced_iters_key, skipped_iters_key, nan_iters_key]: @@ -1099,6 +1099,8 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, if avg > 0.0: log_string += ' {}: {:.6E} |'.format(key, avg) total_loss_dict[key] = get_accelerator().FloatTensor([0.0]) + if wandb is not None and getattr(wandb, 'run', None) is not None: + wandb.log(wandb_metrics) if loss_scale is not None: log_string += ' loss scale: {:.1f} |'.format(loss_scale) if grad_norm is not None: From ead0bc6d5197f8f3c40b0d29a0212c098d307e4b Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 19 Feb 2024 10:32:33 -0600 Subject: [PATCH 062/268] Update `megatron/data/indexed_dataset.py` --- megatron/data/indexed_dataset.py | 1 + 1 file changed, 1 insertion(+) diff --git a/megatron/data/indexed_dataset.py b/megatron/data/indexed_dataset.py index 219ffe8031..62ebdc9813 100644 --- a/megatron/data/indexed_dataset.py +++ b/megatron/data/indexed_dataset.py @@ -504,6 +504,7 @@ def _do_init(self, path, skip_warmup): print_rank_0(" warming up data mmap file...") _warmup_mmap_file(data_file_path(self._path)) print_rank_0(" creating numpy buffer of mmap...") + print_rank_0(data_file_path(self._path)) self._bin_buffer_mmap = np.memmap(data_file_path(self._path), mode='r', order='C') print_rank_0(" creating memory view of numpy buffer...") self._bin_buffer = memoryview(self._bin_buffer_mmap) From 9cde45ad366797b2d1c7b7db8d01cf97add83e0c Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 19 Feb 2024 10:33:37 -0600 Subject: [PATCH 063/268] Update `megatron/data/gpt_dataset.py` --- megatron/data/gpt_dataset.py | 26 +++++++++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/megatron/data/gpt_dataset.py b/megatron/data/gpt_dataset.py index 1d9b7e1c1d..210a92c85e 100644 --- a/megatron/data/gpt_dataset.py +++ b/megatron/data/gpt_dataset.py @@ -273,7 +273,31 @@ def __getitem__(self, idx): args = get_args() orig_idx = idx # Get the shuffled index. - idx = self.shuffle_idx[idx] + try: + idx = self.shuffle_idx[idx] + except IndexError as exc: + if is_rank_0(): + import json + from rich import print_json + print(exc) + print( + '\n'.join( + ['-------------------------------------------------', + f'Trying to access {idx=} from self.shuffle_idx,', + f'but {len(self.shuffle_idx)=}', + '-------------------------------------------------'] + ) + ) + print_json( + json.dumps( + { + 'doc_idx': len(self.doc_idx), + 'sample_idx': len(self.sample_idx), + 'shuffle_idx': len(self.shuffle_idx), + }, + indent=4, + ) + ) # Start and end documents and offsets. doc_index_f = self.sample_idx[idx][0] doc_index_l = self.sample_idx[idx + 1][0] From bffa9f89e8237311fcfa265e138ff5edd49bab7a Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 20 Feb 2024 23:45:34 -0600 Subject: [PATCH 064/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 9737477a9e..36ef5d153f 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -58,7 +58,7 @@ 'WB_PROJECT', os.environ.get( 'WANDB_PROJECT', - 'GenSLM-Megatron-DS' + 'AuroraGPT' ), ) ) From 0a427230553de99d6db1563f9c1503799adc11c8 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 20 Feb 2024 23:45:49 -0600 Subject: [PATCH 065/268] Update `set_params.sh` --- set_params.sh | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/set_params.sh b/set_params.sh index c57eea34cb..8682a86907 100644 --- a/set_params.sh +++ b/set_params.sh @@ -19,6 +19,8 @@ export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} +# echo "USING DATA_FILE_LIST: ${DATA_FILE_LIST}" || exit + # bash $LLM_DK_DIR/intel-extension-for-deepspeed/examples/gpt.sh $@ @@ -127,7 +129,6 @@ run_cmd=" --accumulate-allreduce-grads-in-fp32 \ --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ --data-file-list ${DATA_FILE_LIST} \ - --data-path $DATA_PATH \ ${gpt_args[*]} \ $custom_args \ |& tee $OUTPUT_DIR/output.log From 2bf20836a7b1610c567231571ebcdbc5d5b0e1f7 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 21 Feb 2024 11:29:48 -0600 Subject: [PATCH 066/268] Add `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 193 ++++++++++++++++++++++++++++++++++++ 1 file changed, 193 insertions(+) create mode 100644 train_llama_alcf_polaris.sh diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh new file mode 100644 index 0000000000..a06bfcd194 --- /dev/null +++ b/train_llama_alcf_polaris.sh @@ -0,0 +1,193 @@ +#!/bin/bash --login +#PBS -l walltime=06:00:00 +#PBS -A argonne_tpc +#PBS -q prod +#PBS -l select=48 +#PBS -l filesystems=eagle:home + +cd "${PBS_O_WORKDIR}" || exit +module load conda/2023-10-04; conda activate base +if [[ ! -d ezpz ]]; then + git clone https://github.com/saforem2/ezpz +else + echo "Found ezpz!" +fi +source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit +source ezpz/src/ezpz/bin/getjobenv || exit + +# ---- Parallelism Settings ---- +export PP=${PP:-1} +export TP=${TP:-2} +# ------------------------------ + +HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" +export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} + +# ---- Llama2 7B Config ----------------------- +export HEADS=${HEADS:-32} +export NLAYERS=${NLAYERS:-32} +export HIDDEN=${HIDDEN:-4096} +export NUM_KV_HEAD=${NUM_KV_HEAD:-8} +# --------------------------------------------- + +# ---- Run Settings ------------------------------------------ +export LR=${LR:-0.00015} +export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 +export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 +export ZERO_STAGE=${ZERO_STAGE:-2} +export MICRO_BATCH=${MICRO_BATCH:-8} +export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} +export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) +# --------------------------------------------- + +export EVAL_ITERS=${EVAL_ITERS:-20} +export TRAIN_ITER=${TRAIN_ITER:-317892} +export SAVE_INTERVAL=${SAVE_INTERVAL:-200} +export EVAL_INTERVAL=${EVAL_INTERVAL:-50000} +export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} +# export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} + +# export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/40/data_file_list_chunk_0_of_40.txt" +# export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/10/data_file_list_chunk_0_of_10.txt" +export DATA_FILE_LIST="./dolma_data_file_list-00-of-04.txt" +# export DATA_FILE_LIST="./dolma-chunk-00-of-40.txt" + +export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" + +export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" +export EXTRA_ARGS="--use-flash-attn-v2 --num-key-value-heads ${NUM_KV_HEAD}" + +# export DATA_CACHE_PATH="${DATA_CACHE_PATH}" +if [[ -n "$DATA_CACHE_PATH" ]]; then + echo "Using DATA_CACHE_PATH: ${DATA_CACHE_PATH}" + EXTRA_ARGS="${EXTRA_ARGS} --data-cache-path ${DATA_CACHE_PATH}" +else + echo "Not using DATA_CACHE_PATH !!" +fi + +echo "++++++++++++++++++++++++++++++++++++++++++++++++++" +echo "- WORLD_SIZE:${WORLD_SIZE}" +echo "- NCCL: ${NCCL:-nccl}" +echo "- MODEL_TYPE: ${MODEL_TYPE}" +echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" +echo "++++++++++++++++++++++++++++++++++++++++++++++++++" + + +# bash $LLM_DK_DIR/intel-extension-for-deepspeed/examples/gpt.sh $@ + +DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" +bash ./generate_config.sh "${DS_CONFIG}" || exit 1 + +OUTPUT_PREFIX="logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" +# OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} +OUTPUT_DIR="${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" +mkdir -p "${OUTPUT_DIR}" +echo "!!!Please see logs at ${OUTPUT_DIR}" + +# Hostfile path +hostfile_deepspeed=./hostfile_deepspeed +hostfile_mpich=./hostfile_mpich +cat "$PBS_NODEFILE" > hostfile_mpich +cat "$PBS_NODEFILE" > hostfile_deepspeed ; sed -e 's/$/ slots=4/' -i hostfile_deepspeed + +ds_args=" " +ds_args=" --deepspeed ${ds_args}" +if [ "$PP" == 1 ]; then + ds_args=" --no-pipeline-parallel ${ds_args}" +fi +ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" +ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" + +if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" + ds_args=" --deepspeed-activation-checkpointing ${ds_args}" + # --checkpoint-activations \ + # --deepspeed-activation-checkpointing +fi + +gpt_args=() + +if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" + gpt_args+=( + "--checkpoint-activations" + "--checkpoint-num-layers 1" + ) +fi +# we are now using activation checkpoint provided by megatron, see below. +# ds_args=" --deepspeed-activation-checkpointing ${ds_args}" +# NUM_KV_HEADS="${NUM_KV_HEADS:-0}" +# if [[ $NUM_KV_HEADS -]] + +# take custom args +custom_args=" $@" + +# launcher setting +LAUNCHER=${LAUNCHER:-MPICH} +if [[ $LAUNCHER == "deepspeed" ]]; then + launcher="" +else + launcher="--force_multi --hostfile $hostfile_deepspeed --launcher=${LAUNCHER} --launcher_args='-hostfile ${hostfile_mpich}'" +fi + +NCCL=${NCCL:-nccl} +EXEC="./pretrain_gpt_alcf.py" + +# MODEL=LLAMA_7B +# OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_tp${TP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} + +# --vocab-file $VOCAB_FILE \ +# --merge-file $MERGE_FILE \ +# --lr-decay-iters 320000 \ + # --num-workers 0 \ +run_cmd=" + deepspeed $launcher ${EXEC} \ + --tensor-model-parallel-size $TP \ + --pipeline-model-parallel-size $PP \ + --num-layers $NLAYERS \ + --hidden-size $HIDDEN \ + --num-attention-heads $HEADS \ + --seq-length $SEQ \ + --max-position-embeddings $SEQ \ + --micro-batch-size $MICRO_BATCH \ + --global-batch-size $GLOBAL_BATCH \ + --train-iters $TRAIN_ITER \ + --lr ${LR} \ + --lr-warmup-iters 5000 \ + --lr-decay-iters 10000 \ + --ffn-hidden-size 11008 \ + --lr-decay-style cosine \ + --data-impl mmap \ + --log-interval 1 \ + --eval-iters ${EVAL_ITERS} \ + --eval-interval ${EVAL_INTERVAL} \ + --save-interval ${SAVE_INTERVAL} \ + --split 90,5,5 \ + --$DTYPE \ + $ds_args \ + --no-masked-softmax-fusion \ + --no-bias-gelu-fusion \ + --no-bias-dropout-fusion \ + --no-gradient-accumulation-fusion \ + --distributed-backend $NCCL \ + --tokenizer-type Llama2Tokenizer \ + --save checkpoints/${OUTPUT_PREFIX} \ + --load checkpoints/${OUTPUT_PREFIX} \ + --use-checkpoint-opt_param-scheduler \ + --accumulate-allreduce-grads-in-fp32 \ + --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ + --data-file-list ${DATA_FILE_LIST} \ + --num-workers 4 \ + ${LLAMA_ARGS} \ + ${EXTRA_ARGS} \ + ${gpt_args[*]} \ + $custom_args \ + |& tee $OUTPUT_DIR/output.log + " + +echo "Using $(which deepspeed)" +ds_report + +echo ${run_cmd} +eval ${run_cmd} +set +x From 346ddc38ea9e15b1703503eb9798c4c7e1c07a6e Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 21 Feb 2024 15:50:38 -0600 Subject: [PATCH 067/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 124 +++++++++++++++++++++++++++++++----- 1 file changed, 107 insertions(+), 17 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index a06bfcd194..049d854f71 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -5,21 +5,59 @@ #PBS -l select=48 #PBS -l filesystems=eagle:home +ezpz() { + if [[ ! -d ezpz ]]; then + git clone https://github.com/saforem2/ezpz + else + echo "Found ezpz!" + fi + echo "Using :snake: $(which python3) to install \`ezpz\`:" + mkdir -p logs + python3 -m pip install -e ezpz > ezpz-install.log 2>&1 + source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit + source ezpz/src/ezpz/bin/getjobenv || exit +} + +makeHostfiles() { + GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') + export GPUS_PER_NODE="${GPUS_PER_NODE}" + # ---- Make MPICH hostfile ---------------- + export hostfile_mpich=hostfile_mpich + cat "$PBS_NODEFILE" > "${hostfile_mpich}" + # ---- Make DeepSpeed hostfile ------------------- + export hostfile_deepspeed=hostfile_deepspeed + cat "$PBS_NODEFILE" > "${hostfile_deepspeed}" + sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" + { + echo "PATH=${PATH}" ; + echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" ; + echo "http_proxy=${http_proxy}" ; + echo "https_pro]xy=${https_proxy}" ; + echo "CFLAGS=${CFLAGS}" ; + echo "PYTHONUSERBASE=$PYTHONUSERBASE" ; + } > .deepspeed_env + # echo "PATH=${PATH}" > .deepspeed_env + # echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> .deepspeed_env + # echo "http_proxy=${http_proxy}" >> .deepspeed_env + # echo "https_proxy=${https_proxy}" >> .deepspeed_env + # echo "CFLAGS=${CFLAGS}" >> .d eepspeed_env + # echo "PYTHONUSERBASE=$PYTHONUSERBASE" >> .deepspeed_env + # ------------------------------------------------- +} + + +# ==== SCRIPT START ======================================================== cd "${PBS_O_WORKDIR}" || exit module load conda/2023-10-04; conda activate base -if [[ ! -d ezpz ]]; then - git clone https://github.com/saforem2/ezpz -else - echo "Found ezpz!" -fi -source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit -source ezpz/src/ezpz/bin/getjobenv || exit +ezpz +makeHostfiles # ---- Parallelism Settings ---- export PP=${PP:-1} export TP=${TP:-2} # ------------------------------ +export HERE=$(python3 -c 'import os; print(os.getcwd())') HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} @@ -34,7 +72,7 @@ export NUM_KV_HEAD=${NUM_KV_HEAD:-8} export LR=${LR:-0.00015} export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 -export ZERO_STAGE=${ZERO_STAGE:-2} +export ZERO_STAGE=${ZERO_STAGE:-1} export MICRO_BATCH=${MICRO_BATCH:-8} export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) @@ -47,24 +85,76 @@ export EVAL_INTERVAL=${EVAL_INTERVAL:-50000} export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} +export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" +export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" # export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/40/data_file_list_chunk_0_of_40.txt" # export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/10/data_file_list_chunk_0_of_10.txt" -export DATA_FILE_LIST="./dolma_data_file_list-00-of-04.txt" +# + +# export DOLMA_CHUNK_00_of_10="./chunks/10/data_file_list_chunk_00_of_10.txt" # 762 documents (lines) +# export DOLMA_CHUNK_01_of_10="./chunks/10/data_file_list_chunk_01_of_10.txt" # 722 +# export DOLMA_CHUNK_02_of_10="./chunks/10/data_file_list_chunk_02_of_10.txt" # 727 +# export DOLMA_CHUNK_03_of_10="./chunks/10/data_file_list_chunk_03_of_10.txt" # 707 +# export DOLMA_CHUNK_04_of_10="./chunks/10/data_file_list_chunk_04_of_10.txt" # 744 +# export DOLMA_CHUNK_05_of_10="./chunks/10/data_file_list_chunk_05_of_10.txt" # 766 +# export DOLMA_CHUNK_06_of_10="./chunks/10/data_file_list_chunk_06_of_10.txt" # 730 +# export DOLMA_CHUNK_07_of_10="./chunks/10/data_file_list_chunk_07_of_10.txt" # 759 +# export DOLMA_CHUNK_08_of_10="./chunks/10/data_file_list_chunk_08_of_10.txt" # 777 +# export DOLMA_CHUNK_09_of_10="./chunks/10/data_file_list_chunk_09_of_10.txt" # 752 + +# +# export DOLMA_CHUNK_00_of_04="./dolma_data_file_list-00-of-04.txt" # 1860 documents (lines) +# export DOLMA_CHUNK_01_of_04="./dolma_data_file_list-01-of-04.txt" # 1860 documents (lines) +# export DOLMA_CHUNK_02_of_04="./dolma_data_file_list-02-of-04.txt" # 1860 documents (lines) +# export DOLMA_CHUNK_03_of_04="./dolma_data_file_list-03-of-04.txt" # 1860 documents (lines) +# export DOLMA_CHUNK_04_of_04="./dolma_data_file_list-04-of-04.txt" # 6 documents (lines) + + + +# if [[ -n "$DEBUG_RUN" ]]; then +# # echo "Using LAST DOLMA CHUNK {09 / 10} with ${NDOCS} documents..." +# export DATA_FILE_LIST=${DATA_FILE_LIST:-${DOLMA_CHUNK_09_of_10}} +# # export ndocs=$(wc -l < "${DATA_FILE_LIST}") +# else +# # export fname="./chunks/10/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_10.txt" +# # export fname="${DOLMA_CHUNK_!{DOLMA_CHUNK_IDX}_of_10}" +# # export DATA_FILE_LIST="${DATA_FILE_LIST:-${DOLMA_CHUNK_00_of_10}}" +# fi +# export ndocs +# export DATA_FILE_LIST="${DATA_FILE_LIST}" +# export DATA_FILE_LIST="./dolma_data_file_list-00-of-04.txt" # export DATA_FILE_LIST="./dolma-chunk-00-of-40.txt" +# +# bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit -export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" +# export DATA_CACHE_PATH="${DATA_CACHE_PATH}" +# if [[ -z "$DATA_CACHE_PATH" ]]; then +# echo "Not using DATA_CACHE_PATH !!" +# else +# echo "Using DATA_CACHE_PATH: ${DATA_CACHE_PATH}" +# fi -export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" export EXTRA_ARGS="--use-flash-attn-v2 --num-key-value-heads ${NUM_KV_HEAD}" -# export DATA_CACHE_PATH="${DATA_CACHE_PATH}" -if [[ -n "$DATA_CACHE_PATH" ]]; then - echo "Using DATA_CACHE_PATH: ${DATA_CACHE_PATH}" - EXTRA_ARGS="${EXTRA_ARGS} --data-cache-path ${DATA_CACHE_PATH}" +# export DATA_FILE_LIST="./chunks/10/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_10.txt" +export DOLMA_CHUNK_IDX="${DOLMA_CHUNK_IDX:-0}" +export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_20.txt" +# export DATA_FILE_LIST="./dolma_data_file_list-${DOLMA_CHUNK_IDX}-of-04.txt" + +NDOCS=$(wc -l < "${DATA_FILE_LIST}") +echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NDOCS} documents..." +export NDOCS="${NDOCS}" + +if [[ -z "${DATA_CACHE_PATH}" ]]; then + data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") + export DATA_CACHE_PATH="${HERE}/.cache/${data_file_list_stem}-index-cache" else - echo "Not using DATA_CACHE_PATH !!" + export DATA_CACHE_PATH="${DATA_CACHE_PATH}" + echo "CAUGHT DATA_CACHE_PATH: ${DATA_CACHE_PATH} from env !!" fi +mkdir -p "${DATA_CACHE_PATH}" + echo "++++++++++++++++++++++++++++++++++++++++++++++++++" echo "- WORLD_SIZE:${WORLD_SIZE}" echo "- NCCL: ${NCCL:-nccl}" @@ -72,7 +162,6 @@ echo "- MODEL_TYPE: ${MODEL_TYPE}" echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" echo "++++++++++++++++++++++++++++++++++++++++++++++++++" - # bash $LLM_DK_DIR/intel-extension-for-deepspeed/examples/gpt.sh $@ DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" @@ -177,6 +266,7 @@ run_cmd=" --accumulate-allreduce-grads-in-fp32 \ --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ --data-file-list ${DATA_FILE_LIST} \ + --data-cache-path ${DATA_CACHE_PATH} \ --num-workers 4 \ ${LLAMA_ARGS} \ ${EXTRA_ARGS} \ From bf536554cae05ee8929147c0fc276977f2760de0 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 21 Feb 2024 20:57:38 -0600 Subject: [PATCH 068/268] Remove `train_llama_alcf_chunk_00-of-20.sh` --- train_llama_alcf_chunk_00-of-20.sh | 60 ------------------------------ 1 file changed, 60 deletions(-) delete mode 100755 train_llama_alcf_chunk_00-of-20.sh diff --git a/train_llama_alcf_chunk_00-of-20.sh b/train_llama_alcf_chunk_00-of-20.sh deleted file mode 100755 index 46a00aea52..0000000000 --- a/train_llama_alcf_chunk_00-of-20.sh +++ /dev/null @@ -1,60 +0,0 @@ -#!/bin/bash --login -#PBS -l walltime=06:00:00 -#PBS -A argonne_tpc -#PBS -q prod -#PBS -l select=48 -#PBS -l filesystems=eagle:home - -cd "${PBS_O_WORKDIR}" || exit -module load conda/2023-10-04; conda activate base -if [[ ! -d ezpz ]]; then - git clone https://github.com/saforem2/ezpz -else - echo "Found ezpz!" -fi -source ezpz/src/ezpz/bin/savejobenv || exit -source ezpz/src/ezpz/bin/getjobenv || exit - -export PP=1 -export TP=2 - -export HEADS=32 -export NLAYERS=32 -export HIDDEN=4096 -export NUM_KV_HEAD=8 - -export ZERO_STAGE=2 -export MICRO_BATCH=8 -export GRAD_ACC_STEPS=1 -export SEQ=4096 -export DTYPE=fp16 - -export EVAL_ITERS=20 -export TRAIN_ITER=317892 -export SAVE_INTERVAL=200 -# export EVAL_INTERVAL=1000 - -export DATA_PATH="/eagle/datasets/dolma/data_Llama2Tokenizer/wiki-en-simple/" -export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/20/data_file_list_chunk_0_of_20.txt" -# export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select_5.txt" -# export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/40/data_file_list_chunk_0_of_40.txt" -# export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/data_file_list_chunk_0_of_20.txt" - -export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" - -export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" -export USE_ACTIVATION_CHECKPOINTING=1 ; -export EXTRA_ARGS="--use-flash-attn-v2 --num-key-value-heads ${NUM_KV_HEAD}" - -echo "++++++++++++++++++++++++++++++++++++++++++++++++++" -echo "- WORLD_SIZE:${WORLD_SIZE}" -echo "- NCCL: ${NCCL:-nccl}" -echo "- MODEL_TYPE: ${MODEL_TYPE}" -echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" -echo "++++++++++++++++++++++++++++++++++++++++++++++++++" - - # [ -n "${MODEL_TYPE}" ] && - EXEC="./set_params.sh" - OUTPUT="train-${MODEL_TYPE}-mbs-${MICRO_BATCH}-zs${ZERO_STAGE}-kvh${NUM_KV_HEAD}-$(tstamp).log" - - [ -f "${EXEC}" ] && bash "${EXEC}" "${LLAMA_ARGS}" "${EXTRA_ARGS}" |& tee "${OUTPUT}" From 28ba58faecae9bdd12f4f6363cec615370ff14d0 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 21 Feb 2024 20:57:50 -0600 Subject: [PATCH 069/268] Add `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 69 +++++++++++++++++++++++-------------- 1 file changed, 43 insertions(+), 26 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index 049d854f71..3143f2d69f 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -11,7 +11,7 @@ ezpz() { else echo "Found ezpz!" fi - echo "Using :snake: $(which python3) to install \`ezpz\`:" + echo "Using $(which python3) to install \`ezpz\`:" mkdir -p logs python3 -m pip install -e ezpz > ezpz-install.log 2>&1 source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit @@ -45,19 +45,39 @@ makeHostfiles() { # ------------------------------------------------- } +setupData() { + local cidx=$1 + # export DOLMA_CHUNK_IDX="${DOLMA_CHUNK_IDX:-0}" + # HERE=$(python3 -c 'import os; print(os.getcwd())') + export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/4/data_file_list_chunk_${cidx}_of_4.txt" + NDOCS=$(wc -l < "${DATA_FILE_LIST}") + export NDOCS="${NDOCS}" + if [[ -z "${DATA_CACHE_PATH}" ]]; then + data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") + export DATA_CACHE_PATH=".cache/${data_file_list_stem}-index-cache" + else + export DATA_CACHE_PATH="${DATA_CACHE_PATH}" + echo "CAUGHT DATA_CACHE_PATH: ${DATA_CACHE_PATH} from env !!" + fi + export DOLMA_CHUNK_IDX="${cidx}" + mkdir -p "${DATA_CACHE_PATH}" +} + # ==== SCRIPT START ======================================================== cd "${PBS_O_WORKDIR}" || exit module load conda/2023-10-04; conda activate base ezpz makeHostfiles +setupData "${DOLMA_CHUNK_IDX:-0}" +echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NDOCS} documents..." # ---- Parallelism Settings ---- export PP=${PP:-1} export TP=${TP:-2} # ------------------------------ -export HERE=$(python3 -c 'import os; print(os.getcwd())') +HERE=$(python3 -c 'import os; print(os.getcwd())') HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} @@ -78,10 +98,21 @@ export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) # --------------------------------------------- -export EVAL_ITERS=${EVAL_ITERS:-20} -export TRAIN_ITER=${TRAIN_ITER:-317892} +if [[ "${DOLMA_CHUNK_IDX}" == 0 ]]; then + TRAIN_ITER=78739 +elif [[ "${DOLMA_CHUNK_IDX}" == 1 ]]; then + TRAIN_ITER=81008 +elif [[ "${DOLMA_CHUNK_IDX}" == 2 ]]; then + TRAIN_ITER=79591 +elif [[ "${DOLMA_CHUNK_IDX}" == 3 ]]; then + TRAIN_ITER=78552 +else + echo "Unknown DOLMA_CHUNK_IDX: ${DOLMA_CHUNK_IDX}" + exit +fi +# export TRAIN_ITER=${TRAIN_ITER:-317892} + export SAVE_INTERVAL=${SAVE_INTERVAL:-200} -export EVAL_INTERVAL=${EVAL_INTERVAL:-50000} export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} @@ -134,27 +165,13 @@ export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings # echo "Using DATA_CACHE_PATH: ${DATA_CACHE_PATH}" # fi + export EXTRA_ARGS="--use-flash-attn-v2 --num-key-value-heads ${NUM_KV_HEAD}" # export DATA_FILE_LIST="./chunks/10/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_10.txt" -export DOLMA_CHUNK_IDX="${DOLMA_CHUNK_IDX:-0}" -export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_20.txt" +# export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_20.txt" # export DATA_FILE_LIST="./dolma_data_file_list-${DOLMA_CHUNK_IDX}-of-04.txt" -NDOCS=$(wc -l < "${DATA_FILE_LIST}") -echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NDOCS} documents..." -export NDOCS="${NDOCS}" - -if [[ -z "${DATA_CACHE_PATH}" ]]; then - data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") - export DATA_CACHE_PATH="${HERE}/.cache/${data_file_list_stem}-index-cache" -else - export DATA_CACHE_PATH="${DATA_CACHE_PATH}" - echo "CAUGHT DATA_CACHE_PATH: ${DATA_CACHE_PATH} from env !!" -fi - -mkdir -p "${DATA_CACHE_PATH}" - echo "++++++++++++++++++++++++++++++++++++++++++++++++++" echo "- WORLD_SIZE:${WORLD_SIZE}" echo "- NCCL: ${NCCL:-nccl}" @@ -229,12 +246,17 @@ EXEC="./pretrain_gpt_alcf.py" # --merge-file $MERGE_FILE \ # --lr-decay-iters 320000 \ # --num-workers 0 \ + # --eval-iters ${EVAL_ITERS} \ + # --eval-interval ${EVAL_INTERVAL} \ + # --lr-warmup-iters 5000 \ + # --lr-decay-iters 10000 \ run_cmd=" deepspeed $launcher ${EXEC} \ --tensor-model-parallel-size $TP \ --pipeline-model-parallel-size $PP \ --num-layers $NLAYERS \ --hidden-size $HIDDEN \ + --ffn-hidden-size 11008 \ --num-attention-heads $HEADS \ --seq-length $SEQ \ --max-position-embeddings $SEQ \ @@ -242,14 +264,9 @@ run_cmd=" --global-batch-size $GLOBAL_BATCH \ --train-iters $TRAIN_ITER \ --lr ${LR} \ - --lr-warmup-iters 5000 \ - --lr-decay-iters 10000 \ - --ffn-hidden-size 11008 \ --lr-decay-style cosine \ --data-impl mmap \ --log-interval 1 \ - --eval-iters ${EVAL_ITERS} \ - --eval-interval ${EVAL_INTERVAL} \ --save-interval ${SAVE_INTERVAL} \ --split 90,5,5 \ --$DTYPE \ From 7f9af8dd5051838761aa2fe1cdaf37054cb291ab Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 23 Feb 2024 08:19:54 -0600 Subject: [PATCH 070/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 177 +++++++++++++++++++++++++----------- 1 file changed, 125 insertions(+), 52 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index 3143f2d69f..904dc5d6fd 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -4,6 +4,42 @@ #PBS -q prod #PBS -l select=48 #PBS -l filesystems=eagle:home +# +set +x +loadCondaEnv() { + if [[ "${CONDA_EXE}" ]]; then + echo "Already inside ${CONDA_EXE}, exiting!" + else + MODULE_STR="$1" + module load "conda/${MODULE_STR}" + conda activate base + fi +} + +setupVenv() { + VENV_DIR="$1" + if [[ -d "${VENV_DIR}" ]]; then + echo "Found venv at: ${VENV_DIR}" + source "${VENV_DIR}/bin/activate" + else + echo "Skipping setupVenv() on $(hostname)" + fi +} + +setupPython() { + local conda_date=$1 + local venv_path=$2 + if [[ "${CONDA_EXE}" ]]; then + echo "Caught CONDA_EXE: ${CONDA_EXE}" + else + loadCondaEnv "${conda_date}" + fi + if [[ "${VIRTUAL_ENV}" ]]; then + echo "Caught VIRTUAL_ENV: ${VIRTUAL_ENV}" + else + setupVenv "${venv_path}" + fi +} ezpz() { if [[ ! -d ezpz ]]; then @@ -11,9 +47,13 @@ ezpz() { else echo "Found ezpz!" fi - echo "Using $(which python3) to install \`ezpz\`:" - mkdir -p logs - python3 -m pip install -e ezpz > ezpz-install.log 2>&1 + if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then + echo "Has ezpz installed. Nothing to do." + else + echo "Does not have ezpz installed. Installing..." + echo "Using $(which python3) to install \`ezpz\`:" + python3 -m pip install -e ezpz > ezpz-install.log 2>&1 + fi source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit source ezpz/src/ezpz/bin/getjobenv || exit } @@ -46,38 +86,68 @@ makeHostfiles() { } setupData() { - local cidx=$1 + cidx=$1 + echo "Caught DOLMA_CHUNK_IDX: ${cidx} !!" # export DOLMA_CHUNK_IDX="${DOLMA_CHUNK_IDX:-0}" # HERE=$(python3 -c 'import os; print(os.getcwd())') - export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/4/data_file_list_chunk_${cidx}_of_4.txt" - NDOCS=$(wc -l < "${DATA_FILE_LIST}") + # export DATA_FILE_LIST="/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/chunks/4/data_file_list_chunk_${cidx}_of_4.txt" + # export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select.txt" + # export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/4/data_file_list_chunk_${cidx}_of_4.txt" + # export DATA_FILE_LIST="./chunks/4/data_file_list_chunk_${cidx}_of_4.txt" + # export DATA_FILE_LIST="./chunks/4/data_file_list_chunk_${cidx}_of_4.txt" + # export DATA_FILE_LIST="./dolma_data_file_list-${cidx}-of-4.txt" + export DATA_FILE_LIST="${DATA_FILE_LIST:-"./dolma-shuf-chunk-${cidx}-of-4.txt"}" + echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST}" + # [ -f "$DATA_FILE_LIST" ] || exit + NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" export NDOCS="${NDOCS}" - if [[ -z "${DATA_CACHE_PATH}" ]]; then - data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") - export DATA_CACHE_PATH=".cache/${data_file_list_stem}-index-cache" - else - export DATA_CACHE_PATH="${DATA_CACHE_PATH}" - echo "CAUGHT DATA_CACHE_PATH: ${DATA_CACHE_PATH} from env !!" - fi + # if [[ -z "${DATA_CACHE_PATH}" ]]; then + # else + # echo "CAUGHT DATA_CACHE_PATH: ${DATA_CACHE_PATH} from env !!" + # DATA_CACHE_PATH="${DATA_CACHE_PATH}" + # fi + data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") export DOLMA_CHUNK_IDX="${cidx}" + export DATA_FILE_LIST_STEM="${data_file_list_stem}" + export DATA_CACHE_PATH=".cache/${data_file_list_stem}/index-cache" mkdir -p "${DATA_CACHE_PATH}" } # ==== SCRIPT START ======================================================== -cd "${PBS_O_WORKDIR}" || exit +# cd "${PBS_O_WORKDIR}" || exit +HERE=$(python3 -c 'import os; print(os.getcwd())') +# if [[ -z "${CONDA_EXE}" ]]; then module load conda/2023-10-04; conda activate base +# else +# echo "Caught CONDA_EXE = ${CONDA_EXE} from env" +# fi + +# if [[ -z "${VIRTUAL_ENV}" ]]; then +# source /home/foremans/polaris/projects/argonne-lcf/Megatron-DeepSpeed/venvs/polaris/2023-10-04/bin/activate || exit +# source ~/venvs/polaris/2023-10-04/bin/activate || exit +# else +# echo "Caught VIRTUAL_ENV = ${VIRTUAL_ENV} from env" +# fi +# if [[ "${VIRTUAL_ENV}" ]]; then +# echo "Caught virtual env from environment, using ${VIRTUAL_ENV}" +# else +echo "Using $(which python3)" + ezpz makeHostfiles setupData "${DOLMA_CHUNK_IDX:-0}" +# NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" +# export NDOCS="${NDOCS}" echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NDOCS} documents..." # ---- Parallelism Settings ---- -export PP=${PP:-1} -export TP=${TP:-2} +PP=${PP:-1} +TP=${TP:-2} +export PP="${PP}" +export TP="${TP}" # ------------------------------ -HERE=$(python3 -c 'import os; print(os.getcwd())') HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} @@ -92,11 +162,12 @@ export NUM_KV_HEAD=${NUM_KV_HEAD:-8} export LR=${LR:-0.00015} export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 -export ZERO_STAGE=${ZERO_STAGE:-1} +export ZERO_STAGE=${ZERO_STAGE:-2} export MICRO_BATCH=${MICRO_BATCH:-8} export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) # --------------------------------------------- +export TOKENIZER_MODEL="${TOKENIZER_MODEL:-"/eagle/datasets/dolma/utils/tokenizer.model"}" if [[ "${DOLMA_CHUNK_IDX}" == 0 ]]; then TRAIN_ITER=78739 @@ -107,9 +178,14 @@ elif [[ "${DOLMA_CHUNK_IDX}" == 2 ]]; then elif [[ "${DOLMA_CHUNK_IDX}" == 3 ]]; then TRAIN_ITER=78552 else - echo "Unknown DOLMA_CHUNK_IDX: ${DOLMA_CHUNK_IDX}" - exit + echo "caught DOLMA_CHUNK_IDX=${DOLMA_CHUNK_IDX}" + TRAIN_ITER="${TRAIN_ITER:-320000}" + echo "Setting TRAIN_ITER=${TRAIN_ITER}" + # echo "Unknown DOLMA_CHUNK_IDX: ${DOLMA_CHUNK_IDX}" fi + +export EVAL_ITERS="${EVAL_ITERS:-10}" +export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" # export TRAIN_ITER=${TRAIN_ITER:-317892} export SAVE_INTERVAL=${SAVE_INTERVAL:-200} @@ -166,7 +242,7 @@ export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings # fi -export EXTRA_ARGS="--use-flash-attn-v2 --num-key-value-heads ${NUM_KV_HEAD}" +# export EXTRA_ARGS="--use-flash-attn-v2 --num-key-value-heads ${NUM_KV_HEAD}" # export DATA_FILE_LIST="./chunks/10/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_10.txt" # export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_20.txt" @@ -182,23 +258,17 @@ echo "++++++++++++++++++++++++++++++++++++++++++++++++++" # bash $LLM_DK_DIR/intel-extension-for-deepspeed/examples/gpt.sh $@ DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" -bash ./generate_config.sh "${DS_CONFIG}" || exit 1 +bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit 1 -OUTPUT_PREFIX="logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" +OUTPUT_PREFIX="${HERE}/logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" # OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} OUTPUT_DIR="${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" mkdir -p "${OUTPUT_DIR}" echo "!!!Please see logs at ${OUTPUT_DIR}" -# Hostfile path -hostfile_deepspeed=./hostfile_deepspeed -hostfile_mpich=./hostfile_mpich -cat "$PBS_NODEFILE" > hostfile_mpich -cat "$PBS_NODEFILE" > hostfile_deepspeed ; sed -e 's/$/ slots=4/' -i hostfile_deepspeed - ds_args=" " ds_args=" --deepspeed ${ds_args}" -if [ "$PP" == 1 ]; then +if [[ $PP == 1 ]]; then ds_args=" --no-pipeline-parallel ${ds_args}" fi ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" @@ -237,7 +307,7 @@ else fi NCCL=${NCCL:-nccl} -EXEC="./pretrain_gpt_alcf.py" +EXEC="pretrain_gpt_alcf.py" # MODEL=LLAMA_7B # OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_tp${TP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} @@ -246,51 +316,54 @@ EXEC="./pretrain_gpt_alcf.py" # --merge-file $MERGE_FILE \ # --lr-decay-iters 320000 \ # --num-workers 0 \ - # --eval-iters ${EVAL_ITERS} \ - # --eval-interval ${EVAL_INTERVAL} \ # --lr-warmup-iters 5000 \ # --lr-decay-iters 10000 \ + # --num-workers 4 \ + # launch python3 ${EXEC} \ run_cmd=" deepspeed $launcher ${EXEC} \ - --tensor-model-parallel-size $TP \ - --pipeline-model-parallel-size $PP \ + --$DTYPE \ + --lr ${LR} \ + --log-interval 1 \ + --seq-length $SEQ \ --num-layers $NLAYERS \ --hidden-size $HIDDEN \ --ffn-hidden-size 11008 \ + --train-iters $TRAIN_ITER \ + --eval-iters ${EVAL_ITERS} \ + --distributed-backend $NCCL \ --num-attention-heads $HEADS \ - --seq-length $SEQ \ --max-position-embeddings $SEQ \ --micro-batch-size $MICRO_BATCH \ - --global-batch-size $GLOBAL_BATCH \ - --train-iters $TRAIN_ITER \ - --lr ${LR} \ - --lr-decay-style cosine \ - --data-impl mmap \ - --log-interval 1 \ --save-interval ${SAVE_INTERVAL} \ + --eval-interval ${EVAL_INTERVAL} \ + --tensor-model-parallel-size $TP \ + --global-batch-size $GLOBAL_BATCH \ + --pipeline-model-parallel-size $PP \ + --data-file-list ${DATA_FILE_LIST} \ + --load checkpoints/${OUTPUT_PREFIX} \ + --save checkpoints/${OUTPUT_PREFIX} \ + --data-cache-path ${DATA_CACHE_PATH} \ + --num-key-value-heads ${NUM_KV_HEAD} \ + --tokenizer-model ${TOKENIZER_MODEL} \ --split 90,5,5 \ - --$DTYPE \ - $ds_args \ + --data-impl mmap \ --no-masked-softmax-fusion \ --no-bias-gelu-fusion \ --no-bias-dropout-fusion \ --no-gradient-accumulation-fusion \ - --distributed-backend $NCCL \ + --use-flash-attn-v2 \ + --lr-decay-style cosine \ --tokenizer-type Llama2Tokenizer \ - --save checkpoints/${OUTPUT_PREFIX} \ - --load checkpoints/${OUTPUT_PREFIX} \ --use-checkpoint-opt_param-scheduler \ --accumulate-allreduce-grads-in-fp32 \ - --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ - --data-file-list ${DATA_FILE_LIST} \ - --data-cache-path ${DATA_CACHE_PATH} \ - --num-workers 4 \ + $ds_args \ ${LLAMA_ARGS} \ - ${EXTRA_ARGS} \ ${gpt_args[*]} \ $custom_args \ |& tee $OUTPUT_DIR/output.log " + # ${EXTRA_ARGS} \ echo "Using $(which deepspeed)" ds_report From 7b00ac4a1351d81befee1303bd89c2d143a522f7 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 23 Feb 2024 15:57:35 -0600 Subject: [PATCH 071/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 315 ++++++++++++------------------------ 1 file changed, 100 insertions(+), 215 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index 904dc5d6fd..7f96082665 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -4,249 +4,85 @@ #PBS -q prod #PBS -l select=48 #PBS -l filesystems=eagle:home -# -set +x -loadCondaEnv() { - if [[ "${CONDA_EXE}" ]]; then - echo "Already inside ${CONDA_EXE}, exiting!" - else - MODULE_STR="$1" - module load "conda/${MODULE_STR}" - conda activate base - fi -} - -setupVenv() { - VENV_DIR="$1" - if [[ -d "${VENV_DIR}" ]]; then - echo "Found venv at: ${VENV_DIR}" - source "${VENV_DIR}/bin/activate" - else - echo "Skipping setupVenv() on $(hostname)" - fi -} -setupPython() { - local conda_date=$1 - local venv_path=$2 - if [[ "${CONDA_EXE}" ]]; then - echo "Caught CONDA_EXE: ${CONDA_EXE}" +function sourceFile() { + fp="$1" + echo "source-ing ${fp}" + if [[ -f "${fp}" ]]; then + # shellcheck source="${fp}" + source "${fp}" else - loadCondaEnv "${conda_date}" + echo "ERROR: UNABLE TO SOURCE ${fp}" fi - if [[ "${VIRTUAL_ENV}" ]]; then - echo "Caught VIRTUAL_ENV: ${VIRTUAL_ENV}" - else - setupVenv "${venv_path}" - fi -} - -ezpz() { - if [[ ! -d ezpz ]]; then - git clone https://github.com/saforem2/ezpz - else - echo "Found ezpz!" - fi - if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then - echo "Has ezpz installed. Nothing to do." - else - echo "Does not have ezpz installed. Installing..." - echo "Using $(which python3) to install \`ezpz\`:" - python3 -m pip install -e ezpz > ezpz-install.log 2>&1 - fi - source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit - source ezpz/src/ezpz/bin/getjobenv || exit -} - -makeHostfiles() { - GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') - export GPUS_PER_NODE="${GPUS_PER_NODE}" - # ---- Make MPICH hostfile ---------------- - export hostfile_mpich=hostfile_mpich - cat "$PBS_NODEFILE" > "${hostfile_mpich}" - # ---- Make DeepSpeed hostfile ------------------- - export hostfile_deepspeed=hostfile_deepspeed - cat "$PBS_NODEFILE" > "${hostfile_deepspeed}" - sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" - { - echo "PATH=${PATH}" ; - echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" ; - echo "http_proxy=${http_proxy}" ; - echo "https_pro]xy=${https_proxy}" ; - echo "CFLAGS=${CFLAGS}" ; - echo "PYTHONUSERBASE=$PYTHONUSERBASE" ; - } > .deepspeed_env - # echo "PATH=${PATH}" > .deepspeed_env - # echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> .deepspeed_env - # echo "http_proxy=${http_proxy}" >> .deepspeed_env - # echo "https_proxy=${https_proxy}" >> .deepspeed_env - # echo "CFLAGS=${CFLAGS}" >> .d eepspeed_env - # echo "PYTHONUSERBASE=$PYTHONUSERBASE" >> .deepspeed_env - # ------------------------------------------------- -} - -setupData() { - cidx=$1 - echo "Caught DOLMA_CHUNK_IDX: ${cidx} !!" - # export DOLMA_CHUNK_IDX="${DOLMA_CHUNK_IDX:-0}" - # HERE=$(python3 -c 'import os; print(os.getcwd())') - # export DATA_FILE_LIST="/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/chunks/4/data_file_list_chunk_${cidx}_of_4.txt" - # export DATA_FILE_LIST="/eagle/datasets/dolma/data_file_list_select.txt" - # export DATA_FILE_LIST="/eagle/datasets/dolma/chunks/4/data_file_list_chunk_${cidx}_of_4.txt" - # export DATA_FILE_LIST="./chunks/4/data_file_list_chunk_${cidx}_of_4.txt" - # export DATA_FILE_LIST="./chunks/4/data_file_list_chunk_${cidx}_of_4.txt" - # export DATA_FILE_LIST="./dolma_data_file_list-${cidx}-of-4.txt" - export DATA_FILE_LIST="${DATA_FILE_LIST:-"./dolma-shuf-chunk-${cidx}-of-4.txt"}" - echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST}" - # [ -f "$DATA_FILE_LIST" ] || exit - NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" - export NDOCS="${NDOCS}" - # if [[ -z "${DATA_CACHE_PATH}" ]]; then - # else - # echo "CAUGHT DATA_CACHE_PATH: ${DATA_CACHE_PATH} from env !!" - # DATA_CACHE_PATH="${DATA_CACHE_PATH}" - # fi - data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") - export DOLMA_CHUNK_IDX="${cidx}" - export DATA_FILE_LIST_STEM="${data_file_list_stem}" - export DATA_CACHE_PATH=".cache/${data_file_list_stem}/index-cache" - mkdir -p "${DATA_CACHE_PATH}" } - -# ==== SCRIPT START ======================================================== -# cd "${PBS_O_WORKDIR}" || exit +# +++++++++++++++ SCRIPT START +++++++++++++++++++++++ +# ---- source ./helpers_alcf.sh --------------------- HERE=$(python3 -c 'import os; print(os.getcwd())') -# if [[ -z "${CONDA_EXE}" ]]; then -module load conda/2023-10-04; conda activate base -# else -# echo "Caught CONDA_EXE = ${CONDA_EXE} from env" -# fi +sourceFile "${HERE}/helpers_alcf.sh" || exit -# if [[ -z "${VIRTUAL_ENV}" ]]; then -# source /home/foremans/polaris/projects/argonne-lcf/Megatron-DeepSpeed/venvs/polaris/2023-10-04/bin/activate || exit -# source ~/venvs/polaris/2023-10-04/bin/activate || exit -# else -# echo "Caught VIRTUAL_ENV = ${VIRTUAL_ENV} from env" -# fi -# if [[ "${VIRTUAL_ENV}" ]]; then -# echo "Caught virtual env from environment, using ${VIRTUAL_ENV}" -# else +# ---- load conda ----------------------------------- +module load conda/2023-10-04; conda activate base echo "Using $(which python3)" +# ---- fns from ./helpers_alcf.sh ------------------- ezpz makeHostfiles -setupData "${DOLMA_CHUNK_IDX:-0}" -# NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" -# export NDOCS="${NDOCS}" -echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NDOCS} documents..." +saveDSenv +# setupData "${DOLMA_CHUNK_IDX:-00}" +# export DOLMA_CHUNK_IDX="${DOLMA_CHUNK_IDX:-0}" +# +# ---- DATA SETUP ------------------------------------ +DATA_FILE_LIST="./data_file_list_shuf_debug.txt" && export DATA_FILE_LIST="${DATA_FILE_LIST}" +NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" +WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" && export WEIGHT_SUM="${WEIGHT_SUM}" +DFL_STEM=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") && export DFL_STEM="${DFL_STEM}" +dcp="${HERE}/.cache/${DFL_STEM}-index-cache" +DATA_CACHE_PATH="${DATA_CACHE_PATH:-${dcp}}" && export DATA_CACHE_PATH="${DATA_CACHE_PATH}" +mkdir -p "${DATA_CACHE_PATH}" +if [[ -n "${DOLMA_CHUNK_IDX}" ]]; then + echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NDOCS} documents..." +else + echo "Using NDOCS=${NDOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" +fi +echo "DOCUMENT WEIGHT_SUM: ${WEIGHT_SUM}" +# ---------------------------------------------------- -# ---- Parallelism Settings ---- +# ---- Parallelism Settings -------------------------- PP=${PP:-1} TP=${TP:-2} export PP="${PP}" export TP="${TP}" -# ------------------------------ - -HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" +export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} +# ---------------------------------------------------- -# ---- Llama2 7B Config ----------------------- +# ---- Llama2 7B Config ------------------------------ export HEADS=${HEADS:-32} export NLAYERS=${NLAYERS:-32} export HIDDEN=${HIDDEN:-4096} export NUM_KV_HEAD=${NUM_KV_HEAD:-8} -# --------------------------------------------- +# ---------------------------------------------------- -# ---- Run Settings ------------------------------------------ +# ---- Run Settings ---------------------------------- export LR=${LR:-0.00015} export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 export ZERO_STAGE=${ZERO_STAGE:-2} export MICRO_BATCH=${MICRO_BATCH:-8} export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} -export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) -# --------------------------------------------- export TOKENIZER_MODEL="${TOKENIZER_MODEL:-"/eagle/datasets/dolma/utils/tokenizer.model"}" - -if [[ "${DOLMA_CHUNK_IDX}" == 0 ]]; then - TRAIN_ITER=78739 -elif [[ "${DOLMA_CHUNK_IDX}" == 1 ]]; then - TRAIN_ITER=81008 -elif [[ "${DOLMA_CHUNK_IDX}" == 2 ]]; then - TRAIN_ITER=79591 -elif [[ "${DOLMA_CHUNK_IDX}" == 3 ]]; then - TRAIN_ITER=78552 -else - echo "caught DOLMA_CHUNK_IDX=${DOLMA_CHUNK_IDX}" - TRAIN_ITER="${TRAIN_ITER:-320000}" - echo "Setting TRAIN_ITER=${TRAIN_ITER}" - # echo "Unknown DOLMA_CHUNK_IDX: ${DOLMA_CHUNK_IDX}" -fi - +export TRAIN_ITER=${TRAIN_ITER:-317892} +# export TRAIN_ITER="${TRAIN_ITER:-320000}" export EVAL_ITERS="${EVAL_ITERS:-10}" export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" -# export TRAIN_ITER=${TRAIN_ITER:-317892} - export SAVE_INTERVAL=${SAVE_INTERVAL:-200} export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} - +export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" -# export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/40/data_file_list_chunk_0_of_40.txt" -# export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/10/data_file_list_chunk_0_of_10.txt" -# - -# export DOLMA_CHUNK_00_of_10="./chunks/10/data_file_list_chunk_00_of_10.txt" # 762 documents (lines) -# export DOLMA_CHUNK_01_of_10="./chunks/10/data_file_list_chunk_01_of_10.txt" # 722 -# export DOLMA_CHUNK_02_of_10="./chunks/10/data_file_list_chunk_02_of_10.txt" # 727 -# export DOLMA_CHUNK_03_of_10="./chunks/10/data_file_list_chunk_03_of_10.txt" # 707 -# export DOLMA_CHUNK_04_of_10="./chunks/10/data_file_list_chunk_04_of_10.txt" # 744 -# export DOLMA_CHUNK_05_of_10="./chunks/10/data_file_list_chunk_05_of_10.txt" # 766 -# export DOLMA_CHUNK_06_of_10="./chunks/10/data_file_list_chunk_06_of_10.txt" # 730 -# export DOLMA_CHUNK_07_of_10="./chunks/10/data_file_list_chunk_07_of_10.txt" # 759 -# export DOLMA_CHUNK_08_of_10="./chunks/10/data_file_list_chunk_08_of_10.txt" # 777 -# export DOLMA_CHUNK_09_of_10="./chunks/10/data_file_list_chunk_09_of_10.txt" # 752 - -# -# export DOLMA_CHUNK_00_of_04="./dolma_data_file_list-00-of-04.txt" # 1860 documents (lines) -# export DOLMA_CHUNK_01_of_04="./dolma_data_file_list-01-of-04.txt" # 1860 documents (lines) -# export DOLMA_CHUNK_02_of_04="./dolma_data_file_list-02-of-04.txt" # 1860 documents (lines) -# export DOLMA_CHUNK_03_of_04="./dolma_data_file_list-03-of-04.txt" # 1860 documents (lines) -# export DOLMA_CHUNK_04_of_04="./dolma_data_file_list-04-of-04.txt" # 6 documents (lines) - - - -# if [[ -n "$DEBUG_RUN" ]]; then -# # echo "Using LAST DOLMA CHUNK {09 / 10} with ${NDOCS} documents..." -# export DATA_FILE_LIST=${DATA_FILE_LIST:-${DOLMA_CHUNK_09_of_10}} -# # export ndocs=$(wc -l < "${DATA_FILE_LIST}") -# else -# # export fname="./chunks/10/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_10.txt" -# # export fname="${DOLMA_CHUNK_!{DOLMA_CHUNK_IDX}_of_10}" -# # export DATA_FILE_LIST="${DATA_FILE_LIST:-${DOLMA_CHUNK_00_of_10}}" -# fi -# export ndocs -# export DATA_FILE_LIST="${DATA_FILE_LIST}" -# export DATA_FILE_LIST="./dolma_data_file_list-00-of-04.txt" -# export DATA_FILE_LIST="./dolma-chunk-00-of-40.txt" -# -# bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit - -# export DATA_CACHE_PATH="${DATA_CACHE_PATH}" -# if [[ -z "$DATA_CACHE_PATH" ]]; then -# echo "Not using DATA_CACHE_PATH !!" -# else -# echo "Using DATA_CACHE_PATH: ${DATA_CACHE_PATH}" -# fi - - -# export EXTRA_ARGS="--use-flash-attn-v2 --num-key-value-heads ${NUM_KV_HEAD}" - -# export DATA_FILE_LIST="./chunks/10/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_10.txt" -# export DATA_FILE_LIST="/lus/eagle/projects/datasets/dolma/chunks/data_file_list_chunk_${DOLMA_CHUNK_IDX}_of_20.txt" -# export DATA_FILE_LIST="./dolma_data_file_list-${DOLMA_CHUNK_IDX}-of-04.txt" +# ---------------------------------------------------- echo "++++++++++++++++++++++++++++++++++++++++++++++++++" echo "- WORLD_SIZE:${WORLD_SIZE}" @@ -255,17 +91,65 @@ echo "- MODEL_TYPE: ${MODEL_TYPE}" echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" echo "++++++++++++++++++++++++++++++++++++++++++++++++++" -# bash $LLM_DK_DIR/intel-extension-for-deepspeed/examples/gpt.sh $@ +# if [[ "${DOLMA_CHUNK_IDX}" == 0 ]]; then +# TRAIN_ITER=78739 +# elif [[ "${DOLMA_CHUNK_IDX}" == 1 ]]; then +# TRAIN_ITER=81008 +# elif [[ "${DOLMA_CHUNK_IDX}" == 2 ]]; then +# TRAIN_ITER=79591 +# elif [[ "${DOLMA_CHUNK_IDX}" == 3 ]]; then +# TRAIN_ITER=78552 +# else +# echo "caught DOLMA_CHUNK_IDX=${DOLMA_CHUNK_IDX}" +# TRAIN_ITER="${TRAIN_ITER:-320000}" +# echo "Setting TRAIN_ITER=${TRAIN_ITER}" +# # echo "Unknown DOLMA_CHUNK_IDX: ${DOLMA_CHUNK_IDX}" +# fi +# +++++NOTES ++++++++++++++++++++++++++++++++++++++++++++++++++ +# XXX: +# - need to merge *.json files +# - Can we create indices on a per-dataset basis? +# (i.e. one for common-crawl, one for stack-code, etc.) +# - Aggregate `stack-code/**/{*.bin,*.idx}` +# +# - Given: {f1.bin,f2.bin,...,fn.bin} +# - tot_tokens = 0 +# - agg = [] +# - Start: +# - read: f1.bin +# - tot_tokens += sum(tokens(f1.bin)) +# - if tot_tokens < needed_tokens: +# - agg.append(f1.bin) +# - else: +# + +# TODO: +# - StackExchange ~ 500B total, using 80% ~ 400B tokens +# - figure out how to deal with MANY small files (e.g. stack-code) +# - Add logic for determining `train_iters` dynamically from `data-file-list` +# (which specifies a single _chunk_) +# - get script from Varuni +# - should: +# - take in a `data_file_list.txt` +# - return number of training iterations +# +# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + +# ---- Build DeepSpeed Config --------------------------------- DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit 1 +# ------------------------------------------------------------- +# ---- Specify output location -------------------------------- OUTPUT_PREFIX="${HERE}/logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" # OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} OUTPUT_DIR="${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" mkdir -p "${OUTPUT_DIR}" echo "!!!Please see logs at ${OUTPUT_DIR}" + +# ---- Setup DeepSpeed arguments -------------------------------- ds_args=" " ds_args=" --deepspeed ${ds_args}" if [[ $PP == 1 ]]; then @@ -280,9 +164,12 @@ if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then # --checkpoint-activations \ # --deepspeed-activation-checkpointing fi +# --------------------------------------------------------------- gpt_args=() +# we are now using activation checkpoint provided by megatron, see below. +# ds_args=" --deepspeed-activation-checkpointing ${ds_args}" if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" gpt_args+=( @@ -290,28 +177,26 @@ if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then "--checkpoint-num-layers 1" ) fi -# we are now using activation checkpoint provided by megatron, see below. -# ds_args=" --deepspeed-activation-checkpointing ${ds_args}" -# NUM_KV_HEADS="${NUM_KV_HEADS:-0}" -# if [[ $NUM_KV_HEADS -]] # take custom args custom_args=" $@" # launcher setting +hfds="${HERE}/hostfile_deepspeed" +hfmpi="${HERE}/hostfile_mpich" +[ -f "$hfds" ] || exit +[ -f "$hfmpi" ] || exit + LAUNCHER=${LAUNCHER:-MPICH} if [[ $LAUNCHER == "deepspeed" ]]; then launcher="" else - launcher="--force_multi --hostfile $hostfile_deepspeed --launcher=${LAUNCHER} --launcher_args='-hostfile ${hostfile_mpich}'" + launcher="--force_multi --hostfile $hfds --launcher=${LAUNCHER} --launcher_args='-hostfile ${hfmpi}'" fi NCCL=${NCCL:-nccl} EXEC="pretrain_gpt_alcf.py" -# MODEL=LLAMA_7B -# OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_tp${TP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} - # --vocab-file $VOCAB_FILE \ # --merge-file $MERGE_FILE \ # --lr-decay-iters 320000 \ From 9a3688f05f5d5588fd5bb98adfe3fba1c04aa192 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 23 Feb 2024 15:57:46 -0600 Subject: [PATCH 072/268] Add `helpers_alcf.sh` --- helpers_alcf.sh | 80 +++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 80 insertions(+) create mode 100644 helpers_alcf.sh diff --git a/helpers_alcf.sh b/helpers_alcf.sh new file mode 100644 index 0000000000..b91000a67c --- /dev/null +++ b/helpers_alcf.sh @@ -0,0 +1,80 @@ +#!/bin/bash --login + +ezpz() { + if [[ ! -d ezpz ]]; then + git clone https://github.com/saforem2/ezpz + else + echo "Found ezpz!" + fi + if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then + echo "Has ezpz installed. Nothing to do." + else + echo "Does not have ezpz installed. Installing..." + echo "Using $(which python3) to install \`ezpz\`:" + python3 -m pip install -e ezpz > ezpz-install.log 2>&1 + fi + source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit + source ezpz/src/ezpz/bin/getjobenv || exit +} + +saveDSenv() { + echo "Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env" + { + echo "PATH=${PATH}" ; + echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" ; + echo "http_proxy=${http_proxy}" ; + echo "https_proxy=${https_proxy}" ; + echo "CFLAGS=${CFLAGS}" ; + echo "PYTHONUSERBASE=$PYTHONUSERBASE" ; + } > .deepspeed_env +} + +makeHostfiles() { + GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') + export GPUS_PER_NODE="${GPUS_PER_NODE}" + # ---- Make MPICH hostfile ---------------- + export hostfile_mpich=hostfile_mpich + cat "$PBS_NODEFILE" > "${hostfile_mpich}" + # ---- Make DeepSpeed hostfile ------------------- + export hostfile_deepspeed=hostfile_deepspeed + cat "$PBS_NODEFILE" > "${hostfile_deepspeed}" + sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" +} + +sumWeights() { + local file_list=$1 + weights=$(cat "${file_list}" | awk '{print $1}' | tr '\n' '\ ,\ ' | sed 's/^/[/g' | sed 's/$/]/g' | tr '\ ' "\,\ ") + # weights=$(echo "$weights" | tr ",]" "]") + # echo "weights: $weights" + python3 -c "import numpy as np; print(np.sum(${weights}))" +} + +sumFiles() { + local rd=$1 + for f in $("${rd}/*.txt"); do + ws=$(sumWeights "${rd}/${f}") + echo "sum($f.weights)=${ws}" + done +} + +setupData() { + cidx=$1 + echo "Caught DOLMA_CHUNK_IDX: ${cidx} !!" + dfl="./chunks-reweighted/10/data_file_list_chunk_${cidx}_of_10.txt" + if [[ -z "${DATA_FILE_LIST}" ]]; then + DATA_FILE_LIST="${dfl}" + else + echo "Caught DATA_FILE_LIST: ${DATA_FILE_LIST} from ENV!!" + fi + NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" + WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" + export WEIGHT_SUM="${WEIGHT_SUM}" + export NDOCS="${NDOCS}" + echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST} with ${NDOCS} documents" + echo "WEIGHT SUM: ${WEIGHT_SUM}" + data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") + export DOLMA_CHUNK_IDX="${cidx}" + export DATA_FILE_LIST_STEM="${data_file_list_stem}" + export DATA_CACHE_PATH=".cache/${data_file_list_stem}/index-cache" + mkdir -p "${DATA_CACHE_PATH}" +} From 5cfa5569ec9672128b6227e66ee9a15146389dea Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Sat, 24 Feb 2024 16:59:39 -0600 Subject: [PATCH 073/268] removed unnecessary setup for master_port --- llama_alcf.sh | 7 ++++--- pretrain_gpt_alcf.py | 6 +++--- 2 files changed, 7 insertions(+), 6 deletions(-) diff --git a/llama_alcf.sh b/llama_alcf.sh index dcfa41d109..0ca7cb78bb 100755 --- a/llama_alcf.sh +++ b/llama_alcf.sh @@ -2,7 +2,7 @@ #PBS -l walltime=0:30:00 #PBS -A datascience #PBS -q debug-scaling -#PBS -l select=6 +#PBS -l select=2 #PBS -l filesystems=eagle:grand:home export PPN=4 export MD=/home/hzheng/ALCF-Megatron-DeepSpeed @@ -20,7 +20,8 @@ export SP=$((PBS_JOBSIZE*PPN/PP/TP)) export export DATE_TAG=$(date +"%Y-%m-%d-%H-%M-%S") export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/wiki-en-simple/" -export DATA_FILE_LIST="/eagle/datasets//dolma//data_file_list_select.txt" +#export DATA_FILE_LIST="/eagle/datasets//dolma//data_file_list_select.txt" +DATA_FILE_LIST=$PWD/test.txt echo "BS: $BS\n PP:$PP \n TP: $TP, PBS_JOBSIZE: $PBS_JOBSIZE" HIDDEN_SIZE=4096 @@ -31,7 +32,7 @@ TRAIN_ITERS=10 ZERO_STAGE=2 MODEL=LLAMA_7B OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} -MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --hostfile $PBS_NODEFILE python3 ./pretrain_gpt_alcf.py \ +MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --cpu-bind depth -d 16 --hostfile $PBS_NODEFILE python3 ./pretrain_gpt_alcf.py \ --tensor-model-parallel-size ${TP} \ --pipeline-model-parallel-size ${PP} \ --num-layers ${NUM_LAYERS} \ diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 0f50ee2faa..a625875ab7 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -434,6 +434,7 @@ def git_ds_info(): def main(): # if RANK == 0: # setup_wandb() + ''' the following is import socket from mpi4py import MPI rank = MPI.COMM_WORLD.rank @@ -446,9 +447,8 @@ def main(): master_addr = MPI.COMM_WORLD.bcast(master_addr, root=0) os.environ["MASTER_ADDR"] = master_addr os.environ["MASTER_PORT"] = str(2345) - args = get_args() - - if (args.profile): + ''' + if os.getenv('TORCH_PROFILER_ENABLED') == '1': from torch.profiler import profile, record_function, ProfilerActivity with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: model = pretrain( From 43629e6a5b2285da9cd706d60bf45401ff826051 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 24 Feb 2024 17:18:22 -0600 Subject: [PATCH 074/268] Update `helpers_alcf.sh` for Aurora --- helpers_alcf.sh | 60 ++++++++++++++++++++++++++++++++++++++++--------- 1 file changed, 49 insertions(+), 11 deletions(-) diff --git a/helpers_alcf.sh b/helpers_alcf.sh index b91000a67c..c0f3e467f9 100644 --- a/helpers_alcf.sh +++ b/helpers_alcf.sh @@ -29,17 +29,6 @@ saveDSenv() { } > .deepspeed_env } -makeHostfiles() { - GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') - export GPUS_PER_NODE="${GPUS_PER_NODE}" - # ---- Make MPICH hostfile ---------------- - export hostfile_mpich=hostfile_mpich - cat "$PBS_NODEFILE" > "${hostfile_mpich}" - # ---- Make DeepSpeed hostfile ------------------- - export hostfile_deepspeed=hostfile_deepspeed - cat "$PBS_NODEFILE" > "${hostfile_deepspeed}" - sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" -} sumWeights() { local file_list=$1 @@ -78,3 +67,52 @@ setupData() { export DATA_CACHE_PATH=".cache/${data_file_list_stem}/index-cache" mkdir -p "${DATA_CACHE_PATH}" } + + + +setEnv() { + if [[ $(hostname) == x4* ]]; then + SETENV_FILE="${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" + if [[ "${SETENV_FILE}" ]]; then + # shellcheck source=/home/foremans/anl_24_release_q4/llm.devkit/setenv.sh + source "${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" + else + echo "Unable to source ${SETENV_FILE}, exiting!" + exit + fi + elif [[ $(hostname) == x3* ]]; then + # ---- load conda ----------------------------------- + module load conda/2023-10-04; conda activate base + if [[ "${VIRTUAL_ENV}" ]]; then + echo "Caught VIRTUAL_ENV = ${VIRTUAL_ENV} from environment!!" + else + echo "Not using VIRTUAL_ENV" + # sourceFile "${HERE}/venvs/polaris/2023-10-04/bin/activate" || exit + fi + else + echo "Unknown hostname $(hostname)" + exit 1 + fi +} + +makeHostfiles() { + GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') + export GPUS_PER_NODE="${GPUS_PER_NODE}" + # ---- Make MPICH hostfile ---------------- + export hostfile_mpich=hostfile_mpich + cat "$PBS_NODEFILE" > "${hostfile_mpich}" + # ---- Make DeepSpeed hostfile ------------------- + export hostfile_deepspeed=hostfile_deepspeed + cat "$PBS_NODEFILE" > "${hostfile_deepspeed}" + sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" +} + + +makeDSenv() { + echo "PATH=${PATH}" > .deepspeed_env + echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> .deepspeed_env + echo "http_proxy=${http_proxy}" >> .deepspeed_env + echo "https_proxy=${https_proxy}" >> .deepspeed_env + echo "CFLAGS=${CFLAGS}" >> .deepspeed_env + echo "PYTHONUSERBASE=$PYTHONUSERBASE" >> .deepspeed_env +} From 5a3dae7b3136f4f0567be098535aa17892126c5a Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 24 Feb 2024 17:20:01 -0600 Subject: [PATCH 075/268] Fix `unable to init args` in `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 63 ++++++++++++++++++++++---------------------- 1 file changed, 32 insertions(+), 31 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 7a378c3a4f..cf9251f632 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -143,13 +143,14 @@ def model_provider(pre_process=True, post_process=True): print_rank_0(f"Number of parameters in model: {num_params}") print_rank_0(80 * '-') see_memory_usage("After Building Model", force=True) - if wandb.run is not None: - wandb.run.watch( - model, - log='all', - log_graph=True, - ) - wandb.run.config.update({'num_params': num_params}) + # if wandb.run is not None: + # if torch.cuda.is_available() + # wandb.run.watch( + # model, + # log='all', + # log_graph=True, + # ) + # wandb.run.config.update({'num_params': num_params}) return model def get_batch(data_iterator): @@ -446,30 +447,30 @@ def main(): master_addr = MPI.COMM_WORLD.bcast(master_addr, root=0) os.environ["MASTER_ADDR"] = master_addr os.environ["MASTER_PORT"] = str(2345) - args = get_args() - - if (args.profile): - from torch.profiler import profile, record_function, ProfilerActivity - with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: - model = pretrain( - train_valid_test_datasets_provider, - model_provider, - ModelType.encoder_or_decoder, - forward_step, - args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, - data_post_process=data_post_process - ) - - prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") - else: - model = pretrain( - train_valid_test_datasets_provider, - model_provider, - ModelType.encoder_or_decoder, - forward_step, - args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, - data_post_process=data_post_process - ) + # args = get_args() + # + # if (args.profile): + # from torch.profiler import profile, record_function, ProfilerActivity + # with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: + # model = pretrain( + # train_valid_test_datasets_provider, + # model_provider, + # ModelType.encoder_or_decoder, + # forward_step, + # args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + # data_post_process=data_post_process + # ) + # + # prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") + # else: + model = pretrain( + train_valid_test_datasets_provider, + model_provider, + ModelType.encoder_or_decoder, + forward_step, + args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + data_post_process=data_post_process + ) # # from megatron.training import get_model # if wandb.run is not None: # args = get_args() From d44769cb9822aa24fba094c904c83326cd89fda7 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 24 Feb 2024 19:54:05 -0600 Subject: [PATCH 076/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 96 ++++++++++++++++++++++--------------- 1 file changed, 57 insertions(+), 39 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index 7f96082665..96f6197637 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -16,13 +16,19 @@ function sourceFile() { fi } -# +++++++++++++++ SCRIPT START +++++++++++++++++++++++ +# +++++++++++++++ SCRIPT START ++++++++++++++++++++++ # ---- source ./helpers_alcf.sh --------------------- HERE=$(python3 -c 'import os; print(os.getcwd())') sourceFile "${HERE}/helpers_alcf.sh" || exit # ---- load conda ----------------------------------- module load conda/2023-10-04; conda activate base +if [[ "${VIRTUAL_ENV}" ]]; then + echo "Caught VIRTUAL_ENV = ${VIRTUAL_ENV} from environment!!" +else + echo "Not using VIRTUAL_ENV" + # sourceFile "${HERE}/venvs/polaris/2023-10-04/bin/activate" || exit +fi echo "Using $(which python3)" # ---- fns from ./helpers_alcf.sh ------------------- @@ -33,17 +39,18 @@ saveDSenv # export DOLMA_CHUNK_IDX="${DOLMA_CHUNK_IDX:-0}" # # ---- DATA SETUP ------------------------------------ -DATA_FILE_LIST="./data_file_list_shuf_debug.txt" && export DATA_FILE_LIST="${DATA_FILE_LIST}" -NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" +dfl_debug="./data_file_list_shuf_debug.txt" +DATA_FILE_LIST="${DATA_FILE_LIST:-${dfl_debug}}" && export DATA_FILE_LIST="${DATA_FILE_LIST}" +NUM_DOCS=$(wc -l < "${DATA_FILE_LIST}") && export NUM_DOCS="${NUM_DOCS}" WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" && export WEIGHT_SUM="${WEIGHT_SUM}" DFL_STEM=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") && export DFL_STEM="${DFL_STEM}" dcp="${HERE}/.cache/${DFL_STEM}-index-cache" DATA_CACHE_PATH="${DATA_CACHE_PATH:-${dcp}}" && export DATA_CACHE_PATH="${DATA_CACHE_PATH}" mkdir -p "${DATA_CACHE_PATH}" if [[ -n "${DOLMA_CHUNK_IDX}" ]]; then - echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NDOCS} documents..." + echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NUM_DOCS} documents..." else - echo "Using NDOCS=${NDOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" + echo "Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" fi echo "DOCUMENT WEIGHT_SUM: ${WEIGHT_SUM}" # ---------------------------------------------------- @@ -62,6 +69,7 @@ export HEADS=${HEADS:-32} export NLAYERS=${NLAYERS:-32} export HIDDEN=${HIDDEN:-4096} export NUM_KV_HEAD=${NUM_KV_HEAD:-8} +export FFN_HIDDEN_SIZE=${FFN_HIDDEN_SIZE:-11008} # ---------------------------------------------------- # ---- Run Settings ---------------------------------- @@ -71,15 +79,16 @@ export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 export ZERO_STAGE=${ZERO_STAGE:-2} export MICRO_BATCH=${MICRO_BATCH:-8} export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} -export TOKENIZER_MODEL="${TOKENIZER_MODEL:-"/eagle/datasets/dolma/utils/tokenizer.model"}" -export TRAIN_ITER=${TRAIN_ITER:-317892} -# export TRAIN_ITER="${TRAIN_ITER:-320000}" export EVAL_ITERS="${EVAL_ITERS:-10}" +# export TRAIN_ITER="${TRAIN_ITER:-320000}" +export TRAIN_ITER=${TRAIN_ITER:-317892} export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" export SAVE_INTERVAL=${SAVE_INTERVAL:-200} +export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) +export TOKENIZER_MODEL="${TOKENIZER_MODEL:-"/eagle/datasets/dolma/utils/tokenizer.model"}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" # ---------------------------------------------------- @@ -137,14 +146,17 @@ echo "++++++++++++++++++++++++++++++++++++++++++++++++++" # ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ # ---- Build DeepSpeed Config --------------------------------- -DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" +export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit 1 # ------------------------------------------------------------- # ---- Specify output location -------------------------------- -OUTPUT_PREFIX="${HERE}/logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" +export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" # OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} -OUTPUT_DIR="${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" +OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" +export OUTPUT_DIR="${OUTPUT_DIR}" +export OUTPUT_LOG="${OUTPUT_DIR}/output.log" +echo "${OUTPUT_LOG}" >> "logs/latest" mkdir -p "${OUTPUT_DIR}" echo "!!!Please see logs at ${OUTPUT_DIR}" @@ -205,54 +217,60 @@ EXEC="pretrain_gpt_alcf.py" # --lr-decay-iters 10000 \ # --num-workers 4 \ # launch python3 ${EXEC} \ + # --data-impl mmap \ run_cmd=" deepspeed $launcher ${EXEC} \ --$DTYPE \ + --split 90,5,5 \ + --use-flash-attn-v2 \ + --no-bias-gelu-fusion \ + --lr-decay-style cosine \ + --no-bias-dropout-fusion \ + --no-masked-softmax-fusion \ + --tokenizer-type Llama2Tokenizer \ + --no-gradient-accumulation-fusion \ + --accumulate-allreduce-grads-in-fp32 \ + --use-checkpoint-opt_param-scheduler \ --lr ${LR} \ --log-interval 1 \ --seq-length $SEQ \ - --num-layers $NLAYERS \ - --hidden-size $HIDDEN \ - --ffn-hidden-size 11008 \ - --train-iters $TRAIN_ITER \ + --save ${CKPT_DIR} \ + --load ${CKPT_DIR} \ + --num-layers ${NLAYERS} \ + --hidden-size ${HIDDEN} \ + --train-iters ${TRAIN_ITER} \ --eval-iters ${EVAL_ITERS} \ - --distributed-backend $NCCL \ - --num-attention-heads $HEADS \ - --max-position-embeddings $SEQ \ - --micro-batch-size $MICRO_BATCH \ + --distributed-backend ${NCCL} \ + --num-attention-heads ${HEADS} \ --save-interval ${SAVE_INTERVAL} \ --eval-interval ${EVAL_INTERVAL} \ - --tensor-model-parallel-size $TP \ - --global-batch-size $GLOBAL_BATCH \ - --pipeline-model-parallel-size $PP \ + --max-position-embeddings ${SEQ} \ + --micro-batch-size ${MICRO_BATCH} \ --data-file-list ${DATA_FILE_LIST} \ - --load checkpoints/${OUTPUT_PREFIX} \ - --save checkpoints/${OUTPUT_PREFIX} \ - --data-cache-path ${DATA_CACHE_PATH} \ + --tensor-model-parallel-size ${TP} \ + --global-batch-size ${GLOBAL_BATCH} \ + --pipeline-model-parallel-size ${PP} \ --num-key-value-heads ${NUM_KV_HEAD} \ + --data-cache-path ${DATA_CACHE_PATH} \ + --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ --tokenizer-model ${TOKENIZER_MODEL} \ - --split 90,5,5 \ - --data-impl mmap \ - --no-masked-softmax-fusion \ - --no-bias-gelu-fusion \ - --no-bias-dropout-fusion \ - --no-gradient-accumulation-fusion \ - --use-flash-attn-v2 \ - --lr-decay-style cosine \ - --tokenizer-type Llama2Tokenizer \ - --use-checkpoint-opt_param-scheduler \ - --accumulate-allreduce-grads-in-fp32 \ $ds_args \ ${LLAMA_ARGS} \ ${gpt_args[*]} \ $custom_args \ - |& tee $OUTPUT_DIR/output.log + >> ${OUTPUT_LOG} 2>&1 & " + # |& tee $OUTPUT_DIR/output.log # ${EXTRA_ARGS} \ +echo "All DeepSpeed(s): $(which -a deepspeed)" echo "Using $(which deepspeed)" ds_report -echo ${run_cmd} -eval ${run_cmd} +echo "${run_cmd}" + +echo "[!! NOTE] View output at:" +printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" +# echo "${OUTPUT_LOG}" +eval "${run_cmd}" set +x From d3a297278fb2bf55339f7879cd5a2784628f3b6b Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 24 Feb 2024 19:54:21 -0600 Subject: [PATCH 077/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 289 ++++++++++++++++++++++++------------------- 1 file changed, 160 insertions(+), 129 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index cf9251f632..fe45a67a00 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -70,10 +70,8 @@ def model_provider(pre_process=True, post_process=True): """Build the model.""" - print_rank_0('building GPT model ...') - see_memory_usage(f"Before Building Model", force=True) - + see_memory_usage("Before Building Model", force=True) args = get_args() config = core_transformer_config_from_args(args) if wandb.run is not None: @@ -91,27 +89,36 @@ def model_provider(pre_process=True, post_process=True): assert wandb is not None and wandb.run is not None print(f'Updating {wandb.run.name=} at {wandb.run.url=}') wandb.run.config.update({'args': vars(args)}) - with deepspeed.zero.Init(data_parallel_group=dpg, - remote_device=None if args.remote_device == 'none' else args.remote_device, - config_dict_or_path=args.deepspeed_config_dict, - enabled=args.zero_stage == 3, - mpu=mpu): + with deepspeed.zero.Init( + data_parallel_group=dpg, + remote_device=( + None if args.remote_device == 'none' else args.remote_device + ), + config_dict_or_path=args.deepspeed_config_dict, + enabled=args.zero_stage == 3, + mpu=mpu + ): if args.deepspeed and not args.no_pipeline_parallel: model = GPTModelPipe( config=config, num_tokentypes=0, parallel_output=True ) - # This is a hack to give us a reference to get_batch_pipe from within training.py + # This is a hack to give us a reference to + # get_batch_pipe from within training.py # We need to call model.set_batch_fn after deepspeed.initialize model._megatron_batch_fn = get_batch_pipe - # Predompute the attention mask and store it in args. This avoids having to - # pipeline it as an activation during training. The mask is constant, and thus - # we can reuse it. - attention_mask = torch.tril(torch.ones( - (1, args.seq_length, args.seq_length), device=get_accelerator().current_device_name())).view( - 1, 1, args.seq_length, args.seq_length) + # Predompute the attention mask and store it in args. + # This avoids having to pipeline it + # as an activation during training. + # The mask is constant, and thus we can reuse it. + attention_mask = torch.tril( + torch.ones( + (1, args.seq_length, args.seq_length), + device=get_accelerator().current_device_name() + ) + ).view(1, 1, args.seq_length, args.seq_length) # Convert attention mask to binary: attention_mask = (attention_mask < 0.5) @@ -123,7 +130,8 @@ def model_provider(pre_process=True, post_process=True): # Attention mask must be bool. args.attn_mask = attention_mask.to(torch.bool) - # For prertaining, since sequence length is fixed, cache rotary embedding in args, to avoid communicating around + # For prertaining, since sequence length is fixed, + # cache rotary embedding in args, to avoid communicating around if args.use_rotary_position_embeddings: update_rotary_pos_emb(args.seq_length) @@ -143,8 +151,8 @@ def model_provider(pre_process=True, post_process=True): print_rank_0(f"Number of parameters in model: {num_params}") print_rank_0(80 * '-') see_memory_usage("After Building Model", force=True) - # if wandb.run is not None: - # if torch.cuda.is_available() + if wandb.run is not None: + wandb.run.config.update({'num_params': num_params}) # wandb.run.watch( # model, # log='all', @@ -153,6 +161,7 @@ def model_provider(pre_process=True, post_process=True): # wandb.run.config.update({'num_params': num_params}) return model + def get_batch(data_iterator): """Generate a batch""" args = get_args() @@ -162,11 +171,12 @@ def get_batch(data_iterator): keys = ['text'] datatype = torch.int64 - # Broadcast data. - if data_iterator is not None: - data = next(data_iterator) - else: - data = None + data = next(data_iterator) if data_iterator is not None else None + # # Broadcast data. + # if data_iterator is not None: + # data = next(data_iterator) + # else: + # data = None data_b = tensor_parallel.broadcast_data(keys, data, datatype) # Unpack. @@ -207,6 +217,7 @@ def get_batch(data_iterator): return tokens, labels, loss_mask, attention_mask, position_ids + def data_post_process(data, data_sampler_state_dict): args = get_args() if args.data_efficiency_curriculum_learning: @@ -232,8 +243,12 @@ def data_post_process(data, data_sampler_state_dict): args.data_efficiency_curriculum_learning_seqlen_type = None return data + def get_batch_pipe(data): - """Modification of `get_batch` to work on `next(data_iterator)` instead of `data_iterator`""" + """ + Modification of `get_batch` to work on `next(data_iterator)` + instead of `data_iterator` + """ args = get_args() tokenizer = get_tokenizer() @@ -256,9 +271,13 @@ def get_batch_pipe(data): args.reset_position_ids, args.reset_attention_mask, args.eod_mask_loss) - if args.curriculum_learning_legacy and args.curriculum_seqlen < tokens.size()[1]: + if ( + args.curriculum_learning_legacy + and args.curriculum_seqlen < tokens.size()[1] + ): # seqlen-based curriculum learning - # tokens, position_ids, labels, loss_mask have size [batch size, seqlen] + # tokens, position_ids, labels, loss_mask + # have size [batch size, seqlen] tokens = tokens[:, :args.curriculum_seqlen].contiguous() position_ids = position_ids[:, :args.curriculum_seqlen].contiguous() if labels is not None: @@ -280,18 +299,39 @@ def loss_func(loss_mask, moe_loss, mos_loss, output_tensor): # assert max(args.num_experts) >= 1 loss = loss + moe_loss + mos_loss if args.mos: - return loss, {'total loss': loss, 'lm loss': averaged_loss[0], 'moe loss': moe_loss, 'mos loss': mos_loss} + return loss, { + 'total loss': loss, + 'lm loss': averaged_loss[0], + 'moe loss': moe_loss, + 'mos loss': mos_loss + } elif args.kd: - return loss, {'total loss': loss, 'lm loss': averaged_loss[0], 'moe loss': moe_loss, 'kd loss': mos_loss} - print_rank_0('>>> total loss: {}, lm loss {}, kd loss {}'.format(loss, averaged_loss[0], mos_loss)) + return loss, { + 'total loss': loss, + 'lm loss': averaged_loss[0], + 'moe loss': moe_loss, + 'kd loss': mos_loss + } + print_rank_0( + f'>>> total loss: {loss}, ' + f'lm loss {averaged_loss[0]}, ' + f'kd loss {mos_loss}' + ) else: if max(args.num_experts) <= 1: return loss, {'lm loss': averaged_loss[0]} - else: - loss = loss + moe_loss - return loss, {'lm loss': averaged_loss[0], 'moe loss': moe_loss} + loss = loss + moe_loss + return loss, {'lm loss': averaged_loss[0], 'moe loss': moe_loss} -def calculate_mos_loss(args, stu_output, teacher_model, tokens, position_ids, attention_mask): + +def calculate_mos_loss( + args, + stu_output, + teacher_model, + tokens, + position_ids, + attention_mask +): mos_loss = 0 alpha = args.kd_alpha_ce beta = args.kd_beta_ce @@ -299,24 +339,48 @@ def calculate_mos_loss(args, stu_output, teacher_model, tokens, position_ids, at if teacher_model: with torch.no_grad(): - if args.curriculum_learning_legacy and args.curriculum_seqlen < args.seq_length: + if ( + args.curriculum_learning_legacy and + args.curriculum_seqlen < args.seq_length + ): assert args.curriculum_seqlen is not None curriculum_seqlen = args.curriculum_seqlen tokens = tokens[:, :curriculum_seqlen].contiguous() position_ids = position_ids[:, :curriculum_seqlen].contiguous() - attention_mask = attention_mask[:, :, :curriculum_seqlen, :curriculum_seqlen].contiguous() - # No need to truncate labels as we do not need it for the teacher logits - tea_output, tea_other_losses = teacher_model(tokens, position_ids, attention_mask) - assert stu_output.size() == tea_output.size(), 'teacher and student output should match in size. Student: {}, Teacher: {}, CL seq length {}'.format(stu_output.size(), tea_output.size(), args.curriculum_seqlen) + csl = curriculum_seqlen + attention_mask = ( + attention_mask[:, :, :csl, :csl].contiguous() + ) + # No need to truncate labels + # as we do not need it for the teacher logits + tea_output, tea_other_losses = teacher_model( + tokens, + position_ids, + attention_mask + ) + assert stu_output.size() == tea_output.size(), ( + 'teacher and student output should match in size. ' + f'Student: {stu_output.size()}, ' + f'Teacher: {tea_output.size()}, ' + f'CL seq length {args.curriculum_seqlen}' + ) student_logits = F.log_softmax(stu_output / kd_temp, dim=2) - tea_logits = F.softmax(tea_output / kd_temp, dim=2) # The target logits is expected to be probabilities. If we use log_softmax, then we need to set target_log to true when initializing the KLDivLoss. - - mos_loss = kd_temp * kd_temp * nn.KLDivLoss(reduction='batchmean')(student_logits, tea_logits) + # The target logits is expected to be probabilities. + # If we use log_softmax, + # then we need to set target_log to true + # when initializing the KLDivLoss. + tea_logits = F.softmax(tea_output / kd_temp, dim=2) + + mos_loss = kd_temp * kd_temp * nn.KLDivLoss(reduction='batchmean')( + student_logits, + tea_logits + ) mos_loss = mos_loss.div(args.seq_length) * beta return mos_loss + def forward_step(data_iterator, model): """Forward step.""" args = get_args() @@ -330,21 +394,44 @@ def forward_step(data_iterator, model): if args.data_efficiency_curriculum_learning: args.curriculum_seqlen = tokens.size()[1] - if hasattr(args, 'data_efficiency_curriculum_learning_seqlen_type') and \ - args.data_efficiency_curriculum_learning_seqlen_type == 'seqlen_reshape': - args.data_efficiency_curriculum_learning_numel = torch.numel(tokens) + if ( + hasattr( + args, + 'data_efficiency_curriculum_learning_seqlen_type') + and ( + args.data_efficiency_curriculum_learning_seqlen_type + == 'seqlen_reshape' + ) + ): + args.data_efficiency_curriculum_learning_numel = ( + torch.numel(tokens) + ) if args.mos or args.kd: - # The forward func can return either the loss or the logits, depending on whether passing in the labels or not. + # The forward func can return either the loss or the logits, + # depending on whether passing in the labels or not. stu_output, other_losses = model(tokens, position_ids, attention_mask) - if args.curriculum_learning_legacy and args.curriculum_seqlen < args.seq_length: + if ( + args.curriculum_learning_legacy + and args.curriculum_seqlen < args.seq_length + ): assert args.curriculum_seqlen is not None labels = labels[:, :args.curriculum_seqlen].contiguous() - output_tensor = tensor_parallel.vocab_parallel_cross_entropy(stu_output.contiguous().float(), labels) + output_tensor = tensor_parallel.vocab_parallel_cross_entropy( + stu_output.contiguous().float(), + labels + ) else: - output_tensor, other_losses = model(tokens, position_ids, attention_mask, - labels=labels) - if args.curriculum_learning_legacy and args.curriculum_seqlen < args.seq_length: + output_tensor, other_losses = model( + tokens, + position_ids, + attention_mask, + labels=labels + ) + if ( + args.curriculum_learning_legacy and + args.curriculum_seqlen < args.seq_length + ): loss_mask = loss_mask[:, :args.curriculum_seqlen].contiguous() moe_losses = [] @@ -357,10 +444,17 @@ def forward_step(data_iterator, model): if args.mos or args.kd: assert model.training if args.teacher_forward and args.teacher_model is not None: - mos_loss = calculate_mos_loss(args, stu_output, - args.teacher_model[0], tokens, position_ids, attention_mask) + mos_loss = calculate_mos_loss( + args, + stu_output, + args.teacher_model[0], + tokens, + position_ids, + attention_mask + ) - # Output_tensor stores the standard loss, loos_func calculates the total loss. + # Output_tensor stores the standard loss, + # loss_func calculates the total loss. return output_tensor, partial(loss_func, loss_mask, moe_loss, mos_loss) @@ -377,11 +471,11 @@ def train_valid_test_datasets_provider(train_val_test_num_samples): w, fname = f.split() files.append(float(w)) files.append(fname) - elif len(args.data_path)==1 and os.path.isdir(args.data_path[0]): - path=args.data_path[0] + "/" + elif len(args.data_path) == 1 and os.path.isdir(args.data_path[0]): + path = args.data_path[0] + "/" for f in os.listdir(path): - if (os.path.isfile(path + f) and f.find(".bin")!=-1): - files.append(1) + if (os.path.isfile(path + f) and f.find(".bin") != -1): + files.append(1) files.append(path + f.split(".bin")[0]) else: files = args.data_path @@ -404,7 +498,11 @@ def train_valid_test_datasets_provider(train_val_test_num_samples): def command_exists(cmd): - result = subprocess.Popen(f'type {cmd}', stdout=subprocess.PIPE, shell=True) + result = subprocess.Popen( + f'type {cmd}', + stdout=subprocess.PIPE, + shell=True + ) return result.wait() == 0 @@ -429,24 +527,13 @@ def git_ds_info(): else: git_hash = "unknown" git_branch = "unknown" - print(f'**** Git info for Megatron: git_hash={git_hash} git_branch={git_branch} ****') + print( + f'**** Git info for Megatron: ' + f'git_hash={git_hash} git_branch={git_branch} ****' + ) def main(): - # if RANK == 0: - # setup_wandb() - import socket - from mpi4py import MPI - rank = MPI.COMM_WORLD.rank - - if rank == 0: - master_addr = socket.gethostname() - else: - master_addr = None - - master_addr = MPI.COMM_WORLD.bcast(master_addr, root=0) - os.environ["MASTER_ADDR"] = master_addr - os.environ["MASTER_PORT"] = str(2345) # args = get_args() # # if (args.profile): @@ -471,65 +558,9 @@ def main(): args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, data_post_process=data_post_process ) - # # from megatron.training import get_model - # if wandb.run is not None: - # args = get_args() - # timers = get_timers() - # # model = get_model(model_provider, ModelType.encoder_or_decoder) - # elapsed_time = timers('interval-time').elapsed(barrier=True) - # total_iterations = os.environ.get( - # "TOTAL_ITERATIONS", - # (args.train_iters + args.eval_iters) - # ) - # seq_len = args.seq_length - # elapsed_time_per_iteration = elapsed_time / total_iterations - # if model is not None: - # samples_per_sec, tflops, approx_params_in_billions = throughput_calculator( - # model, - # args, - # elapsed_time, - # total_iterations, - # ) - # # Compute throughput. - # samples_per_sec_per_replica = samples_per_sec / args.data_parallel_size - # tokens_per_sec = samples_per_sec * seq_len - # tokens_per_sec_per_replica = tokens_per_sec / args.data_parallel_size - # sample_consumption_rate = args.consumed_train_samples / elapsed_time - # token_consumption_rate = args.consumed_train_tokens / elapsed_time - # # Tensorboard values. - # tdata = { - # # 'iteration': iteration, - # 'consumed_train_samples': args.consumed_train_samples, - # 'consumed_train_tokens': args.consumed_train_tokens, - # # 'learning_rate': learning_rate, - # # 'batch_size': batch_size, - # # 'loss_scale': loss_scale, - # # 'grad_norm': grad_norm, - # } - # # for key in loss_dict: - # # tdata[f'lm-loss/{key}'] = loss_dict[key] - # - # tdata = {f'train/{k}': v for k, v in tdata.items()} - # # if wbrun is not None and wbrun is wandb.run: - # if wandb.run is not None: - # wandb.run.log(tdata, commit=False) - # tput = { - # 'throughput/iteration-time': elapsed_time_per_iteration, # 1000 ms / s - # 'throughput/samples_per_sec': samples_per_sec, - # 'throughput/samples_per_sec_per_replica': samples_per_sec_per_replica, - # 'throughput/tokens_per_sec': tokens_per_sec, - # 'throughput/tokens_per_sec_per_replica': tokens_per_sec_per_replica, - # 'throughput/tflops': tflops, - # 'throughput/approx_params_in_billions': approx_params_in_billions, - # 'throughput/sample_consumption_rate': sample_consumption_rate, - # 'throughput/token_consumption_rate': token_consumption_rate, - # 'throughput/elapsed_ms_per_iteration': elapsed_time_per_iteration, - # } - # wandb.run.log(tput) return model - if __name__ == "__main__": # git_ds_info() # pretrain(train_valid_test_datasets_provider, From 3b6b94ab713e44a235831de0ab75955765f34f13 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 24 Feb 2024 19:54:37 -0600 Subject: [PATCH 078/268] Update `megatron/training.py` --- megatron/training.py | 35 ++++++++++++++++++++++------------- 1 file changed, 22 insertions(+), 13 deletions(-) diff --git a/megatron/training.py b/megatron/training.py index ef32cd3856..7e6c7dc6bb 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -1021,6 +1021,7 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, writer.add_scalar('optimizer/momentum_abs_max', opt_stats_2[2], iteration) writer.add_scalar('optimizer/weight_abs_max', opt_stats_2[3], iteration) + assert args is not None if iteration % args.log_interval == 0: elapsed_time = timers('interval-time').elapsed(barrier=True) elapsed_time_per_iteration = elapsed_time / total_iterations @@ -1038,6 +1039,7 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, tokens_per_sec_per_replica = tokens_per_sec / args.data_parallel_size tokens_per_gpu_per_second = tokens_per_sec / args.world_size tokens_per_gpu_per_second_per_replica = tokens_per_gpu_per_second / args.data_parallel_size + wandb_metrics = {} if wandb is not None and getattr(wandb, 'run', None) is not None: assert wandb.run is not None wandb_metrics = { @@ -1055,17 +1057,16 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, } if loss_dict is not None: wandb_metrics |= { - f'loss/{k}': v for k, v in loss_dict.items() + 'loss/iteration': iteration, + **{f'loss/{k}': v for k, v in loss_dict.items()} } - wandb_metrics |= {'loss/iteration': iteration} - if writer: - if args.log_timers_to_tensorboard: - writer.add_scalar('iteration-time/iteration-time', - elapsed_time_per_iteration, iteration) - writer.add_scalar('iteration-time/iteration-time vs samples', - elapsed_time_per_iteration, args.consumed_train_samples) - writer.add_scalar('iteration-time/iteration-time vs tokens', - elapsed_time_per_iteration, args.consumed_train_tokens) + if writer and args.log_timers_to_tensorboard: + writer.add_scalar('iteration-time/iteration-time', + elapsed_time_per_iteration, iteration) + writer.add_scalar('iteration-time/iteration-time vs samples', + elapsed_time_per_iteration, args.consumed_train_samples) + writer.add_scalar('iteration-time/iteration-time vs tokens', + elapsed_time_per_iteration, args.consumed_train_tokens) log_string = ' iteration {:8d}/{:8d} |'.format( iteration, args.train_iters) log_string += ' consumed samples: {:12d} |'.format( @@ -1099,16 +1100,18 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, if avg > 0.0: log_string += ' {}: {:.6E} |'.format(key, avg) total_loss_dict[key] = get_accelerator().FloatTensor([0.0]) - if wandb is not None and getattr(wandb, 'run', None) is not None: - wandb.log(wandb_metrics) if loss_scale is not None: log_string += ' loss scale: {:.1f} |'.format(loss_scale) + wandb_metrics |= {'loss/loss_scale': loss_scale} if grad_norm is not None: log_string += ' grad norm: {:.3f} |'.format(grad_norm) + wandb_metrics |= {'loss/grad_norm': grad_norm} if num_zeros_in_grad is not None: log_string += ' num zeros: {:.1f} |'.format(num_zeros_in_grad) + wandb_metrics |= {'loss/num_zeros_in_grad': num_zeros_in_grad} if params_norm is not None: log_string += ' params norm: {:.3f} |'.format(params_norm) + wandb_metrics |= {'loss/params_norm': params_norm} if args.curriculum_learning_legacy or args.data_efficiency_curriculum_learning: log_string += ' curriculum seqlen: {:5d} |'.format(args.curriculum_seqlen) if args.random_ltd: @@ -1129,7 +1132,12 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, # Report memory after optimizer state has been initialized. report_memory('(after {} iterations)'.format(iteration)) report_memory_flag = False - timers.log(timers_to_log, normalizer=args.log_interval) + if wandb is not None and getattr(wandb, 'run', None) is not None: + wandb_metrics |= {'training/skiped_iterations': total_loss_dict[skipped_iters_key]} + wandb_metrics |= {'training/nan_iterations': total_loss_dict[nan_iters_key]} + wandb.log(wandb_metrics) + if timers is not None: + timers.log(timers_to_log, normalizer=args.log_interval) return report_memory_flag @@ -1138,6 +1146,7 @@ def save_checkpoint_and_time(iteration, model, optimizer, opt_param_scheduler): timers = get_timers() # Extra barrier is added to make sure # all ranks report the max time. + # assert timers is not None timers('save-checkpoint', log_level=0).start(barrier=True) save_checkpoint(iteration, model, optimizer, opt_param_scheduler) timers('save-checkpoint').stop(barrier=True) From 4628b9f4c6a5157ab65331a7ec0a3f48c63e6cc7 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 24 Feb 2024 20:55:03 -0600 Subject: [PATCH 079/268] Add `train_llama_alcf_aurora.sh` --- train_llama_alcf_aurora.sh | 230 +++++++++++++++++++++++++++++++++++++ 1 file changed, 230 insertions(+) create mode 100644 train_llama_alcf_aurora.sh diff --git a/train_llama_alcf_aurora.sh b/train_llama_alcf_aurora.sh new file mode 100644 index 0000000000..04341ca843 --- /dev/null +++ b/train_llama_alcf_aurora.sh @@ -0,0 +1,230 @@ +#!/bin/bash --login +#PBS -l walltime=06:00:00 +#PBS -A argonne_tpc +#PBS -q prod +#PBS -l select=48 +#PBS -l filesystems=eagle:home +# + +function sourceFile() { + fp="$1" + echo "source-ing ${fp}" + if [[ -f "${fp}" ]]; then + # shellcheck source="${fp}" + source "${fp}" + else + echo "ERROR: UNABLE TO SOURCE ${fp}" + fi +} + +# +++++++++++++++ SCRIPT START ++++++++++++++++++++++ +# ---- source ./helpers_alcf.sh --------------------- +HERE=$(python3 -c 'import os; print(os.getcwd())') +sourceFile "${HERE}/helpers_alcf.sh" || exit + +# cd ~/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed || exit +# eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate anl_release_q4v2 +ezpz +setEnv +makeDSenv +makeHostfiles + +# ---- DATA SETUP ------------------------------------ +export DATA_FILE_LIST="./data_file_list_shuf_debug.txt" +NUM_DOCS=$(wc -l < "${DATA_FILE_LIST}") && export NUM_DOCS="${NUM_DOCS}" +WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" && export WEIGHT_SUM="${WEIGHT_SUM}" +DFL_STEM=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") && export DFL_STEM="${DFL_STEM}" +dcp="${HERE}/.cache/${DFL_STEM}-index-cache" +DATA_CACHE_PATH="${DATA_CACHE_PATH:-${dcp}}" && export DATA_CACHE_PATH="${DATA_CACHE_PATH}" +mkdir -p "${DATA_CACHE_PATH}" +if [[ -n "${DOLMA_CHUNK_IDX}" ]]; then + echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NUM_DOCS} documents..." +else + echo "Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" +fi +echo "DOCUMENT WEIGHT_SUM: ${WEIGHT_SUM}" +# ---------------------------------------------------- + + +# ---- Parallelism Settings -------------------------- +PP=${PP:-1} +TP=${TP:-1} +export PP="${PP}" +export TP="${TP}" +export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" +export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} +# export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${PBS_NODEFILE}")} +# ---------------------------------------------------- + +# ---- Llama2 7B Config ----------------------- +export HEADS=${HEADS:-32} +export NLAYERS=${NLAYERS:-32} +export HIDDEN=${HIDDEN:-4096} +export NUM_KV_HEAD=${NUM_KV_HEAD:-8} +export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" +# --------------------------------------------- + +# ---- Run Settings --------------------------- +export LR=${LR:-0.0003} +export SEQ=${SEQ:-4096} +export DTYPE=${DTYPE:-bf16} +export ZERO_STAGE=${ZERO_STAGE:-2} +export MICRO_BATCH=${MICRO_BATCH:-4} +export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} +export TRAIN_ITER=${TRAIN_ITER:-317892} +export SAVE_INTERVAL=${SAVE_INTERVAL:-200} +export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} +export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) +export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} +export TOKENIZER_MODEL="/lus/gecko/projects/Aurora_deployment/AuroraGPT/datasets/dolma/utils/tokenizer.model" +# export EXTRA_ARGS="" +export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" +# --------------------------------------------- + +# ---- Build DeepSpeed Config --------------------------------- +export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" +bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit +# ------------------------------------------------------------- + + +# ---- Specify output location -------------------------------- +export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" +# OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} +OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" +export OUTPUT_DIR="${OUTPUT_DIR}" +export OUTPUT_LOG="${OUTPUT_DIR}/output.log" +export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" +echo "${OUTPUT_LOG}" >> "logs/latest" +mkdir -p "${OUTPUT_DIR}" +echo "!!!Please see logs at ${OUTPUT_DIR}" + + +gpt_args=() +ds_args=" " +ds_args=" --deepspeed ${ds_args}" +if [ "$PP" == 1 ]; then + ds_args=" --no-pipeline-parallel ${ds_args}" +fi +ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" +ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" + +# BUG: [???] ---------------------------------------------------------------- +# I dont know where this came from... +# > we are now using activation checkpoint provided by megatron, see below. +# --------------------------------------------------------------------------- +# +# NOTE: [???] --------------------------------------------------------------- +# In `train_llama_alcf_polaris.sh` we also pass +# `"--checkpoint-num-layers 1"` +# ---------------------------------------------------------------------------- +if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" + ds_args=" --deepspeed-activation-checkpointing ${ds_args}" + gpt_args+=( + "--checkpoint-activations" + ) + # "--checkpoint-num-layers 1" + # --checkpoint-activations \ + # --deepspeed-activation-checkpointing +fi + +# take custom args +custom_args=" $@" + +# Ensure `./hostfile_deepspeed` and `./hostfile_mpich` exist in $(pwd) +hfds="${HERE}/hostfile_deepspeed" +hfmpi="${HERE}/hostfile_mpich" +[ -f "$hfds" ] || exit +[ -f "$hfmpi" ] || exit + +# launcher setting +LAUNCHER=${LAUNCHER:-MPICH} +if [[ $LAUNCHER == "deepspeed" ]]; then + launcher="" +else + launcher="--force_multi --hostfile ${hfds} --launcher=${LAUNCHER} --launcher_args='-hostfile ${hfmpi}'" +fi + + +if [[ $(hostname) == x4* ]]; then + CCL=${CCL:-ccl} + BE="${CCL}" +elif [[ $(hostname) == x3* ]]; then + NCCL=${NCCL:-nccl} + BE="${NCCL}" +fi +# NCCL=${NCCL:-nccl} +EXEC=pretrain_gpt_alcf.py + +# MODEL=LLAMA_7B +# OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_tp${TP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} +echo "++++++++++++++++++++++++++++++++++++++++++++++++++" +echo "- WORLD_SIZE:${WORLD_SIZE}" +echo "- BACKEND: ${BE}" +echo "- MODEL_TYPE: ${MODEL_TYPE}" +echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" +echo "++++++++++++++++++++++++++++++++++++++++++++++++++" + +run_cmd=" + deepspeed $launcher ${EXEC} \ + --use-flash-attn \ + --num-key-value-heads ${NUM_KV_HEAD} \ + --tensor-model-parallel-size $TP \ + --pipeline-model-parallel-size $PP \ + --num-layers $NLAYERS \ + --hidden-size $HIDDEN \ + --num-attention-heads $HEADS \ + --seq-length $SEQ \ + --max-position-embeddings $SEQ \ + --micro-batch-size $MICRO_BATCH \ + --global-batch-size $GLOBAL_BATCH \ + --train-iters $TRAIN_ITER \ + --lr ${LR} \ + --lr-decay-style cosine \ + --log-interval 1 \ + --save-interval ${SAVE_INTERVAL} \ + --split 100,0,0 \ + --$DTYPE \ + --no-masked-softmax-fusion \ + --no-bias-gelu-fusion \ + --no-bias-dropout-fusion \ + --no-gradient-accumulation-fusion \ + --distributed-backend ${BE} \ + --tokenizer-type Llama2Tokenizer \ + --save checkpoints/${OUTPUT_PREFIX} \ + --load checkpoints/${OUTPUT_PREFIX} \ + --use-checkpoint-opt_param-scheduler \ + --tokenizer-model ${TOKENIZER_MODEL} \ + --data-file-list ${DATA_FILE_LIST} \ + --data-cache-path ${DATA_CACHE_PATH} \ + $ds_args \ + ${LLAMA_ARGS} \ + ${gpt_args[*]} \ + $custom_args \ + >> ${OUTPUT_LOG} 2>&1 & + " + # |& tee $OUTPUT_DIR/output.log + +# --ffn-hidden-size 11008 \ +# --vocab-file $VOCAB_FILE \ +# --merge-file $MERGE_FILE \ +# --lr-decay-iters 320000 \ +# --num-workers 0 \ +# --eval-iters ${EVAL_ITERS} \ +# --eval-interval ${EVAL_INTERVAL} \ +# --lr-warmup-iters 5000 \ +# --lr-decay-iters 10000 \ +# --accumulate-allreduce-grads-in-fp32 \ +# --data-impl mmap \ + +echo "All DeepSpeed(s): $(which -a deepspeed)" +echo "Using $(which deepspeed)" +ds_report + +echo "${run_cmd}" + +echo "[!! NOTE] View output at:" +printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" + +eval "${run_cmd}" +set +x From ef1e83ed18fb56e3ee93d159c574b264d9d35c94 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 24 Feb 2024 20:58:51 -0600 Subject: [PATCH 080/268] Renamed `llama_alcf.sh -> train_llama_alcf_polaris_hzheng.sh` --- llama_alcf.sh => train_llama_alcf_polaris_hzheng.sh | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename llama_alcf.sh => train_llama_alcf_polaris_hzheng.sh (100%) diff --git a/llama_alcf.sh b/train_llama_alcf_polaris_hzheng.sh similarity index 100% rename from llama_alcf.sh rename to train_llama_alcf_polaris_hzheng.sh From 34f72d7fca5abd01b26a4cbae2b4a119bceb49bf Mon Sep 17 00:00:00 2001 From: Varuni Date: Mon, 26 Feb 2024 16:41:53 +0000 Subject: [PATCH 081/268] add util files --- ALCF_utils/fused_stackcode.py | 36 ++++++++++++++++ ALCF_utils/fused_stackcode_bysize.py | 64 ++++++++++++++++++++++++++++ 2 files changed, 100 insertions(+) create mode 100644 ALCF_utils/fused_stackcode.py create mode 100644 ALCF_utils/fused_stackcode_bysize.py diff --git a/ALCF_utils/fused_stackcode.py b/ALCF_utils/fused_stackcode.py new file mode 100644 index 0000000000..28c1e5c694 --- /dev/null +++ b/ALCF_utils/fused_stackcode.py @@ -0,0 +1,36 @@ +import os +from os import system +import glob +import json +import gzip +import pdb + +def list_json_gz_files(directory): + # Create the search pattern for JSON.gz files + search_pattern = os.path.join(directory, "**/*.json.gz") + + # Use glob to find all files matching the pattern + json_gz_files = glob.glob(search_pattern, recursive=True) + + return json_gz_files + +def combine_json_gz_files(json_gz_files, output_file): + in_list = "" + for i in json_gz_files: + in_list = in_list + " " +str(i) + command = "cat" + in_list + " > " + output_file + print(command) + system(command) + print("done") + +directory_path = "./data/stack-code/" +folder_count = 0 +for folder in os.listdir(directory_path): + print(f"working for folder {folder} {os.path.join(directory_path, folder)}") + folder_count = folder_count + 1 + json_gz_files = list_json_gz_files(os.path.join(directory_path, folder)) + out_path = os.path.join("./fused_stack", folder) + os.makedirs(out_path, exist_ok=True) + output_file = os.path.join(out_path, 'fused.json.gz') + combine_json_gz_files(json_gz_files, output_file) + diff --git a/ALCF_utils/fused_stackcode_bysize.py b/ALCF_utils/fused_stackcode_bysize.py new file mode 100644 index 0000000000..d838369e6b --- /dev/null +++ b/ALCF_utils/fused_stackcode_bysize.py @@ -0,0 +1,64 @@ +import os +from os import system +import glob +import json +import gzip +import pdb + +def list_json_gz_files(directory): + # Create the search pattern for JSON.gz files + search_pattern = os.path.join(directory, "**/*.json.gz") + + # Use glob to find all files matching the pattern + json_gz_files = glob.glob(search_pattern, recursive=True) + + return json_gz_files + +def combine_json_gz_files(json_gz_files, output_file): + in_list = "" + for i in json_gz_files: + in_list = in_list + " " +str(i) + command = "cat" + in_list + " > " + output_file + print(command) + system(command) + print("done ?") + +directory_path = "./fused_stack/" +out_path = "./fused_by_size" +folder_count = 0 +file_list = list_json_gz_files(directory_path) +size_dict = {} +for efile in file_list: + size_of_files = os.stat(efile) + size_dict[efile] = size_of_files.st_size / (1024*1024) # in MBs + +sorted_size_dict = dict(sorted(size_dict.items(), key=lambda item: item[1])) +vol = 0 +sublist = [] +super_list = {} +i=1 +for key, val in sorted_size_dict.items(): + if vol + val > 4608: + # add this item to list and reset vol, sublist + vol = 0 + sublist.append(key) + #print(sublist) + print("************") + super_list[i] = sublist + output_file = out_path + "/fused_stack_" + str(i) + ".json.gz" + print(output_file) + combine_json_gz_files(sublist, output_file) + sublist = [] + i=i+1 + else: + vol = vol + val + sublist.append(key) +#print(t) +#for folder in os.listdir(directory_path): +# print(f"working for folder {folder} {os.path.join(directory_path, folder)}") +# folder_count = folder_count + 1 +# json_gz_files = list_json_gz_files(os.path.join(directory_path, folder)) +# out_path = os.path.join("./fused_stack", folder) +# os.makedirs(out_path, exist_ok=True) +# output_file = os.path.join(out_path, 'fused.json.gz') +# combine_json_gz_files(json_gz_files, output_file) From 5a0fa3016b3c500b17b7eb74197798db4b21b834 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 28 Feb 2024 09:44:03 -0600 Subject: [PATCH 082/268] Add `ALCF_utils/{test_blend.sh,test_blendable_dataset.py}` --- ALCF_utils/test_blend.sh | 73 ++++++++++++++++++++++++++++ ALCF_utils/test_blendable_dataset.py | 73 ++++++++++++++++++++++++++++ 2 files changed, 146 insertions(+) create mode 100755 ALCF_utils/test_blend.sh create mode 100644 ALCF_utils/test_blendable_dataset.py diff --git a/ALCF_utils/test_blend.sh b/ALCF_utils/test_blend.sh new file mode 100755 index 0000000000..9073d2a58c --- /dev/null +++ b/ALCF_utils/test_blend.sh @@ -0,0 +1,73 @@ +#!/bin/bash +#PBS -l walltime=0:30:00 +#PBS -A datascience +#PBS -q debug +#PBS -l select=1 +#PBS -l filesystems=eagle:grand:home +cd ${PBS_O_WORKDIR} +export PPN=4 +export MD=/home/hzheng/ALCF-Megatron-DeepSpeed +module load conda/2023-10-04 +#conda activate /soft/datascience/megatron-deepspeed/2023-10-04 +conda activate $HOME/PolarisAT/pyenvs/megatron/2023-10-04 +export TP=1 +export PP=1 +export SP=128 +export MBS=1 +export BS=$((MBS*SP)) +export export DATE_TAG=$(date +"%Y-%m-%d-%H-%M-%S") +export DATA_FILE_LIST="/eagle/datasets//dolma/chunks-merge/data_file_list_chunk_1_of_4.txt" + +HIDDEN_SIZE=4096 +NUM_LAYERS=32 +SEQ_LENGTH=2048 +EMBEDDINGS=2048 +TRAIN_ITERS=10 +ZERO_STAGE=2 +MODEL=LLAMA_7B +OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} +#MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --cpu-bind depth -d 16 --hostfile $PBS_NODEFILE +python3 ./test_blendable_dataset.py \ + --tensor-model-parallel-size ${TP} \ + --pipeline-model-parallel-size ${PP} \ + --num-layers ${NUM_LAYERS} \ + --hidden-size ${HIDDEN_SIZE} \ + --ffn-hidden-size 5504 \ + --num-attention-heads 32 \ + --micro-batch-size ${MBS} \ + --global-batch-size ${BS} \ + --seq-length ${SEQ_LENGTH} \ + --max-position-embeddings ${EMBEDDINGS} \ + --train-iters 80797 \ + --save ${MD}/checkpoints/${OUTPUT_PREFIX} \ + --load ${MD}/checkpoints/${OUTPUT_PREFIX} \ + --tokenizer-type Llama2Tokenizer \ + --split 949,50,1 \ + --distributed-backend nccl \ + --lr 3e-4 \ + --lr-decay-style cosine \ + --min-lr 3e-5 \ + --weight-decay 0.1 \ + --clip-grad 1 \ + --lr-warmup-iters 2 \ + --optimizer adam \ + --adam-beta1 0.9 \ + --adam-beta2 0.95 \ + --log-interval 1 \ + --cpu-optimizer \ + --save-interval 10000 \ + --eval-interval 1000 \ + --eval-iters 10 --fp16 \ + --no-query-key-layer-scaling \ + --attention-dropout 0 \ + --hidden-dropout 0 \ + --use-rotary-position-embeddings \ + --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ + --untie-embeddings-and-output-weights \ + --swiglu --normalization layernorm --disable-bias-linear --num-key-value-heads 4 \ + --tensorboard-dir ./outputs/${OUTPUT_PREFIX}/tensorboard --log-timers-to-tensorboard --tensorboard-log-interval 1 \ + --data-file-list ${DATA_FILE_LIST} \ + --data-path ${DATA_PATH} \ + --data-cache-path /tmp/hzheng-megatron-deepspeed-cache/ \ + --vocab-file ${MD}/dataset/gpt2-vocab.json --merge-file ${MD}/dataset/gpt2-merges.txt \ + --zero-stage=${ZERO_STAGE} --deepspeed_config=${MD}/ds_config-gpt.json --deepspeed diff --git a/ALCF_utils/test_blendable_dataset.py b/ALCF_utils/test_blendable_dataset.py new file mode 100644 index 0000000000..1cf40c5aaf --- /dev/null +++ b/ALCF_utils/test_blendable_dataset.py @@ -0,0 +1,73 @@ +#!/usr/bin/env python +from megatron.data.gpt_dataset import build_train_valid_test_datasets +import numpy as np +from megatron.global_vars import set_args, set_global_variables, get_args +from megatron.arguments import parse_args +from megatron.initialize import initialize_megatron +from megatron.data.data_samplers import build_pretraining_data_loader + +initialize_megatron(allow_no_cuda=True) +args = get_args() + +data_file_list = args.data_file_list +print(f"Reading data from {args.data_file_list}") +files = [] +weights = [] +flist = [] +with open(data_file_list, 'r') as fin: + for f in fin.readlines(): + w, fname = f.split() + weights.append(float(w)) + flist.append(fname) + files.append(float(w)) + files.append(fname) +splits_string="100,0,0" + +weights = np.array(weights) +weights = weights/np.sum(weights) + +num_samples = args.global_batch_size*args.train_iters +num_datasets = len(weights) + +print(f"Number of datasets: {num_datasets}") +print(f"Global batch size: {args.global_batch_size}") +print(f"Training iterations: {args.train_iters}") +train_valid_test_num_samples = [num_samples, 0, 0] +seed=args.seed +data_impl = args.data_impl +skip_warmup = False +seq_length = args.seq_length +splits_string = "1,0,0" + +# Build datasets +train_ds, valid_ds, test_ds = build_train_valid_test_datasets(files, data_impl, splits_string, + train_valid_test_num_samples, + seq_length, seed, skip_warmup, data_cache_path=args.data_cache_path) + +dataset_idx = [train_ds.dataset_index[i] for i in range(num_samples)] +ratio_select=np.zeros(num_datasets) +#for i in range(num_datasets): +# ratio_select[i] = np.sum([i==d for d in dataset_idx])/num_samples + +print(f"Total number of samples: {len(train_ds)}") +print(f"Weights set: {weights[:min(8, num_datasets)]}") +#print(f"Weights across training: {ratio_select[:min(8, num_datasets)]}") + +for e in range(min(100, args.train_iters)): + ratio_select=np.zeros(num_datasets) + for i in range(num_datasets): + ratio_select[i] = np.sum([i==d for d in dataset_idx[e*args.global_batch_size:(e+1)*args.global_batch_size]])/args.global_batch_size + print(f"iter-{e}: {ratio_select[:min(8, num_datasets)]}") + + +print("First 10 samples") +for i in range(10): + print(f"Sample: {i} \t dataset_idx: {train_ds.dataset_index[i]}, sample_idx: {train_ds.dataset_sample_index[i]}") + + +#### Build data loaders +train_dataloader = build_pretraining_data_loader( + train_ds, args.consumed_train_samples) +valid_dataloader = build_pretraining_data_loader( + valid_ds, args.consumed_valid_samples) +test_dataloader = build_pretraining_data_loader(test_ds, 0) From a4a08c9a9897ac6e883d97e3e0037268369d4cd3 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 28 Feb 2024 09:52:38 -0600 Subject: [PATCH 083/268] Update `train_llama_alcf_aurora.sh` --- train_llama_alcf_aurora.sh | 48 ++++++++++++++++++++------------------ 1 file changed, 25 insertions(+), 23 deletions(-) diff --git a/train_llama_alcf_aurora.sh b/train_llama_alcf_aurora.sh index 04341ca843..5bc9098b61 100644 --- a/train_llama_alcf_aurora.sh +++ b/train_llama_alcf_aurora.sh @@ -8,8 +8,8 @@ function sourceFile() { fp="$1" - echo "source-ing ${fp}" if [[ -f "${fp}" ]]; then + echo "Found ${fp}, \`source\`-ing" # shellcheck source="${fp}" source "${fp}" else @@ -21,29 +21,29 @@ function sourceFile() { # ---- source ./helpers_alcf.sh --------------------- HERE=$(python3 -c 'import os; print(os.getcwd())') sourceFile "${HERE}/helpers_alcf.sh" || exit - # cd ~/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed || exit # eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate anl_release_q4v2 -ezpz -setEnv -makeDSenv -makeHostfiles - -# ---- DATA SETUP ------------------------------------ -export DATA_FILE_LIST="./data_file_list_shuf_debug.txt" -NUM_DOCS=$(wc -l < "${DATA_FILE_LIST}") && export NUM_DOCS="${NUM_DOCS}" -WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" && export WEIGHT_SUM="${WEIGHT_SUM}" -DFL_STEM=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") && export DFL_STEM="${DFL_STEM}" -dcp="${HERE}/.cache/${DFL_STEM}-index-cache" -DATA_CACHE_PATH="${DATA_CACHE_PATH:-${dcp}}" && export DATA_CACHE_PATH="${DATA_CACHE_PATH}" -mkdir -p "${DATA_CACHE_PATH}" -if [[ -n "${DOLMA_CHUNK_IDX}" ]]; then - echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NUM_DOCS} documents..." -else - echo "Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" -fi -echo "DOCUMENT WEIGHT_SUM: ${WEIGHT_SUM}" -# ---------------------------------------------------- +ezpz || exit +setEnv || exit +saveDSenv || exit +makeHostfiles || exit +setupData "${DATA_FILE_LIST:-${HERE}/data_file_list_shuf_debug.txt}" || exit +# dfl_fallback="${HERE}/data_file_list_shuf_debug.txt" + +# # ---- DATA SETUP ------------------------------------ +# dfl_debug="./data_file_list_shuf_debug.txt" +# DATA_FILE_LIST="${DATA_FILE_LIST:-${dfl_debug}}" && export DATA_FILE_LIST="${DATA_FILE_LIST}" +# NUM_DOCS=$(wc -l < "${DATA_FILE_LIST}") && export NUM_DOCS="${NUM_DOCS}" +# WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" && export WEIGHT_SUM="${WEIGHT_SUM}" +# DFL_STEM=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") && export DFL_STEM="${DFL_STEM}" +# dcp="${HERE}/.cache/${DFL_STEM}-index-cache" +# DATA_CACHE_PATH="${DATA_CACHE_PATH:-${dcp}}" && export DATA_CACHE_PATH="${DATA_CACHE_PATH}" +# mkdir -p "${DATA_CACHE_PATH}" +# if [[ -n "${DOLMA_CHUNK_IDX}" ]]; then +# echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NUM_DOCS} documents..." +# else +# echo "Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" +# fi # ---- Parallelism Settings -------------------------- @@ -162,7 +162,9 @@ echo "++++++++++++++++++++++++++++++++++++++++++++++++++" echo "- WORLD_SIZE:${WORLD_SIZE}" echo "- BACKEND: ${BE}" echo "- MODEL_TYPE: ${MODEL_TYPE}" +echo "- DOCUMENT WEIGHT_SUM: ${WEIGHT_SUM}" echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" +echo "- Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" echo "++++++++++++++++++++++++++++++++++++++++++++++++++" run_cmd=" @@ -223,7 +225,7 @@ ds_report echo "${run_cmd}" -echo "[!! NOTE] View output at:" +printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" eval "${run_cmd}" From 0daba44f8961ae3650b8c0d3283dbb50cb9ba52e Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 28 Feb 2024 09:53:09 -0600 Subject: [PATCH 084/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index 96f6197637..e627c6f8bf 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -84,7 +84,6 @@ export EVAL_ITERS="${EVAL_ITERS:-10}" export TRAIN_ITER=${TRAIN_ITER:-317892} export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" export SAVE_INTERVAL=${SAVE_INTERVAL:-200} -export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) @@ -156,11 +155,11 @@ export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_B OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" export OUTPUT_DIR="${OUTPUT_DIR}" export OUTPUT_LOG="${OUTPUT_DIR}/output.log" +export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" echo "${OUTPUT_LOG}" >> "logs/latest" mkdir -p "${OUTPUT_DIR}" echo "!!!Please see logs at ${OUTPUT_DIR}" - # ---- Setup DeepSpeed arguments -------------------------------- ds_args=" " ds_args=" --deepspeed ${ds_args}" From 62ef3c5c39aa1cd05cd085497d845b2d1b083c84 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 28 Feb 2024 09:53:29 -0600 Subject: [PATCH 085/268] Remove old `set_params.sh` --- set_params.sh | 142 -------------------------------------------------- 1 file changed, 142 deletions(-) delete mode 100644 set_params.sh diff --git a/set_params.sh b/set_params.sh deleted file mode 100644 index 8682a86907..0000000000 --- a/set_params.sh +++ /dev/null @@ -1,142 +0,0 @@ -#!/bin/bash login -# echo "!!!please use generate_hostfile.sh to set hostfile for 18 nodes before training" -export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${PBS_NODEFILE}")} -export MICRO_BATCH=${MICRO_BATCH:-1} -export NLAYERS=${NLAYERS:-96} -export HIDDEN=${HIDDEN:-12288} -export HEADS=${HEADS:-96} -export LR=${LR:-0.0003} -export SEQ=${SEQ:-4096} -export TRAIN_ITER=${TRAIN_ITER:-300000} -export EVAL_ITERS=${EVAL_ITERS:-50} -export SAVE_INTERVAL=${SAVE_INTERVAL:-1000} -export EVAL_INTERVAL=${EVAL_INTERVAL:-50000} -export ZERO_STAGE=${ZERO_STAGE:-2} -export DTYPE=${DTYPE:-fp16} -export TP=${TP:-2} -export PP=${PP:-1} -export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} -export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) -export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} - -# echo "USING DATA_FILE_LIST: ${DATA_FILE_LIST}" || exit - - -# bash $LLM_DK_DIR/intel-extension-for-deepspeed/examples/gpt.sh $@ - -# Disabling tensor/pipeline parallelism -TP=${TP:-1} -PP=${PP:-1} - -DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" -bash ./generate_config.sh "${DS_CONFIG}" || exit 1 - -OUTPUT_PREFIX="logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" -# OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} -OUTPUT_DIR="${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" -mkdir -p "${OUTPUT_DIR}" -echo "!!!Please see logs at ${OUTPUT_DIR}" - -# Hostfile path -hostfile_deepspeed=./hostfile_deepspeed -hostfile_mpich=./hostfile_mpich -cat "$PBS_NODEFILE" > hostfile_mpich -cat "$PBS_NODEFILE" > hostfile_deepspeed ; sed -e 's/$/ slots=4/' -i hostfile_deepspeed - -ds_args=" " -ds_args=" --deepspeed ${ds_args}" -if [ "$PP" == 1 ]; then - ds_args=" --no-pipeline-parallel ${ds_args}" -fi -ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" -ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" - -if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then - echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" - ds_args=" --deepspeed-activation-checkpointing ${ds_args}" - # --checkpoint-activations \ - # --deepspeed-activation-checkpointing -fi - -gpt_args=() - -if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then - echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" - gpt_args+=( - "--checkpoint-activations" - "--checkpoint-num-layers 1" - ) -fi -# we are now using activation checkpoint provided by megatron, see below. -# ds_args=" --deepspeed-activation-checkpointing ${ds_args}" -# NUM_KV_HEADS="${NUM_KV_HEADS:-0}" -# if [[ $NUM_KV_HEADS -]] - -# take custom args -custom_args=" $@" - -# launcher setting -LAUNCHER=${LAUNCHER:-MPICH} -if [[ $LAUNCHER == "deepspeed" ]]; then - launcher="" -else - launcher="--force_multi --hostfile $hostfile_deepspeed --launcher=${LAUNCHER} --launcher_args='-hostfile ${hostfile_mpich}'" -fi - -NCCL=${NCCL:-nccl} - -# MODEL=LLAMA_7B -# OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_tp${TP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} - -# --vocab-file $VOCAB_FILE \ -# --merge-file $MERGE_FILE \ -# --lr-decay-iters 320000 \ -run_cmd=" - deepspeed $launcher pretrain_gpt_alcf.py \ - --tensor-model-parallel-size $TP \ - --pipeline-model-parallel-size $PP \ - --num-layers $NLAYERS \ - --hidden-size $HIDDEN \ - --num-attention-heads $HEADS \ - --seq-length $SEQ \ - --max-position-embeddings $SEQ \ - --micro-batch-size $MICRO_BATCH \ - --global-batch-size $GLOBAL_BATCH \ - --train-iters $TRAIN_ITER \ - --lr ${LR} \ - --lr-warmup-iters 5000 \ - --lr-decay-iters 10000 \ - --ffn-hidden-size 11008 \ - --lr-decay-style cosine \ - --data-impl mmap \ - --log-interval 1 \ - --eval-iters ${EVAL_ITERS} \ - --eval-interval ${EVAL_INTERVAL} \ - --save-interval ${SAVE_INTERVAL} \ - --split 90,5,5 \ - --$DTYPE \ - $ds_args \ - --no-masked-softmax-fusion \ - --no-bias-gelu-fusion \ - --no-bias-dropout-fusion \ - --no-gradient-accumulation-fusion \ - --distributed-backend $NCCL \ - --num-workers 0 \ - --tokenizer-type Llama2Tokenizer \ - --save checkpoints/${OUTPUT_PREFIX} \ - --load checkpoints/${OUTPUT_PREFIX} \ - --use-checkpoint-opt_param-scheduler \ - --accumulate-allreduce-grads-in-fp32 \ - --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ - --data-file-list ${DATA_FILE_LIST} \ - ${gpt_args[*]} \ - $custom_args \ - |& tee $OUTPUT_DIR/output.log - " - -echo "Using $(which deepspeed)" -ds_report - -echo ${run_cmd} -eval ${run_cmd} -set +x From 6676252a684a727591509b3dc4fb521a0c6de676 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 28 Feb 2024 09:54:36 -0600 Subject: [PATCH 086/268] Update `helpers_alcf.sh` --- helpers_alcf.sh | 72 ++++++++++++++++++++++++++++++++++++++++++++----- 1 file changed, 65 insertions(+), 7 deletions(-) diff --git a/helpers_alcf.sh b/helpers_alcf.sh index c0f3e467f9..e3df380828 100644 --- a/helpers_alcf.sh +++ b/helpers_alcf.sh @@ -29,6 +29,19 @@ saveDSenv() { } > .deepspeed_env } +# makeDSenv() { +# saveDSenv +# } + + +# makeDSenv() { +# echo "PATH=${PATH}" > .deepspeed_env +# echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> .deepspeed_env +# echo "http_proxy=${http_proxy}" >> .deepspeed_env +# echo "https_proxy=${https_proxy}" >> .deepspeed_env +# echo "CFLAGS=${CFLAGS}" >> .deepspeed_env +# echo "PYTHONUSERBASE=$PYTHONUSERBASE" >> .deepspeed_env +# } sumWeights() { local file_list=$1 @@ -108,11 +121,56 @@ makeHostfiles() { } -makeDSenv() { - echo "PATH=${PATH}" > .deepspeed_env - echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> .deepspeed_env - echo "http_proxy=${http_proxy}" >> .deepspeed_env - echo "https_proxy=${https_proxy}" >> .deepspeed_env - echo "CFLAGS=${CFLAGS}" >> .deepspeed_env - echo "PYTHONUSERBASE=$PYTHONUSERBASE" >> .deepspeed_env +setupData() { # dfl: abbrv. for DATA_FILE_LIST + dfl=$1 + printf "Calling: \`setupData()\` with %s\n" "${dfl}" + ndocs=$(wc -l < "${dfl}") + ws=$(sumWeights "${dfl}") + dfl_stem=$(echo "${dfl}" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") + dcp="${HERE}/.cache/${dfl_stem}/index-cache" + mkdir -p dcp + export DATA_FILE_LIST="${dfl}" + export NUM_DOCS="${ndocs}" + export WEIGHT_SUM="${ws}" + export DFL_STEM="${dfl_stem}" + export DATA_CACHE_PATH="${dcp}" + echo "--------------------" + echo "Updated environment:" + printf "DATA_FILE_LIST: %s\n" "${DATA_FILE_LIST}" + printf "NUM_DOCS: %s\n " "${NUM_DOCS}" + printf "WEIGHT_SUM: %s\n" "${WEIGHT_SUM}" + printf "DFL_STEM: %s\n" "${DFL_STEM}" + printf "DATA_CACHE_PATH: %s\n" "${DATA_CACHE_PATH}" + echo "--------------------" +} + +printBlack() { + printf "\e[1;30m%s\e[0m\n" "$@" +} + +printRed() { + printf "\e[1;31m%s\e[0m\n" "$@" +} + +printGreen() { + printf "\e[1;32m%s\e[0m\n" "$@" +} + +printYellow() { + printf "\e[1;33m%s\e[0m\n" "$@" +} + +printBlue() { + printf "\e[1;34m%s\e[0m\n" "$@" +} + +printMagenta() { + printf "\e[1;35m%s\e[0m\n" "$@" +} + +printCyan() { + printf "\e[1;36m%s\e[0m\n" "$@" +} +printWhite() { + printf "\e[1;37m%s\e[0m\n" "$@" } From 747b568bc79543e85817fcd4238509b2a6d05868 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 28 Feb 2024 09:55:47 -0600 Subject: [PATCH 087/268] Update `.gitignore` --- .gitignore | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.gitignore b/.gitignore index 610af67ac3..3e46cef4c5 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,6 @@ +.deepspeed_env +*.bak +.cache/* outputs/ venvs/ wandb/ From 25358b7962c88a3923c10848f413643dc1e6ef44 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Wed, 28 Feb 2024 11:35:58 -0600 Subject: [PATCH 088/268] fixed int8 issue --- megatron/data/blendable_dataset.py | 3 +-- megatron/data/helpers.cpp | 6 +++--- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/megatron/data/blendable_dataset.py b/megatron/data/blendable_dataset.py index 2516e58415..f3276c6823 100644 --- a/megatron/data/blendable_dataset.py +++ b/megatron/data/blendable_dataset.py @@ -34,8 +34,7 @@ def __init__(self, datasets, weights, size, *, # Build indicies. def _build_indices(): start_time = time.time() - assert num_datasets < 255 - dataset_index = np.zeros(self.size, dtype=np.uint8) + dataset_index = np.zeros(self.size, dtype=np.int64) dataset_sample_index = np.zeros(self.size, dtype=np.int64) from megatron.data import helpers diff --git a/megatron/data/helpers.cpp b/megatron/data/helpers.cpp index 5c3a054875..142f159dd3 100644 --- a/megatron/data/helpers.cpp +++ b/megatron/data/helpers.cpp @@ -17,10 +17,10 @@ using namespace std; const int32_t LONG_SENTENCE_LEN = 512; -void build_blending_indices(py::array_t& dataset_index, +void build_blending_indices(py::array_t& dataset_index, py::array_t& dataset_sample_index, const py::array_t& weights, - const int32_t num_datasets, + const int64_t num_datasets, const int64_t size, const bool verbose) { /* Given multiple datasets and a weighting array, build samples such that it follows those wieghts.*/ @@ -58,7 +58,7 @@ void build_blending_indices(py::array_t& dataset_index, } // Populate the indices. - dataset_index_ptr[sample_idx] = static_cast(max_error_index); + dataset_index_ptr[sample_idx] = static_cast(max_error_index); dataset_sample_index_ptr[sample_idx] = current_samples[max_error_index]; // Update the total samples. From 45a3428ee6d92a8355da0d7d1f227a160bb76553 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 28 Feb 2024 12:35:57 -0600 Subject: [PATCH 089/268] Move `helpers_alcf.sh -> ALCF_utils/helpers_alcf.sh` --- helpers_alcf.sh => ALCF_utils/helpers_alcf.sh | 44 +++++++++---------- 1 file changed, 22 insertions(+), 22 deletions(-) rename helpers_alcf.sh => ALCF_utils/helpers_alcf.sh (82%) diff --git a/helpers_alcf.sh b/ALCF_utils/helpers_alcf.sh similarity index 82% rename from helpers_alcf.sh rename to ALCF_utils/helpers_alcf.sh index e3df380828..b70ac43407 100644 --- a/helpers_alcf.sh +++ b/ALCF_utils/helpers_alcf.sh @@ -59,28 +59,28 @@ sumFiles() { done } -setupData() { - cidx=$1 - echo "Caught DOLMA_CHUNK_IDX: ${cidx} !!" - dfl="./chunks-reweighted/10/data_file_list_chunk_${cidx}_of_10.txt" - if [[ -z "${DATA_FILE_LIST}" ]]; then - DATA_FILE_LIST="${dfl}" - else - echo "Caught DATA_FILE_LIST: ${DATA_FILE_LIST} from ENV!!" - fi - NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" - WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" - export WEIGHT_SUM="${WEIGHT_SUM}" - export NDOCS="${NDOCS}" - echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST} with ${NDOCS} documents" - echo "WEIGHT SUM: ${WEIGHT_SUM}" - data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") - export DOLMA_CHUNK_IDX="${cidx}" - export DATA_FILE_LIST_STEM="${data_file_list_stem}" - export DATA_CACHE_PATH=".cache/${data_file_list_stem}/index-cache" - mkdir -p "${DATA_CACHE_PATH}" -} - +# setupData() { +# cidx=$1 +# echo "Caught DOLMA_CHUNK_IDX: ${cidx} !!" +# dfl="./chunks-reweighted/10/data_file_list_chunk_${cidx}_of_10.txt" +# if [[ -z "${DATA_FILE_LIST}" ]]; then +# DATA_FILE_LIST="${dfl}" +# else +# echo "Caught DATA_FILE_LIST: ${DATA_FILE_LIST} from ENV!!" +# fi +# NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" +# WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" +# export WEIGHT_SUM="${WEIGHT_SUM}" +# export NDOCS="${NDOCS}" +# echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST} with ${NDOCS} documents" +# echo "WEIGHT SUM: ${WEIGHT_SUM}" +# data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") +# export DOLMA_CHUNK_IDX="${cidx}" +# export DATA_FILE_LIST_STEM="${data_file_list_stem}" +# export DATA_CACHE_PATH=".cache/${data_file_list_stem}/index-cache" +# mkdir -p "${DATA_CACHE_PATH}" +# } +# setEnv() { From a907b47813900c44aef15c13cc3c9ef3026a0544 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Wed, 28 Feb 2024 13:57:46 -0600 Subject: [PATCH 090/268] modifying testing dataset --- ALCF_utils/test_blend_full.sh | 73 ++++++++++++++++++++++++++++ ALCF_utils/test_blendable_dataset.py | 2 +- 2 files changed, 74 insertions(+), 1 deletion(-) create mode 100755 ALCF_utils/test_blend_full.sh diff --git a/ALCF_utils/test_blend_full.sh b/ALCF_utils/test_blend_full.sh new file mode 100755 index 0000000000..719ebb4151 --- /dev/null +++ b/ALCF_utils/test_blend_full.sh @@ -0,0 +1,73 @@ +#!/bin/bash +#PBS -l walltime=0:30:00 +#PBS -A datascience +#PBS -q debug +#PBS -l select=1 +#PBS -l filesystems=eagle:grand:home +cd ${PBS_O_WORKDIR} +export PPN=4 +export MD=/home/hzheng/ALCF-Megatron-DeepSpeed +module load conda/2023-10-04 +#conda activate /soft/datascience/megatron-deepspeed/2023-10-04 +conda activate $HOME/PolarisAT/pyenvs/megatron/2023-10-04 +export TP=1 +export PP=1 +export SP=128 +export MBS=1 +export BS=$((MBS*SP)) +export export DATE_TAG=$(date +"%Y-%m-%d-%H-%M-%S") +export DATA_FILE_LIST="/eagle/datasets//dolma/data_file_list_reweighted.txt" + +HIDDEN_SIZE=4096 +NUM_LAYERS=32 +SEQ_LENGTH=2048 +EMBEDDINGS=2048 +TRAIN_ITERS=10 +ZERO_STAGE=2 +MODEL=LLAMA_7B +OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} +#MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --cpu-bind depth -d 16 --hostfile $PBS_NODEFILE +python3 ./test_blendable_dataset.py \ + --tensor-model-parallel-size ${TP} \ + --pipeline-model-parallel-size ${PP} \ + --num-layers ${NUM_LAYERS} \ + --hidden-size ${HIDDEN_SIZE} \ + --ffn-hidden-size 5504 \ + --num-attention-heads 32 \ + --micro-batch-size ${MBS} \ + --global-batch-size ${BS} \ + --seq-length ${SEQ_LENGTH} \ + --max-position-embeddings ${EMBEDDINGS} \ + --train-iters 80797 \ + --save ${MD}/checkpoints/${OUTPUT_PREFIX} \ + --load ${MD}/checkpoints/${OUTPUT_PREFIX} \ + --tokenizer-type Llama2Tokenizer \ + --split 949,50,1 \ + --distributed-backend nccl \ + --lr 3e-4 \ + --lr-decay-style cosine \ + --min-lr 3e-5 \ + --weight-decay 0.1 \ + --clip-grad 1 \ + --lr-warmup-iters 2 \ + --optimizer adam \ + --adam-beta1 0.9 \ + --adam-beta2 0.95 \ + --log-interval 1 \ + --cpu-optimizer \ + --save-interval 10000 \ + --eval-interval 1000 \ + --eval-iters 10 --fp16 \ + --no-query-key-layer-scaling \ + --attention-dropout 0 \ + --hidden-dropout 0 \ + --use-rotary-position-embeddings \ + --tokenizer-model /eagle/datasets/dolma/utils/tokenizer.model \ + --untie-embeddings-and-output-weights \ + --swiglu --normalization layernorm --disable-bias-linear --num-key-value-heads 4 \ + --tensorboard-dir ./outputs/${OUTPUT_PREFIX}/tensorboard --log-timers-to-tensorboard --tensorboard-log-interval 1 \ + --data-file-list ${DATA_FILE_LIST} \ + --data-path ${DATA_PATH} \ + --data-cache-path /tmp/hzheng-megatron-deepspeed-cache/ \ + --vocab-file ${MD}/dataset/gpt2-vocab.json --merge-file ${MD}/dataset/gpt2-merges.txt \ + --zero-stage=${ZERO_STAGE} --deepspeed_config=${MD}/ds_config-gpt.json --deepspeed diff --git a/ALCF_utils/test_blendable_dataset.py b/ALCF_utils/test_blendable_dataset.py index 1cf40c5aaf..a0cccbb6cb 100644 --- a/ALCF_utils/test_blendable_dataset.py +++ b/ALCF_utils/test_blendable_dataset.py @@ -35,7 +35,7 @@ train_valid_test_num_samples = [num_samples, 0, 0] seed=args.seed data_impl = args.data_impl -skip_warmup = False +skip_warmup = not args.mmap_warmup seq_length = args.seq_length splits_string = "1,0,0" From 9435b633c39559e1d96d0b651747e0a7673b1642 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 28 Feb 2024 14:21:37 -0600 Subject: [PATCH 091/268] Update `train_llama_alcf_aurora.sh` --- train_llama_alcf_aurora.sh | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/train_llama_alcf_aurora.sh b/train_llama_alcf_aurora.sh index 5bc9098b61..dca3e17243 100644 --- a/train_llama_alcf_aurora.sh +++ b/train_llama_alcf_aurora.sh @@ -19,15 +19,16 @@ function sourceFile() { # +++++++++++++++ SCRIPT START ++++++++++++++++++++++ # ---- source ./helpers_alcf.sh --------------------- +cd "${PBS_O_WORKDIR}" || exit HERE=$(python3 -c 'import os; print(os.getcwd())') -sourceFile "${HERE}/helpers_alcf.sh" || exit +sourceFile "${HERE}/ALCF_utils/helpers_alcf.sh" || exit # cd ~/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed || exit # eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate anl_release_q4v2 ezpz || exit setEnv || exit saveDSenv || exit makeHostfiles || exit -setupData "${DATA_FILE_LIST:-${HERE}/data_file_list_shuf_debug.txt}" || exit +setupData "${DATA_FILE_LIST:-${HERE}/data_file_list_reweighted.txt}" || exit # dfl_fallback="${HERE}/data_file_list_shuf_debug.txt" # # ---- DATA SETUP ------------------------------------ From fdf19045cfd3430d72e4b33e16a9eb45af410e97 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 28 Feb 2024 15:03:33 -0600 Subject: [PATCH 092/268] Set `skip_warmup=True` in `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 936ea5ec4b..4fefef795f 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -487,7 +487,8 @@ def train_valid_test_datasets_provider(train_val_test_num_samples): train_valid_test_num_samples=train_val_test_num_samples, seq_length=args.seq_length, seed=args.seed, - skip_warmup=(not args.mmap_warmup), + skip_warmup=True, + # skip_warmup=(not args.mmap_warmup), train_data_prefix=args.train_data_path, valid_data_prefix=args.valid_data_path, test_data_prefix=args.test_data_path, From 802a6e896a0fbf91bc0503696c901b36b9f2b5d5 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Wed, 28 Feb 2024 17:05:26 -0600 Subject: [PATCH 093/268] test_blend_full --- ALCF_utils/test_blend_full.sh | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/ALCF_utils/test_blend_full.sh b/ALCF_utils/test_blend_full.sh index 719ebb4151..4245304456 100755 --- a/ALCF_utils/test_blend_full.sh +++ b/ALCF_utils/test_blend_full.sh @@ -22,12 +22,11 @@ HIDDEN_SIZE=4096 NUM_LAYERS=32 SEQ_LENGTH=2048 EMBEDDINGS=2048 -TRAIN_ITERS=10 +TRAIN_ITERS=80797 ZERO_STAGE=2 MODEL=LLAMA_7B OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} -#MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --cpu-bind depth -d 16 --hostfile $PBS_NODEFILE -python3 ./test_blendable_dataset.py \ +python3 ALCF_utils/test_blendable_dataset.py \ --tensor-model-parallel-size ${TP} \ --pipeline-model-parallel-size ${PP} \ --num-layers ${NUM_LAYERS} \ @@ -38,7 +37,7 @@ python3 ./test_blendable_dataset.py \ --global-batch-size ${BS} \ --seq-length ${SEQ_LENGTH} \ --max-position-embeddings ${EMBEDDINGS} \ - --train-iters 80797 \ + --train-iters ${TRAIN_ITERS} \ --save ${MD}/checkpoints/${OUTPUT_PREFIX} \ --load ${MD}/checkpoints/${OUTPUT_PREFIX} \ --tokenizer-type Llama2Tokenizer \ @@ -52,6 +51,7 @@ python3 ./test_blendable_dataset.py \ --lr-warmup-iters 2 \ --optimizer adam \ --adam-beta1 0.9 \ + --mmap_warmup False \ --adam-beta2 0.95 \ --log-interval 1 \ --cpu-optimizer \ From 6b33b81649c1636be0bb3c62ba8f1ed5bcb54198 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Fri, 1 Mar 2024 09:28:37 -0600 Subject: [PATCH 094/268] changed multiprocessing context --- megatron/data/data_samplers.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/megatron/data/data_samplers.py b/megatron/data/data_samplers.py index 2d7da67e15..623e19e70e 100644 --- a/megatron/data/data_samplers.py +++ b/megatron/data/data_samplers.py @@ -44,7 +44,7 @@ def build_pretraining_data_loader(dataset, consumed_samples): loader = torch.utils.data.DataLoader(dataset, batch_sampler=batch_sampler, num_workers=args.num_workers, - pin_memory=True) + pin_memory=True, multiprocessing_context='spawn') if args.repeated_dataloader: loader=RepeatingLoader(loader) return loader @@ -187,4 +187,4 @@ def __iter__(self): if len(batch) == self.micro_batch_size: self.consumed_samples += self.micro_batch_times_data_parallel_size yield batch - batch = [] \ No newline at end of file + batch = [] From ea9f6e3cb2edf2fd06cd7eda43cae8a8b39faa6b Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 4 Mar 2024 16:13:49 -0600 Subject: [PATCH 095/268] Update Aurora qsub scripts --- train_llama_alcf_aurora.sh | 3 ++- train_llama_alcf_aurora_qsub.sh | 7 +++++++ 2 files changed, 9 insertions(+), 1 deletion(-) create mode 100755 train_llama_alcf_aurora_qsub.sh diff --git a/train_llama_alcf_aurora.sh b/train_llama_alcf_aurora.sh index dca3e17243..48651dbeb1 100644 --- a/train_llama_alcf_aurora.sh +++ b/train_llama_alcf_aurora.sh @@ -204,8 +204,9 @@ run_cmd=" ${LLAMA_ARGS} \ ${gpt_args[*]} \ $custom_args \ - >> ${OUTPUT_LOG} 2>&1 & + |& tee ${OUTPUT_LOG} " + # >> ${OUTPUT_LOG} 2>&1 & # |& tee $OUTPUT_DIR/output.log # --ffn-hidden-size 11008 \ diff --git a/train_llama_alcf_aurora_qsub.sh b/train_llama_alcf_aurora_qsub.sh new file mode 100755 index 0000000000..6f247da9c8 --- /dev/null +++ b/train_llama_alcf_aurora_qsub.sh @@ -0,0 +1,7 @@ +#!/bin/bash --login + + +cd "${PBS_O_WORKDIR}" || exit +eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate anl_release_q4v2 +source /home/foremans/anl_24_release_q4/llm.devkit/setenv.sh +bash ./train_llama_alcf_aurora.sh From 67914f3dce062615dca18e89b7f42edb133a42c1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 5 Mar 2024 16:42:07 -0600 Subject: [PATCH 096/268] Update `megatron/data/data_samplers.py` --- megatron/data/data_samplers.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/megatron/data/data_samplers.py b/megatron/data/data_samplers.py index 623e19e70e..8eb2f2a668 100644 --- a/megatron/data/data_samplers.py +++ b/megatron/data/data_samplers.py @@ -41,10 +41,13 @@ def build_pretraining_data_loader(dataset, consumed_samples): args.dataloader_type)) # Torch dataloader. - loader = torch.utils.data.DataLoader(dataset, - batch_sampler=batch_sampler, - num_workers=args.num_workers, - pin_memory=True, multiprocessing_context='spawn') + loader = torch.utils.data.DataLoader( + dataset, + batch_sampler=batch_sampler, + num_workers=args.num_workers, + pin_memory=True, + # multiprocessing_context='spawn' + ) if args.repeated_dataloader: loader=RepeatingLoader(loader) return loader From 9f84633a28ceae0e4e6d1c2b7f1eacb0fcfa9083 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 6 Mar 2024 21:53:47 -0600 Subject: [PATCH 097/268] Add `ALCF_utils/data_file_list_polaris.txt` --- ALCF_utils/data_file_list_polaris.txt | 3074 +++++++++++++++++++++++++ 1 file changed, 3074 insertions(+) create mode 100644 ALCF_utils/data_file_list_polaris.txt diff --git a/ALCF_utils/data_file_list_polaris.txt b/ALCF_utils/data_file_list_polaris.txt new file mode 100644 index 0000000000..bac6e0cb33 --- /dev/null +++ b/ALCF_utils/data_file_list_polaris.txt @@ -0,0 +1,3074 @@ +0.00029986601436087147 /eagle/datasets//dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/cc_en_middle-0553_text_document +0.00025354733193980704 /eagle/datasets//dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/cc_en_middle-0299_text_document +0.00022796278454747796 /eagle/datasets//dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/cc_en_middle-0366_text_document +0.00015898148098181938 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/eagle/datasets/dolma/data_Llama2Tokenizer_stackcode_fused_5GB/fused_52_text_document From 6bcac4ee574da196d0d7da548693b2e8f62e0146 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 6 Mar 2024 22:17:16 -0600 Subject: [PATCH 098/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 78 +++++++++++++------------------------ 1 file changed, 26 insertions(+), 52 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index e627c6f8bf..b990cc124d 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -5,6 +5,7 @@ #PBS -l select=48 #PBS -l filesystems=eagle:home + function sourceFile() { fp="$1" echo "source-ing ${fp}" @@ -17,42 +18,27 @@ function sourceFile() { } # +++++++++++++++ SCRIPT START ++++++++++++++++++++++ -# ---- source ./helpers_alcf.sh --------------------- +cd "${PBS_O_WORKDIR}" || exit HERE=$(python3 -c 'import os; print(os.getcwd())') -sourceFile "${HERE}/helpers_alcf.sh" || exit +sourceFile "${HERE}/ALCF_utils/helpers_alcf.sh" || exit + +# ---- fns from ./helpers_alcf.sh ------------------- +setEnv || exit +saveDSenv || exit +ezpz || exit +makeHostfiles || exit +DFL="/eagle/datasets/dolma/data_file_list_reweighted.txt" +setupData "${DATA_FILE_LIST:-${DFL}}" || exit -# ---- load conda ----------------------------------- -module load conda/2023-10-04; conda activate base -if [[ "${VIRTUAL_ENV}" ]]; then - echo "Caught VIRTUAL_ENV = ${VIRTUAL_ENV} from environment!!" -else - echo "Not using VIRTUAL_ENV" - # sourceFile "${HERE}/venvs/polaris/2023-10-04/bin/activate" || exit -fi echo "Using $(which python3)" -# ---- fns from ./helpers_alcf.sh ------------------- -ezpz -makeHostfiles -saveDSenv -# setupData "${DOLMA_CHUNK_IDX:-00}" -# export DOLMA_CHUNK_IDX="${DOLMA_CHUNK_IDX:-0}" -# -# ---- DATA SETUP ------------------------------------ -dfl_debug="./data_file_list_shuf_debug.txt" -DATA_FILE_LIST="${DATA_FILE_LIST:-${dfl_debug}}" && export DATA_FILE_LIST="${DATA_FILE_LIST}" -NUM_DOCS=$(wc -l < "${DATA_FILE_LIST}") && export NUM_DOCS="${NUM_DOCS}" -WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" && export WEIGHT_SUM="${WEIGHT_SUM}" -DFL_STEM=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") && export DFL_STEM="${DFL_STEM}" -dcp="${HERE}/.cache/${DFL_STEM}-index-cache" -DATA_CACHE_PATH="${DATA_CACHE_PATH:-${dcp}}" && export DATA_CACHE_PATH="${DATA_CACHE_PATH}" -mkdir -p "${DATA_CACHE_PATH}" -if [[ -n "${DOLMA_CHUNK_IDX}" ]]; then - echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NUM_DOCS} documents..." -else - echo "Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" -fi -echo "DOCUMENT WEIGHT_SUM: ${WEIGHT_SUM}" +# mkdir -p "${DATA_CACHE_PATH}" +# if [[ -n "${DOLMA_CHUNK_IDX}" ]]; then +# echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NUM_DOCS} documents..." +# else +# echo "Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" +# fi +# echo "DOCUMENT WEIGHT_SUM: ${WEIGHT_SUM}" # ---------------------------------------------------- # ---- Parallelism Settings -------------------------- @@ -65,6 +51,7 @@ export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} # ---------------------------------------------------- # ---- Llama2 7B Config ------------------------------ +export MODEL_KEY="Llama-7B" export HEADS=${HEADS:-32} export NLAYERS=${NLAYERS:-32} export HIDDEN=${HIDDEN:-4096} @@ -73,7 +60,7 @@ export FFN_HIDDEN_SIZE=${FFN_HIDDEN_SIZE:-11008} # ---------------------------------------------------- # ---- Run Settings ---------------------------------- -export LR=${LR:-0.00015} +export LR=${LR:-0.0003} export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 export ZERO_STAGE=${ZERO_STAGE:-2} @@ -99,21 +86,6 @@ echo "- MODEL_TYPE: ${MODEL_TYPE}" echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" echo "++++++++++++++++++++++++++++++++++++++++++++++++++" -# if [[ "${DOLMA_CHUNK_IDX}" == 0 ]]; then -# TRAIN_ITER=78739 -# elif [[ "${DOLMA_CHUNK_IDX}" == 1 ]]; then -# TRAIN_ITER=81008 -# elif [[ "${DOLMA_CHUNK_IDX}" == 2 ]]; then -# TRAIN_ITER=79591 -# elif [[ "${DOLMA_CHUNK_IDX}" == 3 ]]; then -# TRAIN_ITER=78552 -# else -# echo "caught DOLMA_CHUNK_IDX=${DOLMA_CHUNK_IDX}" -# TRAIN_ITER="${TRAIN_ITER:-320000}" -# echo "Setting TRAIN_ITER=${TRAIN_ITER}" -# # echo "Unknown DOLMA_CHUNK_IDX: ${DOLMA_CHUNK_IDX}" -# fi - # +++++NOTES ++++++++++++++++++++++++++++++++++++++++++++++++++ # XXX: # - need to merge *.json files @@ -211,7 +183,6 @@ EXEC="pretrain_gpt_alcf.py" # --vocab-file $VOCAB_FILE \ # --merge-file $MERGE_FILE \ # --lr-decay-iters 320000 \ - # --num-workers 0 \ # --lr-warmup-iters 5000 \ # --lr-decay-iters 10000 \ # --num-workers 4 \ @@ -220,7 +191,7 @@ EXEC="pretrain_gpt_alcf.py" run_cmd=" deepspeed $launcher ${EXEC} \ --$DTYPE \ - --split 90,5,5 \ + --split 100,0,0 \ --use-flash-attn-v2 \ --no-bias-gelu-fusion \ --lr-decay-style cosine \ @@ -232,6 +203,7 @@ run_cmd=" --use-checkpoint-opt_param-scheduler \ --lr ${LR} \ --log-interval 1 \ + --num-workers 0 \ --seq-length $SEQ \ --save ${CKPT_DIR} \ --load ${CKPT_DIR} \ @@ -257,8 +229,10 @@ run_cmd=" ${LLAMA_ARGS} \ ${gpt_args[*]} \ $custom_args \ - >> ${OUTPUT_LOG} 2>&1 & + |& tee ${OUTPUT_LOG} " + # >> ${OUTPUT_LOG} 2>&1 & + # >> ${OUTPUT_LOG} 2>&1 & # |& tee $OUTPUT_DIR/output.log # ${EXTRA_ARGS} \ @@ -268,7 +242,7 @@ ds_report echo "${run_cmd}" -echo "[!! NOTE] View output at:" +printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" # echo "${OUTPUT_LOG}" eval "${run_cmd}" From e7d76d3904c7b0b8cc5dedcb4290a6def5d812e3 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 10:27:39 -0600 Subject: [PATCH 099/268] Move `ALCF_utils/*` to `ALCF/*` - move (existing) contents from `ALCF/*` to `ALCF/pre-AuroraGPT/*` - Rename `ALCF_utils/helpers_alcf.sh` -> `ALCF/helpers.sh` --- {ALCF_utils => ALCF}/fused_stackcode.py | 0 .../fused_stackcode_bysize.py | 0 ALCF/helpers.sh | 351 ++ ALCF/{ => pre-AuroraGPT}/README.md | 0 ALCF/{ => pre-AuroraGPT}/args.sh | 0 ALCF/{ => pre-AuroraGPT}/launch.sh | 0 ALCF/{ => pre-AuroraGPT}/llama2_vars.sh | 0 ALCF/{ => pre-AuroraGPT}/model.sh | 0 ALCF/{ => pre-AuroraGPT}/setup.sh | 0 ALCF/{ => pre-AuroraGPT}/submit-pbs.sh | 0 ALCF/{ => pre-AuroraGPT}/submit.sh | 0 ALCF/{ => pre-AuroraGPT}/train-gpt3.sh | 0 ALCF/{ => pre-AuroraGPT}/train-llama.sh | 0 {ALCF_utils => ALCF}/test_blend.sh | 0 {ALCF_utils => ALCF}/test_blend_full.sh | 0 .../test_blendable_dataset.py | 0 ALCF_utils/data_file_list_polaris.txt | 3074 ----------------- ALCF_utils/helpers_alcf.sh | 176 - 18 files changed, 351 insertions(+), 3250 deletions(-) rename {ALCF_utils => ALCF}/fused_stackcode.py (100%) rename {ALCF_utils => ALCF}/fused_stackcode_bysize.py (100%) create mode 100644 ALCF/helpers.sh rename ALCF/{ => pre-AuroraGPT}/README.md (100%) rename ALCF/{ => pre-AuroraGPT}/args.sh (100%) rename ALCF/{ => pre-AuroraGPT}/launch.sh (100%) rename ALCF/{ => pre-AuroraGPT}/llama2_vars.sh (100%) rename ALCF/{ => pre-AuroraGPT}/model.sh (100%) rename ALCF/{ => pre-AuroraGPT}/setup.sh (100%) rename ALCF/{ => pre-AuroraGPT}/submit-pbs.sh (100%) rename ALCF/{ => pre-AuroraGPT}/submit.sh (100%) rename ALCF/{ => pre-AuroraGPT}/train-gpt3.sh (100%) rename ALCF/{ => pre-AuroraGPT}/train-llama.sh (100%) rename {ALCF_utils => ALCF}/test_blend.sh (100%) rename {ALCF_utils => ALCF}/test_blend_full.sh (100%) rename {ALCF_utils => ALCF}/test_blendable_dataset.py (100%) delete mode 100644 ALCF_utils/data_file_list_polaris.txt delete mode 100644 ALCF_utils/helpers_alcf.sh diff --git a/ALCF_utils/fused_stackcode.py b/ALCF/fused_stackcode.py similarity index 100% rename from ALCF_utils/fused_stackcode.py rename to ALCF/fused_stackcode.py diff --git a/ALCF_utils/fused_stackcode_bysize.py b/ALCF/fused_stackcode_bysize.py similarity index 100% rename from ALCF_utils/fused_stackcode_bysize.py rename to ALCF/fused_stackcode_bysize.py diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh new file mode 100644 index 0000000000..6ff3447f05 --- /dev/null +++ b/ALCF/helpers.sh @@ -0,0 +1,351 @@ +#!/bin/bash --login + +buildCLIargs() { + custom_args=" $@" + export CLI_ARGS=" + --$DTYPE \ + --num-workers 0 \ + --split 100,0,0 \ + --log-interval 1 \ + --use-flash-attn-v2 \ + --no-bias-gelu-fusion \ + --lr-decay-style cosine \ + --no-bias-dropout-fusion \ + --no-masked-softmax-fusion \ + --tokenizer-type Llama2Tokenizer \ + --no-gradient-accumulation-fusion \ + --accumulate-allreduce-grads-in-fp32 \ + --use-checkpoint-opt_param-scheduler \ + --lr ${LR} \ + --save ${CKPT_DIR} \ + --load ${CKPT_DIR} \ + --seq-length ${SEQ} \ + --num-layers ${NLAYERS} \ + --hidden-size ${HIDDEN} \ + --train-iters ${TRAIN_ITER} \ + --eval-iters ${EVAL_ITERS} \ + --distributed-backend ${NCCL} \ + --num-attention-heads ${HEADS} \ + --save-interval ${SAVE_INTERVAL} \ + --eval-interval ${EVAL_INTERVAL} \ + --max-position-embeddings ${SEQ} \ + --micro-batch-size ${MICRO_BATCH} \ + --data-file-list ${DATA_FILE_LIST} \ + --tensor-model-parallel-size ${TP} \ + --global-batch-size ${GLOBAL_BATCH} \ + --pipeline-model-parallel-size ${PP} \ + --num-key-value-heads ${NUM_KV_HEAD} \ + --data-cache-path ${DATA_CACHE_PATH} \ + --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ + --tokenizer-model ${TOKENIZER_MODEL} \ + $ds_args \ + ${LLAMA_ARGS} \ + ${gpt_args[*]} \ + ${custom_args} \ + " +} + +printJobInfo() { + echo "++++++++++++++++++++++++++++++++++++++++++++++++++" + echo "- MPICH_DIR=$MPICH_DIR" + echo "- Using $(which python3)" + echo "- WORLD_SIZE:${WORLD_SIZE}" + echo "- NCCL: ${NCCL:-nccl}" + echo "- MODEL_TYPE: ${MODEL_TYPE}" + echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" + echo "++++++++++++++++++++++++++++++++++++++++++++++++++" +} + +function setDSlauncher() { + # launcher setting + outdir=$1 + # hfds=$1 + # hfmpi=$2 + # here=$(python3 -c 'import os; print(os.getcwd())') + export hfds="$outdir/hostfile_deepspeed" + export hfmpi="$outdir/hostfile_mpich" + [ -f "$hfds" ] || exit + [ -f "$hfmpi" ] || exit + export LAUNCHER=${LAUNCHER:-MPICH} + if [[ $LAUNCHER == "deepspeed" ]]; then + export launcher="" + else + export launcher="--force_multi --hostfile $hfds --launcher=${LAUNCHER} --launcher_args='-hostfile ${hfmpi}'" + fi +} + +setParams() { + # [Parallelism Settings] {{{ + if [[ $(hostname) == x4* ]]; then # ---- [AURORA] ---- + TP=${TP:-1} # • TP = 1 + PP=${PP:-1} # • PP = 1 + export CCL=${CCL:-ccl} # • CCL + export BE="${CCL}" # • BE = CCL + export DTYPE=${DTYPE:-bf16} # • DTYPE: bf16 + elif [[ $(hostname) == x3* ]]; then # ---- [POLARIS] ---- + PP=${PP:-1} # • PP = 1 + TP=${TP:-2} # • TP = 2 + export NCCL=${NCCL:-nccl} # • NCCL + export BE="${NCCL}" # • BE = NCCL + export DTYPE=${DTYPE:-fp16} # • DTYPE: FP16 + fi + # }}} + export PP="${PP}" + export TP="${TP}" + export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" + export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} + # ---- Llama2 7B Config ------------------------------ + export MODEL_KEY="Llama-7B" + export HEADS=${HEADS:-32} + export NLAYERS=${NLAYERS:-32} + export HIDDEN=${HIDDEN:-4096} + export NUM_KV_HEAD=${NUM_KV_HEAD:-8} + export FFN_HIDDEN_SIZE=${FFN_HIDDEN_SIZE:-11008} + # ---- Run Settings ---------------------------------- + export LR=${LR:-0.0003} + export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 + export ZERO_STAGE=${ZERO_STAGE:-2} + export MICRO_BATCH=${MICRO_BATCH:-8} + export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} + export EVAL_ITERS="${EVAL_ITERS:-10}" + export TRAIN_ITER=${TRAIN_ITER:-317892} + export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" + export SAVE_INTERVAL=${SAVE_INTERVAL:-200} + export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} + # export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} + export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) + export TOKENIZER_MODEL="${TOKENIZER_MODEL:-"/eagle/datasets/dolma/utils/tokenizer.model"}" + export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" + export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" + # ---------------------------------------------------- +} + + +setArgs() { + # ---- Set DeepSpeed arguments -------------------------------- + ds_args=" " + ds_args=" --deepspeed ${ds_args}" + if [[ $PP == 1 ]]; then + ds_args=" --no-pipeline-parallel ${ds_args}" + fi + ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" + ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" + if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" + ds_args=" --deepspeed-activation-checkpointing ${ds_args}" + # --checkpoint-activations \ + # --deepspeed-activation-checkpointing + fi + export ds_args + # --------------------------------------------------------------- + gpt_args=() + # we are now using activation checkpoint provided by megatron, see below. + # ds_args=" --deepspeed-activation-checkpointing ${ds_args}" + if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then + echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" + gpt_args+=( + "--checkpoint-activations" + "--checkpoint-num-layers 1" + ) + fi + export gpt_args +} + +ezpz() { + if [[ ! -d ezpz ]]; then + git clone https://github.com/saforem2/ezpz + else + echo "Found ezpz!" + fi + if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then + echo "Has ezpz installed. Nothing to do." + else + echo "Does not have ezpz installed. Installing..." + echo "Using $(which python3) to install \`ezpz\`:" + python3 -m pip install -e ezpz > ezpz-install.log 2>&1 + fi + source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit + source ezpz/src/ezpz/bin/getjobenv || exit +} + +saveDSenv() { + echo "Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env" + { + echo "PATH=${PATH}" ; + echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" ; + echo "http_proxy=${http_proxy}" ; + echo "https_proxy=${https_proxy}" ; + echo "CFLAGS=${CFLAGS}" ; + echo "PYTHONUSERBASE=$PYTHONUSERBASE" ; + } > .deepspeed_env +} + +setOutput() { + # ---- Specify output location -------------------------------- + export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" + # OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} + OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" + export OUTPUT_DIR="${OUTPUT_DIR}" + export OUTPUT_LOG="${OUTPUT_DIR}/output.log" + export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" + echo "${OUTPUT_LOG}" >> "logs/latest" + mkdir -p "${OUTPUT_DIR}" + echo "!!!Please see logs at ${OUTPUT_DIR}" +} + +buildDSconfig() { + # ---- Build DeepSpeed Config --------------------------------- + export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" + bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit 1 + # ------------------------------------------------------------- +} + + +# makeDSenv() { +# saveDSenv +# } + + +# makeDSenv() { +# echo "PATH=${PATH}" > .deepspeed_env +# echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> .deepspeed_env +# echo "http_proxy=${http_proxy}" >> .deepspeed_env +# echo "https_proxy=${https_proxy}" >> .deepspeed_env +# echo "CFLAGS=${CFLAGS}" >> .deepspeed_env +# echo "PYTHONUSERBASE=$PYTHONUSERBASE" >> .deepspeed_env +# } + +sumWeights() { + local file_list=$1 + weights=$(cat "${file_list}" | awk '{print $1}' | tr '\n' '\ ,\ ' | sed 's/^/[/g' | sed 's/$/]/g' | tr '\ ' "\,\ ") + # weights=$(echo "$weights" | tr ",]" "]") + # echo "weights: $weights" + python3 -c "import numpy as np; print(np.sum(${weights}))" +} + +sumFiles() { + local rd=$1 + for f in $("${rd}/*.txt"); do + ws=$(sumWeights "${rd}/${f}") + echo "sum($f.weights)=${ws}" + done +} + +# setupData() { +# cidx=$1 +# echo "Caught DOLMA_CHUNK_IDX: ${cidx} !!" +# dfl="./chunks-reweighted/10/data_file_list_chunk_${cidx}_of_10.txt" +# if [[ -z "${DATA_FILE_LIST}" ]]; then +# DATA_FILE_LIST="${dfl}" +# else +# echo "Caught DATA_FILE_LIST: ${DATA_FILE_LIST} from ENV!!" +# fi +# NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" +# WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" +# export WEIGHT_SUM="${WEIGHT_SUM}" +# export NDOCS="${NDOCS}" +# echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST} with ${NDOCS} documents" +# echo "WEIGHT SUM: ${WEIGHT_SUM}" +# data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") +# export DOLMA_CHUNK_IDX="${cidx}" +# export DATA_FILE_LIST_STEM="${data_file_list_stem}" +# export DATA_CACHE_PATH=".cache/${data_file_list_stem}/index-cache" +# mkdir -p "${DATA_CACHE_PATH}" +# } +# + + +setEnv() { + if [[ $(hostname) == x4* ]]; then + SETENV_FILE="${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" + if [[ "${SETENV_FILE}" ]]; then + # shellcheck source=/home/foremans/anl_24_release_q4/llm.devkit/setenv.sh + source "${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" + else + echo "Unable to source ${SETENV_FILE}, exiting!" + exit + fi + elif [[ $(hostname) == x3* ]]; then + # ---- load conda ----------------------------------- + module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 + export PYTHONUSERBASE="${HOME}/.local/polaris/conda/2024-03-06" + mkdir -p "${PYTHONUSERBASE}" + # if [[ "${VIRTUAL_ENV}" ]]; then + # echo "Caught VIRTUAL_ENV = ${VIRTUAL_ENV} from environment!!" + # else + # echo "Not using VIRTUAL_ENV" + # # sourceFile "${HERE}/venvs/polaris/2023-10-04/bin/activate" || exit + # fi + else + echo "Unknown hostname $(hostname)" + exit 1 + fi +} + +makeHostfiles() { + GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') + export GPUS_PER_NODE="${GPUS_PER_NODE}" + # ---- Make MPICH hostfile ---------------- + export hostfile_mpich=hostfile_mpich + cat "$PBS_NODEFILE" > "${hostfile_mpich}" + # ---- Make DeepSpeed hostfile ------------------- + export hostfile_deepspeed=hostfile_deepspeed + cat "$PBS_NODEFILE" > "${hostfile_deepspeed}" + sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" +} + + +setData() { # dfl: abbrv. for DATA_FILE_LIST + dfl="${1:-/eagle/datasets/dolma/data_file_list_reweighted.txt}" + # dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" + printf "Calling: \`setData()\` with %s\n" "${dfl}" + ndocs=$(wc -l < "${dfl}") + ws=$(sumWeights "${dfl}") + dfl_stem=$(echo "${dfl}" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") + dcp="${HERE}/.cache/${dfl_stem}/index-cache" + mkdir -p dcp + export DATA_FILE_LIST="${dfl}" + export NUM_DOCS="${ndocs}" + export WEIGHT_SUM="${ws}" + export DFL_STEM="${dfl_stem}" + export DATA_CACHE_PATH="${dcp}" + echo "--------------------" + echo "Updated environment:" + printf "DATA_FILE_LIST: %s\n" "${DATA_FILE_LIST}" + printf "NUM_DOCS: %s\n " "${NUM_DOCS}" + printf "WEIGHT_SUM: %s\n" "${WEIGHT_SUM}" + printf "DFL_STEM: %s\n" "${DFL_STEM}" + printf "DATA_CACHE_PATH: %s\n" "${DATA_CACHE_PATH}" + echo "--------------------" +} + +printBlack() { + printf "\e[1;30m%s\e[0m\n" "$@" +} + +printRed() { + printf "\e[1;31m%s\e[0m\n" "$@" +} + +printGreen() { + printf "\e[1;32m%s\e[0m\n" "$@" +} + +printYellow() { + printf "\e[1;33m%s\e[0m\n" "$@" +} + +printBlue() { + printf "\e[1;34m%s\e[0m\n" "$@" +} + +printMagenta() { + printf "\e[1;35m%s\e[0m\n" "$@" +} + +printCyan() { + printf "\e[1;36m%s\e[0m\n" "$@" +} +printWhite() { + printf "\e[1;37m%s\e[0m\n" "$@" +} diff --git a/ALCF/README.md b/ALCF/pre-AuroraGPT/README.md similarity index 100% rename from ALCF/README.md rename to ALCF/pre-AuroraGPT/README.md diff --git a/ALCF/args.sh b/ALCF/pre-AuroraGPT/args.sh similarity index 100% rename from ALCF/args.sh rename to ALCF/pre-AuroraGPT/args.sh diff --git a/ALCF/launch.sh b/ALCF/pre-AuroraGPT/launch.sh similarity index 100% rename from ALCF/launch.sh rename to ALCF/pre-AuroraGPT/launch.sh diff --git a/ALCF/llama2_vars.sh b/ALCF/pre-AuroraGPT/llama2_vars.sh similarity index 100% rename from ALCF/llama2_vars.sh rename to ALCF/pre-AuroraGPT/llama2_vars.sh diff --git a/ALCF/model.sh b/ALCF/pre-AuroraGPT/model.sh similarity index 100% rename from ALCF/model.sh rename to ALCF/pre-AuroraGPT/model.sh diff --git a/ALCF/setup.sh b/ALCF/pre-AuroraGPT/setup.sh similarity index 100% rename from ALCF/setup.sh rename to ALCF/pre-AuroraGPT/setup.sh diff --git a/ALCF/submit-pbs.sh b/ALCF/pre-AuroraGPT/submit-pbs.sh similarity index 100% rename from ALCF/submit-pbs.sh rename to ALCF/pre-AuroraGPT/submit-pbs.sh diff --git a/ALCF/submit.sh b/ALCF/pre-AuroraGPT/submit.sh similarity index 100% rename from ALCF/submit.sh rename to ALCF/pre-AuroraGPT/submit.sh diff --git a/ALCF/train-gpt3.sh b/ALCF/pre-AuroraGPT/train-gpt3.sh similarity index 100% rename from ALCF/train-gpt3.sh rename to ALCF/pre-AuroraGPT/train-gpt3.sh diff --git a/ALCF/train-llama.sh b/ALCF/pre-AuroraGPT/train-llama.sh similarity index 100% rename from ALCF/train-llama.sh rename to ALCF/pre-AuroraGPT/train-llama.sh diff --git a/ALCF_utils/test_blend.sh b/ALCF/test_blend.sh similarity index 100% rename from ALCF_utils/test_blend.sh rename to ALCF/test_blend.sh diff --git a/ALCF_utils/test_blend_full.sh b/ALCF/test_blend_full.sh similarity index 100% rename from ALCF_utils/test_blend_full.sh rename to ALCF/test_blend_full.sh diff --git a/ALCF_utils/test_blendable_dataset.py b/ALCF/test_blendable_dataset.py similarity index 100% rename from ALCF_utils/test_blendable_dataset.py rename to ALCF/test_blendable_dataset.py diff --git a/ALCF_utils/data_file_list_polaris.txt b/ALCF_utils/data_file_list_polaris.txt deleted file mode 100644 index bac6e0cb33..0000000000 --- a/ALCF_utils/data_file_list_polaris.txt +++ /dev/null @@ -1,3074 +0,0 @@ -0.00029986601436087147 /eagle/datasets//dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/cc_en_middle-0553_text_document -0.00025354733193980704 /eagle/datasets//dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/cc_en_middle-0299_text_document -0.00022796278454747796 /eagle/datasets//dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/cc_en_middle-0366_text_document -0.00015898148098181938 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/eagle/datasets/dolma/data_Llama2Tokenizer_stackcode_fused_5GB/fused_52_text_document diff --git a/ALCF_utils/helpers_alcf.sh b/ALCF_utils/helpers_alcf.sh deleted file mode 100644 index b70ac43407..0000000000 --- a/ALCF_utils/helpers_alcf.sh +++ /dev/null @@ -1,176 +0,0 @@ -#!/bin/bash --login - -ezpz() { - if [[ ! -d ezpz ]]; then - git clone https://github.com/saforem2/ezpz - else - echo "Found ezpz!" - fi - if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then - echo "Has ezpz installed. Nothing to do." - else - echo "Does not have ezpz installed. Installing..." - echo "Using $(which python3) to install \`ezpz\`:" - python3 -m pip install -e ezpz > ezpz-install.log 2>&1 - fi - source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit - source ezpz/src/ezpz/bin/getjobenv || exit -} - -saveDSenv() { - echo "Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env" - { - echo "PATH=${PATH}" ; - echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" ; - echo "http_proxy=${http_proxy}" ; - echo "https_proxy=${https_proxy}" ; - echo "CFLAGS=${CFLAGS}" ; - echo "PYTHONUSERBASE=$PYTHONUSERBASE" ; - } > .deepspeed_env -} - -# makeDSenv() { -# saveDSenv -# } - - -# makeDSenv() { -# echo "PATH=${PATH}" > .deepspeed_env -# echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> .deepspeed_env -# echo "http_proxy=${http_proxy}" >> .deepspeed_env -# echo "https_proxy=${https_proxy}" >> .deepspeed_env -# echo "CFLAGS=${CFLAGS}" >> .deepspeed_env -# echo "PYTHONUSERBASE=$PYTHONUSERBASE" >> .deepspeed_env -# } - -sumWeights() { - local file_list=$1 - weights=$(cat "${file_list}" | awk '{print $1}' | tr '\n' '\ ,\ ' | sed 's/^/[/g' | sed 's/$/]/g' | tr '\ ' "\,\ ") - # weights=$(echo "$weights" | tr ",]" "]") - # echo "weights: $weights" - python3 -c "import numpy as np; print(np.sum(${weights}))" -} - -sumFiles() { - local rd=$1 - for f in $("${rd}/*.txt"); do - ws=$(sumWeights "${rd}/${f}") - echo "sum($f.weights)=${ws}" - done -} - -# setupData() { -# cidx=$1 -# echo "Caught DOLMA_CHUNK_IDX: ${cidx} !!" -# dfl="./chunks-reweighted/10/data_file_list_chunk_${cidx}_of_10.txt" -# if [[ -z "${DATA_FILE_LIST}" ]]; then -# DATA_FILE_LIST="${dfl}" -# else -# echo "Caught DATA_FILE_LIST: ${DATA_FILE_LIST} from ENV!!" -# fi -# NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" -# WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" -# export WEIGHT_SUM="${WEIGHT_SUM}" -# export NDOCS="${NDOCS}" -# echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST} with ${NDOCS} documents" -# echo "WEIGHT SUM: ${WEIGHT_SUM}" -# data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") -# export DOLMA_CHUNK_IDX="${cidx}" -# export DATA_FILE_LIST_STEM="${data_file_list_stem}" -# export DATA_CACHE_PATH=".cache/${data_file_list_stem}/index-cache" -# mkdir -p "${DATA_CACHE_PATH}" -# } -# - - -setEnv() { - if [[ $(hostname) == x4* ]]; then - SETENV_FILE="${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" - if [[ "${SETENV_FILE}" ]]; then - # shellcheck source=/home/foremans/anl_24_release_q4/llm.devkit/setenv.sh - source "${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" - else - echo "Unable to source ${SETENV_FILE}, exiting!" - exit - fi - elif [[ $(hostname) == x3* ]]; then - # ---- load conda ----------------------------------- - module load conda/2023-10-04; conda activate base - if [[ "${VIRTUAL_ENV}" ]]; then - echo "Caught VIRTUAL_ENV = ${VIRTUAL_ENV} from environment!!" - else - echo "Not using VIRTUAL_ENV" - # sourceFile "${HERE}/venvs/polaris/2023-10-04/bin/activate" || exit - fi - else - echo "Unknown hostname $(hostname)" - exit 1 - fi -} - -makeHostfiles() { - GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') - export GPUS_PER_NODE="${GPUS_PER_NODE}" - # ---- Make MPICH hostfile ---------------- - export hostfile_mpich=hostfile_mpich - cat "$PBS_NODEFILE" > "${hostfile_mpich}" - # ---- Make DeepSpeed hostfile ------------------- - export hostfile_deepspeed=hostfile_deepspeed - cat "$PBS_NODEFILE" > "${hostfile_deepspeed}" - sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" -} - - -setupData() { # dfl: abbrv. for DATA_FILE_LIST - dfl=$1 - printf "Calling: \`setupData()\` with %s\n" "${dfl}" - ndocs=$(wc -l < "${dfl}") - ws=$(sumWeights "${dfl}") - dfl_stem=$(echo "${dfl}" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") - dcp="${HERE}/.cache/${dfl_stem}/index-cache" - mkdir -p dcp - export DATA_FILE_LIST="${dfl}" - export NUM_DOCS="${ndocs}" - export WEIGHT_SUM="${ws}" - export DFL_STEM="${dfl_stem}" - export DATA_CACHE_PATH="${dcp}" - echo "--------------------" - echo "Updated environment:" - printf "DATA_FILE_LIST: %s\n" "${DATA_FILE_LIST}" - printf "NUM_DOCS: %s\n " "${NUM_DOCS}" - printf "WEIGHT_SUM: %s\n" "${WEIGHT_SUM}" - printf "DFL_STEM: %s\n" "${DFL_STEM}" - printf "DATA_CACHE_PATH: %s\n" "${DATA_CACHE_PATH}" - echo "--------------------" -} - -printBlack() { - printf "\e[1;30m%s\e[0m\n" "$@" -} - -printRed() { - printf "\e[1;31m%s\e[0m\n" "$@" -} - -printGreen() { - printf "\e[1;32m%s\e[0m\n" "$@" -} - -printYellow() { - printf "\e[1;33m%s\e[0m\n" "$@" -} - -printBlue() { - printf "\e[1;34m%s\e[0m\n" "$@" -} - -printMagenta() { - printf "\e[1;35m%s\e[0m\n" "$@" -} - -printCyan() { - printf "\e[1;36m%s\e[0m\n" "$@" -} -printWhite() { - printf "\e[1;37m%s\e[0m\n" "$@" -} From 7e6e2637e4132834700aa935a43add65ce56be97 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 10:29:35 -0600 Subject: [PATCH 100/268] Add (new) `ALCF/README.md` --- ALCF/README.md | 134 +++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 134 insertions(+) create mode 100644 ALCF/README.md diff --git a/ALCF/README.md b/ALCF/README.md new file mode 100644 index 0000000000..bc2314b914 --- /dev/null +++ b/ALCF/README.md @@ -0,0 +1,134 @@ +# Megatron-DeepSpeed @ ALCF + + +## Polaris + +### Install + +1. Clone [`argonne-lcf/Megatron-DeepSpeed`](https://github.com/argonne-lcf/Megatron-DeepSpeed) + + ```bash + [#](#.md) ---- 0. Clone + navigate into `Megatron-DeepSpeed`: + $ git clone https://github.com/argonne-lcf/Megatron-DeepSpeed + $ cd Megatron-DeepSpeed + ``` + +2. Create `conda` env: + + ```bash + # ---- 1. Create conda env ------------------------------------------------- + $ module load conda/2023-10-04 #; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 + $ MPICC="cc -shared -taret-accel=nvidia80" + $ DAY=$(date "+%Y-^m-%d") + $ conda create --solver libmamba -c pytorch -c nvidia --name "${DAY}" "python==3.10" + $ export PYTHONUSERBASE="${HOME}/.local/polaris/conda/${DAY}" + # --------------------------------------------------------------------------- + ``` + +3. Install dependencies: + + ```bash + # -------- a. Install dependencies ------------------------------------------ + $ conda install -c pytorch -c nvidia --solver libmamba mpi4py pytorch-cuda=11.8 ninja torchvision torchaudio pytorch-cuda=11.8 transformers xformers triton + $ python3 -m pip install --upgrade pip pybind11 toolong appdirs wandb sentencepiece ipython setuptools wheel ninja + $ python3 -m pip install --upgrade deepspeed wandb + ``` + + 1. Install `apex`: + + ```bash + # ------------ i. Install `apex` -------------------------------------------- + $ git clone https://github.com/NVIDIA/apex + $ cd apex + $ module swap gcc gcc/10.3.0 + $ python3 -m pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./ + ``` + + 2. Install `ezpz`: + + ```bash + # ------------ ii. Install `ezpz` -------------------------------------------- + $ git clone https://github.com/saforem2/ezpz + $ python3 -m pip install -e "ezpz[dev]" + # --------------------------------------------------------------------------- + ``` + +### Running + +- The (shell) script used to launch pre-training is: + - Polaris: + [`train_llama_alcf_polaris.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/train_llama_alcf_polaris.sh) + - Aurora: + [`train_llama_alcf_aurora.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/train_llama_alcf_aurora.sh) + +- These shell script(s) will set the appropriate environment variables, load the correct conda +modules and launch +[`pretrain_gpt_alcf.py`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/pretrain_gpt_alcf.py) using `deepspeed` + + +Explicitly, we can: + +```bash +# 1. Launch interactive job +$ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I +# 2. Load conda environment +$ module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 +$ export PYTHONUSERBASE=/home/foremans/.local/polaris/conda/2024-03-06 +# 3. Navigate into `Megatron-DeepSpeed` directory +$ cd Megatron-DeepSpeed +# 4. Launch: +$ bash train_llama_alcf_polaris.sh +``` + +
[Output] + +```bash +source-ing /lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/ALCF/helpers_alcf.sh + +CommandNotFoundError: Your shell has not been properly configured to use 'conda deactivate'. +To initialize your shell, run + + $ conda init + +Currently supported shells are: + - bash + - fish + - tcsh + - xonsh + - zsh + - powershell + +See 'conda init --help' for more information and options. + +IMPORTANT: You may need to close and restart your shell after running 'conda init'. + + +Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env +Found ezpz! +/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/ezpz/src/ezpz/__init__.py +Has ezpz installed. Nothing to do. +┌────────────────────────────────────────────────────────────────── +│ [Hosts]: +│ • [host:0] - x3005c0s37b0n0.hsn.cm.polaris.alcf.anl.gov +│ • [host:1] - x3005c0s37b1n0.hsn.cm.polaris.alcf.anl.gov +└────────────────────────────────────────────────────────────────── +┌────────────────────────────────────────────────────────────────── +│ [DIST INFO]: +│ • Loading job env from: /home/foremans/.pbsenv +│ • HOSTFILE: /var/spool/pbs/aux/1777928.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov +│ • NHOSTS: 2 +│ • NGPU_PER_HOST: 4 +│ • NGPUS (NHOSTS x NGPU_PER_HOST): 8 +│ • WORLD_SIZE: 8 +│ • DIST_LAUNCH: mpiexec --verbose --envall -n 8 -ppn 4 --hostfile /var/spool/pbs/aux/1777928.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov +└────────────────────────────────────────────────────────────────── +┌────────────────────────────────────────────────────────────────── +│ [Launch]: +│ • Use: 'launch' (=mpiexec --verbose --envall -n 8 -ppn 4 --hostfile /var/spool/pbs/aux/1777928.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov) +│ to launch job +└────────────────────────────────────────────────────────────────── + +# [...] +``` + +
From 7133eb63212ba6b2773313df8029e33532ba55be Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 10:29:47 -0600 Subject: [PATCH 101/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 290 ++++++++++-------------------------- 1 file changed, 81 insertions(+), 209 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index b990cc124d..e4b4ef4f43 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -5,7 +5,6 @@ #PBS -l select=48 #PBS -l filesystems=eagle:home - function sourceFile() { fp="$1" echo "source-ing ${fp}" @@ -17,220 +16,94 @@ function sourceFile() { fi } -# +++++++++++++++ SCRIPT START ++++++++++++++++++++++ +# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +# ---- 0. Navigate into `$PBS_O_WORKDIR` ------------------------------------- cd "${PBS_O_WORKDIR}" || exit HERE=$(python3 -c 'import os; print(os.getcwd())') -sourceFile "${HERE}/ALCF_utils/helpers_alcf.sh" || exit - -# ---- fns from ./helpers_alcf.sh ------------------- -setEnv || exit -saveDSenv || exit -ezpz || exit -makeHostfiles || exit -DFL="/eagle/datasets/dolma/data_file_list_reweighted.txt" -setupData "${DATA_FILE_LIST:-${DFL}}" || exit - -echo "Using $(which python3)" - -# mkdir -p "${DATA_CACHE_PATH}" -# if [[ -n "${DOLMA_CHUNK_IDX}" ]]; then -# echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NUM_DOCS} documents..." -# else -# echo "Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" -# fi -# echo "DOCUMENT WEIGHT_SUM: ${WEIGHT_SUM}" -# ---------------------------------------------------- - -# ---- Parallelism Settings -------------------------- -PP=${PP:-1} -TP=${TP:-2} -export PP="${PP}" -export TP="${TP}" -export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" -export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} -# ---------------------------------------------------- - -# ---- Llama2 7B Config ------------------------------ -export MODEL_KEY="Llama-7B" -export HEADS=${HEADS:-32} -export NLAYERS=${NLAYERS:-32} -export HIDDEN=${HIDDEN:-4096} -export NUM_KV_HEAD=${NUM_KV_HEAD:-8} -export FFN_HIDDEN_SIZE=${FFN_HIDDEN_SIZE:-11008} -# ---------------------------------------------------- - -# ---- Run Settings ---------------------------------- -export LR=${LR:-0.0003} -export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 -export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 -export ZERO_STAGE=${ZERO_STAGE:-2} -export MICRO_BATCH=${MICRO_BATCH:-8} -export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} -export EVAL_ITERS="${EVAL_ITERS:-10}" -# export TRAIN_ITER="${TRAIN_ITER:-320000}" -export TRAIN_ITER=${TRAIN_ITER:-317892} -export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" -export SAVE_INTERVAL=${SAVE_INTERVAL:-200} -export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} -# export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} -export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) -export TOKENIZER_MODEL="${TOKENIZER_MODEL:-"/eagle/datasets/dolma/utils/tokenizer.model"}" -export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" -export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" -# ---------------------------------------------------- - -echo "++++++++++++++++++++++++++++++++++++++++++++++++++" -echo "- WORLD_SIZE:${WORLD_SIZE}" -echo "- NCCL: ${NCCL:-nccl}" -echo "- MODEL_TYPE: ${MODEL_TYPE}" -echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" -echo "++++++++++++++++++++++++++++++++++++++++++++++++++" - -# +++++NOTES ++++++++++++++++++++++++++++++++++++++++++++++++++ -# XXX: -# - need to merge *.json files -# - Can we create indices on a per-dataset basis? -# (i.e. one for common-crawl, one for stack-code, etc.) -# - Aggregate `stack-code/**/{*.bin,*.idx}` -# -# - Given: {f1.bin,f2.bin,...,fn.bin} -# - tot_tokens = 0 -# - agg = [] -# - Start: -# - read: f1.bin -# - tot_tokens += sum(tokens(f1.bin)) -# - if tot_tokens < needed_tokens: -# - agg.append(f1.bin) -# - else: -# - -# TODO: -# - StackExchange ~ 500B total, using 80% ~ 400B tokens -# - figure out how to deal with MANY small files (e.g. stack-code) -# - Add logic for determining `train_iters` dynamically from `data-file-list` -# (which specifies a single _chunk_) -# - get script from Varuni -# - should: -# - take in a `data_file_list.txt` -# - return number of training iterations -# -# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ - -# ---- Build DeepSpeed Config --------------------------------- -export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" -bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit 1 -# ------------------------------------------------------------- - -# ---- Specify output location -------------------------------- -export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" -# OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} -OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" -export OUTPUT_DIR="${OUTPUT_DIR}" -export OUTPUT_LOG="${OUTPUT_DIR}/output.log" -export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" -echo "${OUTPUT_LOG}" >> "logs/latest" -mkdir -p "${OUTPUT_DIR}" -echo "!!!Please see logs at ${OUTPUT_DIR}" - -# ---- Setup DeepSpeed arguments -------------------------------- -ds_args=" " -ds_args=" --deepspeed ${ds_args}" -if [[ $PP == 1 ]]; then - ds_args=" --no-pipeline-parallel ${ds_args}" -fi -ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" -ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" - -if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then - echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" - ds_args=" --deepspeed-activation-checkpointing ${ds_args}" - # --checkpoint-activations \ - # --deepspeed-activation-checkpointing -fi -# --------------------------------------------------------------- - -gpt_args=() - -# we are now using activation checkpoint provided by megatron, see below. -# ds_args=" --deepspeed-activation-checkpointing ${ds_args}" -if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then - echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" - gpt_args+=( - "--checkpoint-activations" - "--checkpoint-num-layers 1" - ) -fi - -# take custom args +export HERE +# ---- 1. Assert `./pretrain_gpt_alcf.py` exists: ----------------------------- +export EXEC="${HERE}/pretrain_gpt_alcf.py" +[ -f "${EXEC}" ] || exit +# ---- 2. `source ./ALCF/helpers_alcf.sh`: ------------------------------------ +sourceFile "${HERE}/ALCF/helpers.sh" || exit +# ---- 3. Call fns from `./ALCF/helpers_alcf.sh` ------------------------------ +setEnv || exit # 1. load `conda` environment +saveDSenv || exit # 2. save env vars to `.deepspeed_env` +ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars +makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` +buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ +setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} +setArgs || exit # 8. specify additional `deepspeed` arguments +setData || exit # 9. specify `DATA_FILE_LIST` for dolma dataset +setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` +printJobInfo || exit # 11. print job info +# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + +# Take custom args custom_args=" $@" -# launcher setting -hfds="${HERE}/hostfile_deepspeed" -hfmpi="${HERE}/hostfile_mpich" -[ -f "$hfds" ] || exit -[ -f "$hfmpi" ] || exit - -LAUNCHER=${LAUNCHER:-MPICH} -if [[ $LAUNCHER == "deepspeed" ]]; then - launcher="" -else - launcher="--force_multi --hostfile $hfds --launcher=${LAUNCHER} --launcher_args='-hostfile ${hfmpi}'" -fi - -NCCL=${NCCL:-nccl} -EXEC="pretrain_gpt_alcf.py" +# Assert `./hostfile_deepspeed` exists +export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit # --vocab-file $VOCAB_FILE \ # --merge-file $MERGE_FILE \ # --lr-decay-iters 320000 \ - # --lr-warmup-iters 5000 \ - # --lr-decay-iters 10000 \ - # --num-workers 4 \ - # launch python3 ${EXEC} \ - # --data-impl mmap \ -run_cmd=" - deepspeed $launcher ${EXEC} \ - --$DTYPE \ - --split 100,0,0 \ - --use-flash-attn-v2 \ - --no-bias-gelu-fusion \ - --lr-decay-style cosine \ - --no-bias-dropout-fusion \ - --no-masked-softmax-fusion \ - --tokenizer-type Llama2Tokenizer \ - --no-gradient-accumulation-fusion \ - --accumulate-allreduce-grads-in-fp32 \ - --use-checkpoint-opt_param-scheduler \ - --lr ${LR} \ - --log-interval 1 \ - --num-workers 0 \ - --seq-length $SEQ \ - --save ${CKPT_DIR} \ - --load ${CKPT_DIR} \ - --num-layers ${NLAYERS} \ - --hidden-size ${HIDDEN} \ - --train-iters ${TRAIN_ITER} \ - --eval-iters ${EVAL_ITERS} \ - --distributed-backend ${NCCL} \ - --num-attention-heads ${HEADS} \ - --save-interval ${SAVE_INTERVAL} \ - --eval-interval ${EVAL_INTERVAL} \ - --max-position-embeddings ${SEQ} \ - --micro-batch-size ${MICRO_BATCH} \ - --data-file-list ${DATA_FILE_LIST} \ - --tensor-model-parallel-size ${TP} \ - --global-batch-size ${GLOBAL_BATCH} \ - --pipeline-model-parallel-size ${PP} \ - --num-key-value-heads ${NUM_KV_HEAD} \ - --data-cache-path ${DATA_CACHE_PATH} \ - --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ - --tokenizer-model ${TOKENIZER_MODEL} \ - $ds_args \ - ${LLAMA_ARGS} \ - ${gpt_args[*]} \ - $custom_args \ - |& tee ${OUTPUT_LOG} - " +# --lr-warmup-iters 5000 \ +# --lr-decay-iters 10000 \ +# --num-workers 4 \ +# launch python3 ${EXEC} \ +# --data-impl mmap \ +# source ./ezpz/src/ezpz/bin/getjobenv || exit + # ${DIST_LAUNCH} ./local_rank.sh python3 ${EXEC} \ + # ${DIST_LAUNCH} python3 ${EXEC} \ + # deepspeed $launcher ${EXEC} \ +# run_cmd=" +# deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ +# |& tee ${OUTPUT_LOG} +# " + # --$DTYPE \ + # --num-workers 0 \ + # --split 100,0,0 \ + # --log-interval 1 \ + # --use-flash-attn-v2 \ + # --no-bias-gelu-fusion \ + # --lr-decay-style cosine \ + # --no-bias-dropout-fusion \ + # --no-masked-softmax-fusion \ + # --tokenizer-type Llama2Tokenizer \ + # --no-gradient-accumulation-fusion \ + # --accumulate-allreduce-grads-in-fp32 \ + # --use-checkpoint-opt_param-scheduler \ + # --lr ${LR} \ + # --seq-length $SEQ \ + # --save ${CKPT_DIR} \ + # --load ${CKPT_DIR} \ + # --num-layers ${NLAYERS} \ + # --hidden-size ${HIDDEN} \ + # --train-iters ${TRAIN_ITER} \ + # --eval-iters ${EVAL_ITERS} \ + # --distributed-backend ${NCCL} \ + # --num-attention-heads ${HEADS} \ + # --save-interval ${SAVE_INTERVAL} \ + # --eval-interval ${EVAL_INTERVAL} \ + # --max-position-embeddings ${SEQ} \ + # --micro-batch-size ${MICRO_BATCH} \ + # --data-file-list ${DATA_FILE_LIST} \ + # --tensor-model-parallel-size ${TP} \ + # --global-batch-size ${GLOBAL_BATCH} \ + # --pipeline-model-parallel-size ${PP} \ + # --num-key-value-heads ${NUM_KV_HEAD} \ + # --data-cache-path ${DATA_CACHE_PATH} \ + # --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ + # --tokenizer-model ${TOKENIZER_MODEL} \ + # $ds_args \ + # ${LLAMA_ARGS} \ + # ${gpt_args[*]} \ + # $custom_args \ + +run_cmd="deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} ${CLI_ARGS} |& tee ${OUTPUT_LOG}" + # >> ${OUTPUT_LOG} 2>&1 & # >> ${OUTPUT_LOG} 2>&1 & # |& tee $OUTPUT_DIR/output.log @@ -240,8 +113,7 @@ echo "All DeepSpeed(s): $(which -a deepspeed)" echo "Using $(which deepspeed)" ds_report -echo "${run_cmd}" - +echo "[RUNNING]: ${run_cmd}" printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" # echo "${OUTPUT_LOG}" From eb89ee4c1516b93d5f807bb699ae81c0bc3ac097 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 10:31:27 -0600 Subject: [PATCH 102/268] Update `ALCF/README.md` --- ALCF/README.md | 31 ++++++++++++------------------- 1 file changed, 12 insertions(+), 19 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index bc2314b914..31bf4b759d 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -1,6 +1,5 @@ # Megatron-DeepSpeed @ ALCF - ## Polaris ### Install @@ -16,19 +15,16 @@ 2. Create `conda` env: ```bash - # ---- 1. Create conda env ------------------------------------------------- $ module load conda/2023-10-04 #; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 $ MPICC="cc -shared -taret-accel=nvidia80" $ DAY=$(date "+%Y-^m-%d") $ conda create --solver libmamba -c pytorch -c nvidia --name "${DAY}" "python==3.10" $ export PYTHONUSERBASE="${HOME}/.local/polaris/conda/${DAY}" - # --------------------------------------------------------------------------- ``` 3. Install dependencies: ```bash - # -------- a. Install dependencies ------------------------------------------ $ conda install -c pytorch -c nvidia --solver libmamba mpi4py pytorch-cuda=11.8 ninja torchvision torchaudio pytorch-cuda=11.8 transformers xformers triton $ python3 -m pip install --upgrade pip pybind11 toolong appdirs wandb sentencepiece ipython setuptools wheel ninja $ python3 -m pip install --upgrade deepspeed wandb @@ -37,7 +33,6 @@ 1. Install `apex`: ```bash - # ------------ i. Install `apex` -------------------------------------------- $ git clone https://github.com/NVIDIA/apex $ cd apex $ module swap gcc gcc/10.3.0 @@ -47,10 +42,8 @@ 2. Install `ezpz`: ```bash - # ------------ ii. Install `ezpz` -------------------------------------------- $ git clone https://github.com/saforem2/ezpz $ python3 -m pip install -e "ezpz[dev]" - # --------------------------------------------------------------------------- ``` ### Running @@ -66,19 +59,19 @@ modules and launch [`pretrain_gpt_alcf.py`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/pretrain_gpt_alcf.py) using `deepspeed` -Explicitly, we can: +- Explicitly, to launch: -```bash -# 1. Launch interactive job -$ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I -# 2. Load conda environment -$ module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 -$ export PYTHONUSERBASE=/home/foremans/.local/polaris/conda/2024-03-06 -# 3. Navigate into `Megatron-DeepSpeed` directory -$ cd Megatron-DeepSpeed -# 4. Launch: -$ bash train_llama_alcf_polaris.sh -``` + ```bash + # 1. Launch interactive job + $ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I + # 2. Load conda environment + $ module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 + $ export PYTHONUSERBASE=/home/foremans/.local/polaris/conda/2024-03-06 + # 3. Navigate into `Megatron-DeepSpeed` directory + $ cd Megatron-DeepSpeed + # 4. Launch: + $ bash train_llama_alcf_polaris.sh + ```
[Output] From 4076cf09fb92d6f61b637b2b51234f11e5280b19 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 10:36:48 -0600 Subject: [PATCH 103/268] Update `ALCF/README.md` --- ALCF/README.md | 112 ++++++++++++++++++++++++------------------------- 1 file changed, 54 insertions(+), 58 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 31bf4b759d..47920644db 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -7,7 +7,6 @@ 1. Clone [`argonne-lcf/Megatron-DeepSpeed`](https://github.com/argonne-lcf/Megatron-DeepSpeed) ```bash - [#](#.md) ---- 0. Clone + navigate into `Megatron-DeepSpeed`: $ git clone https://github.com/argonne-lcf/Megatron-DeepSpeed $ cd Megatron-DeepSpeed ``` @@ -15,9 +14,9 @@ 2. Create `conda` env: ```bash - $ module load conda/2023-10-04 #; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 - $ MPICC="cc -shared -taret-accel=nvidia80" - $ DAY=$(date "+%Y-^m-%d") + $ module load conda/2023-10-04 + $ export MPICC="cc -shared -taret-accel=nvidia80" + $ export DAY=$(date "+%Y-^m-%d") $ conda create --solver libmamba -c pytorch -c nvidia --name "${DAY}" "python==3.10" $ export PYTHONUSERBASE="${HOME}/.local/polaris/conda/${DAY}" ``` @@ -30,7 +29,7 @@ $ python3 -m pip install --upgrade deepspeed wandb ``` - 1. Install `apex`: + - [`NVIDIA/apex`](https://github.com/NVIDIA/apex): ```bash $ git clone https://github.com/NVIDIA/apex @@ -39,7 +38,7 @@ $ python3 -m pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./ ``` - 2. Install `ezpz`: + - [`ezpz`](https://github.com/saforem2/ezpz): ```bash $ git clone https://github.com/saforem2/ezpz @@ -72,56 +71,53 @@ modules and launch # 4. Launch: $ bash train_llama_alcf_polaris.sh ``` +
[Output] -
[Output] - -```bash -source-ing /lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/ALCF/helpers_alcf.sh - -CommandNotFoundError: Your shell has not been properly configured to use 'conda deactivate'. -To initialize your shell, run - - $ conda init - -Currently supported shells are: - - bash - - fish - - tcsh - - xonsh - - zsh - - powershell - -See 'conda init --help' for more information and options. - -IMPORTANT: You may need to close and restart your shell after running 'conda init'. - - -Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env -Found ezpz! -/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/ezpz/src/ezpz/__init__.py -Has ezpz installed. Nothing to do. -┌────────────────────────────────────────────────────────────────── -│ [Hosts]: -│ • [host:0] - x3005c0s37b0n0.hsn.cm.polaris.alcf.anl.gov -│ • [host:1] - x3005c0s37b1n0.hsn.cm.polaris.alcf.anl.gov -└────────────────────────────────────────────────────────────────── -┌────────────────────────────────────────────────────────────────── -│ [DIST INFO]: -│ • Loading job env from: /home/foremans/.pbsenv -│ • HOSTFILE: /var/spool/pbs/aux/1777928.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov -│ • NHOSTS: 2 -│ • NGPU_PER_HOST: 4 -│ • NGPUS (NHOSTS x NGPU_PER_HOST): 8 -│ • WORLD_SIZE: 8 -│ • DIST_LAUNCH: mpiexec --verbose --envall -n 8 -ppn 4 --hostfile /var/spool/pbs/aux/1777928.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov -└────────────────────────────────────────────────────────────────── -┌────────────────────────────────────────────────────────────────── -│ [Launch]: -│ • Use: 'launch' (=mpiexec --verbose --envall -n 8 -ppn 4 --hostfile /var/spool/pbs/aux/1777928.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov) -│ to launch job -└────────────────────────────────────────────────────────────────── - -# [...] -``` - -
+ ```bash + source-ing /lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/ALCF/helpers_alcf.sh + + CommandNotFoundError: Your shell has not been properly configured to use 'conda deactivate'. + To initialize your shell, run + + $ conda init + + Currently supported shells are: + - bash + - fish + - tcsh + - xonsh + - zsh + - powershell + + See 'conda init --help' for more information and options. + + IMPORTANT: You may need to close and restart your shell after running 'conda init'. + + + Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env + Found ezpz! + /lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/ezpz/src/ezpz/__init__.py + Has ezpz installed. Nothing to do. + ┌────────────────────────────────────────────────────────────────── + │ [Hosts]: + │ • [host:0] - x3005c0s37b0n0.hsn.cm.polaris.alcf.anl.gov + │ • [host:1] - x3005c0s37b1n0.hsn.cm.polaris.alcf.anl.gov + └────────────────────────────────────────────────────────────────── + ┌────────────────────────────────────────────────────────────────── + │ [DIST INFO]: + │ • Loading job env from: /home/foremans/.pbsenv + │ • HOSTFILE: /var/spool/pbs/aux/1777928.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov + │ • NHOSTS: 2 + │ • NGPU_PER_HOST: 4 + │ • NGPUS (NHOSTS x NGPU_PER_HOST): 8 + │ • WORLD_SIZE: 8 + │ • DIST_LAUNCH: mpiexec --verbose --envall -n 8 -ppn 4 --hostfile /var/spool/pbs/aux/1777928.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov + └────────────────────────────────────────────────────────────────── + ┌────────────────────────────────────────────────────────────────── + │ [Launch]: + │ • Use: 'launch' (=mpiexec --verbose --envall -n 8 -ppn 4 --hostfile /var/spool/pbs/aux/1777928.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov) + │ to launch job + └────────────────────────────────────────────────────────────────── + # [...] + ``` +
From 7e8a1a8ebeacf0e185dd2e53ee99349aae35c6cf Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 17:07:30 -0600 Subject: [PATCH 104/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 115 ++++++++++++++++++------------------ 1 file changed, 58 insertions(+), 57 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index e4b4ef4f43..e657334d23 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -35,7 +35,7 @@ setParams || exit # 5. set command line arguments to pass to ` buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} setArgs || exit # 8. specify additional `deepspeed` arguments -setData || exit # 9. specify `DATA_FILE_LIST` for dolma dataset +setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` printJobInfo || exit # 11. print job info # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ @@ -46,64 +46,64 @@ custom_args=" $@" # Assert `./hostfile_deepspeed` exists export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit -# --vocab-file $VOCAB_FILE \ -# --merge-file $MERGE_FILE \ -# --lr-decay-iters 320000 \ -# --lr-warmup-iters 5000 \ -# --lr-decay-iters 10000 \ -# --num-workers 4 \ -# launch python3 ${EXEC} \ -# --data-impl mmap \ -# source ./ezpz/src/ezpz/bin/getjobenv || exit +run_cmd=" + deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ + --$DTYPE \ + --num-workers 0 \ + --split 100,0,0 \ + --log-interval 1 \ + --use-flash-attn-v2 \ + --no-bias-gelu-fusion \ + --lr-decay-style cosine \ + --no-bias-dropout-fusion \ + --no-masked-softmax-fusion \ + --tokenizer-type Llama2Tokenizer \ + --no-gradient-accumulation-fusion \ + --accumulate-allreduce-grads-in-fp32 \ + --use-checkpoint-opt_param-scheduler \ + --lr ${LR} \ + --seq-length $SEQ \ + --save ${CKPT_DIR} \ + --load ${CKPT_DIR} \ + --num-layers ${NLAYERS} \ + --hidden-size ${HIDDEN} \ + --train-iters ${TRAIN_ITER} \ + --eval-iters ${EVAL_ITERS} \ + --distributed-backend ${NCCL} \ + --num-attention-heads ${HEADS} \ + --save-interval ${SAVE_INTERVAL} \ + --eval-interval ${EVAL_INTERVAL} \ + --max-position-embeddings ${SEQ} \ + --micro-batch-size ${MICRO_BATCH} \ + --data-file-list ${DATA_FILE_LIST} \ + --tensor-model-parallel-size ${TP} \ + --global-batch-size ${GLOBAL_BATCH} \ + --pipeline-model-parallel-size ${PP} \ + --num-key-value-heads ${NUM_KV_HEAD} \ + --data-cache-path ${DATA_CACHE_PATH} \ + --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ + --tokenizer-model ${TOKENIZER_MODEL} \ + ${LLAMA_ARGS} \ + $ds_args \ + ${gpt_args[*]} \ + $custom_args \ + |& tee ${OUTPUT_LOG} + " + + # --------------------------------------------------- + # --vocab-file $VOCAB_FILE \ + # --merge-file $MERGE_FILE \ + # --lr-decay-iters 320000 \ + # --lr-warmup-iters 5000 \ + # --lr-decay-iters 10000 \ + # --num-workers 4 \ + # launch python3 ${EXEC} \ + # --data-impl mmap \ + # source ./ezpz/src/ezpz/bin/getjobenv || exit + # --------------------------------------------------- # ${DIST_LAUNCH} ./local_rank.sh python3 ${EXEC} \ # ${DIST_LAUNCH} python3 ${EXEC} \ # deepspeed $launcher ${EXEC} \ -# run_cmd=" -# deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ -# |& tee ${OUTPUT_LOG} -# " - # --$DTYPE \ - # --num-workers 0 \ - # --split 100,0,0 \ - # --log-interval 1 \ - # --use-flash-attn-v2 \ - # --no-bias-gelu-fusion \ - # --lr-decay-style cosine \ - # --no-bias-dropout-fusion \ - # --no-masked-softmax-fusion \ - # --tokenizer-type Llama2Tokenizer \ - # --no-gradient-accumulation-fusion \ - # --accumulate-allreduce-grads-in-fp32 \ - # --use-checkpoint-opt_param-scheduler \ - # --lr ${LR} \ - # --seq-length $SEQ \ - # --save ${CKPT_DIR} \ - # --load ${CKPT_DIR} \ - # --num-layers ${NLAYERS} \ - # --hidden-size ${HIDDEN} \ - # --train-iters ${TRAIN_ITER} \ - # --eval-iters ${EVAL_ITERS} \ - # --distributed-backend ${NCCL} \ - # --num-attention-heads ${HEADS} \ - # --save-interval ${SAVE_INTERVAL} \ - # --eval-interval ${EVAL_INTERVAL} \ - # --max-position-embeddings ${SEQ} \ - # --micro-batch-size ${MICRO_BATCH} \ - # --data-file-list ${DATA_FILE_LIST} \ - # --tensor-model-parallel-size ${TP} \ - # --global-batch-size ${GLOBAL_BATCH} \ - # --pipeline-model-parallel-size ${PP} \ - # --num-key-value-heads ${NUM_KV_HEAD} \ - # --data-cache-path ${DATA_CACHE_PATH} \ - # --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ - # --tokenizer-model ${TOKENIZER_MODEL} \ - # $ds_args \ - # ${LLAMA_ARGS} \ - # ${gpt_args[*]} \ - # $custom_args \ - -run_cmd="deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} ${CLI_ARGS} |& tee ${OUTPUT_LOG}" - # >> ${OUTPUT_LOG} 2>&1 & # >> ${OUTPUT_LOG} 2>&1 & # |& tee $OUTPUT_DIR/output.log @@ -113,7 +113,8 @@ echo "All DeepSpeed(s): $(which -a deepspeed)" echo "Using $(which deepspeed)" ds_report -echo "[RUNNING]: ${run_cmd}" +echo "${run_cmd}" + printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" # echo "${OUTPUT_LOG}" From 13adb2e1e8b7b3626580dc39b2c96c43bd6460bb Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 17:08:00 -0600 Subject: [PATCH 105/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 140 ++++++++++++++++++------------------------------ 1 file changed, 51 insertions(+), 89 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 6ff3447f05..ccb7c345ec 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -1,49 +1,5 @@ #!/bin/bash --login -buildCLIargs() { - custom_args=" $@" - export CLI_ARGS=" - --$DTYPE \ - --num-workers 0 \ - --split 100,0,0 \ - --log-interval 1 \ - --use-flash-attn-v2 \ - --no-bias-gelu-fusion \ - --lr-decay-style cosine \ - --no-bias-dropout-fusion \ - --no-masked-softmax-fusion \ - --tokenizer-type Llama2Tokenizer \ - --no-gradient-accumulation-fusion \ - --accumulate-allreduce-grads-in-fp32 \ - --use-checkpoint-opt_param-scheduler \ - --lr ${LR} \ - --save ${CKPT_DIR} \ - --load ${CKPT_DIR} \ - --seq-length ${SEQ} \ - --num-layers ${NLAYERS} \ - --hidden-size ${HIDDEN} \ - --train-iters ${TRAIN_ITER} \ - --eval-iters ${EVAL_ITERS} \ - --distributed-backend ${NCCL} \ - --num-attention-heads ${HEADS} \ - --save-interval ${SAVE_INTERVAL} \ - --eval-interval ${EVAL_INTERVAL} \ - --max-position-embeddings ${SEQ} \ - --micro-batch-size ${MICRO_BATCH} \ - --data-file-list ${DATA_FILE_LIST} \ - --tensor-model-parallel-size ${TP} \ - --global-batch-size ${GLOBAL_BATCH} \ - --pipeline-model-parallel-size ${PP} \ - --num-key-value-heads ${NUM_KV_HEAD} \ - --data-cache-path ${DATA_CACHE_PATH} \ - --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ - --tokenizer-model ${TOKENIZER_MODEL} \ - $ds_args \ - ${LLAMA_ARGS} \ - ${gpt_args[*]} \ - ${custom_args} \ - " -} printJobInfo() { echo "++++++++++++++++++++++++++++++++++++++++++++++++++" @@ -183,7 +139,6 @@ saveDSenv() { setOutput() { # ---- Specify output location -------------------------------- export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" - # OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" export OUTPUT_DIR="${OUTPUT_DIR}" export OUTPUT_LOG="${OUTPUT_DIR}/output.log" @@ -201,20 +156,6 @@ buildDSconfig() { } -# makeDSenv() { -# saveDSenv -# } - - -# makeDSenv() { -# echo "PATH=${PATH}" > .deepspeed_env -# echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> .deepspeed_env -# echo "http_proxy=${http_proxy}" >> .deepspeed_env -# echo "https_proxy=${https_proxy}" >> .deepspeed_env -# echo "CFLAGS=${CFLAGS}" >> .deepspeed_env -# echo "PYTHONUSERBASE=$PYTHONUSERBASE" >> .deepspeed_env -# } - sumWeights() { local file_list=$1 weights=$(cat "${file_list}" | awk '{print $1}' | tr '\n' '\ ,\ ' | sed 's/^/[/g' | sed 's/$/]/g' | tr '\ ' "\,\ ") @@ -231,42 +172,19 @@ sumFiles() { done } -# setupData() { -# cidx=$1 -# echo "Caught DOLMA_CHUNK_IDX: ${cidx} !!" -# dfl="./chunks-reweighted/10/data_file_list_chunk_${cidx}_of_10.txt" -# if [[ -z "${DATA_FILE_LIST}" ]]; then -# DATA_FILE_LIST="${dfl}" -# else -# echo "Caught DATA_FILE_LIST: ${DATA_FILE_LIST} from ENV!!" -# fi -# NDOCS=$(wc -l < "${DATA_FILE_LIST}") && export NDOCS="${NDOCS}" -# WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" -# export WEIGHT_SUM="${WEIGHT_SUM}" -# export NDOCS="${NDOCS}" -# echo "Using DATA_FILE_LIST: ${DATA_FILE_LIST} with ${NDOCS} documents" -# echo "WEIGHT SUM: ${WEIGHT_SUM}" -# data_file_list_stem=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") -# export DOLMA_CHUNK_IDX="${cidx}" -# export DATA_FILE_LIST_STEM="${data_file_list_stem}" -# export DATA_CACHE_PATH=".cache/${data_file_list_stem}/index-cache" -# mkdir -p "${DATA_CACHE_PATH}" -# } -# - setEnv() { - if [[ $(hostname) == x4* ]]; then + if [[ $(hostname) == x4* ]]; then # ---- [Aurora] ---------------------- SETENV_FILE="${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" if [[ "${SETENV_FILE}" ]]; then # shellcheck source=/home/foremans/anl_24_release_q4/llm.devkit/setenv.sh - source "${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" + source "${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" || exit else echo "Unable to source ${SETENV_FILE}, exiting!" exit fi - elif [[ $(hostname) == x3* ]]; then - # ---- load conda ----------------------------------- + elif [[ $(hostname) == x3* ]]; then # ---- [Polaris] --------------------- + # ---- [load conda] --------------------- module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 export PYTHONUSERBASE="${HOME}/.local/polaris/conda/2024-03-06" mkdir -p "${PYTHONUSERBASE}" @@ -276,7 +194,7 @@ setEnv() { # echo "Not using VIRTUAL_ENV" # # sourceFile "${HERE}/venvs/polaris/2023-10-04/bin/activate" || exit # fi - else + else # ------------------------------------- [Unknown] ------------------- echo "Unknown hostname $(hostname)" exit 1 fi @@ -294,8 +212,7 @@ makeHostfiles() { sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" } - -setData() { # dfl: abbrv. for DATA_FILE_LIST +setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- dfl="${1:-/eagle/datasets/dolma/data_file_list_reweighted.txt}" # dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" printf "Calling: \`setData()\` with %s\n" "${dfl}" @@ -319,6 +236,51 @@ setData() { # dfl: abbrv. for DATA_FILE_LIST echo "--------------------" } +buildCLIargs() { # ---- [BROKEN] ------------------------------------------- + custom_args=" $@" + export CLI_ARGS=" + --$DTYPE \ + --num-workers 0 \ + --split 100,0,0 \ + --log-interval 1 \ + --use-flash-attn-v2 \ + --no-bias-gelu-fusion \ + --lr-decay-style cosine \ + --no-bias-dropout-fusion \ + --no-masked-softmax-fusion \ + --tokenizer-type Llama2Tokenizer \ + --no-gradient-accumulation-fusion \ + --accumulate-allreduce-grads-in-fp32 \ + --use-checkpoint-opt_param-scheduler \ + --lr ${LR} \ + --save ${CKPT_DIR} \ + --load ${CKPT_DIR} \ + --seq-length ${SEQ} \ + --num-layers ${NLAYERS} \ + --hidden-size ${HIDDEN} \ + --train-iters ${TRAIN_ITER} \ + --eval-iters ${EVAL_ITERS} \ + --distributed-backend ${NCCL} \ + --num-attention-heads ${HEADS} \ + --save-interval ${SAVE_INTERVAL} \ + --eval-interval ${EVAL_INTERVAL} \ + --max-position-embeddings ${SEQ} \ + --micro-batch-size ${MICRO_BATCH} \ + --data-file-list ${DATA_FILE_LIST} \ + --tensor-model-parallel-size ${TP} \ + --global-batch-size ${GLOBAL_BATCH} \ + --pipeline-model-parallel-size ${PP} \ + --num-key-value-heads ${NUM_KV_HEAD} \ + --data-cache-path ${DATA_CACHE_PATH} \ + --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ + --tokenizer-model ${TOKENIZER_MODEL} \ + $ds_args \ + ${LLAMA_ARGS} \ + ${gpt_args[*]} \ + ${custom_args} \ + " +} + printBlack() { printf "\e[1;30m%s\e[0m\n" "$@" } From 509e8ec58771c32171447193883224411571df02 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 17:13:27 -0600 Subject: [PATCH 106/268] Update `ALCF/README.md` --- ALCF/README.md | 68 ++++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 66 insertions(+), 2 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 47920644db..4b67b59ee2 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -2,6 +2,70 @@ ## Polaris +- Unable to save checkpoints with `torch==2.1` + `cuda==11.8`: + - **NEED TO DEBUG / FIX !!** + - Training progresses OK: + + ```bash + [2024-03-07 15:27:02,646] [INFO] [timer.py:260:stop] epoch=0/micro_step=199/global_step=199, RunningAvgSamplesPerSec=58.730622229657506, CurrSamplesPerSec=61.35304005128382, MemAllocated=6.01GB, MaxMemAllocated=19.52GB + iteration 199/ 317892 | consumed samples: 152832 | consumed tokens: 625999872 | elapsed time per iteration (ms): 14287.5 | learning rate: 2.407E-04 | global batch size: 768 | lm loss: 5.905366E+00 | loss scale: 8192.0 | actual seqlen: 4096 | number of skipped iterations: 0 | number of nan iterations: 0 | samples per second: 53.753 | tokens per gpu per second (tgs): 1146.733 | TFLOPs: 69.85 | + [2024-03-07 15:27:15,063] [INFO] [logging.py:96:log_dist] [Rank 0] step=200, skipped=4, lr=[0.000240653265864008, 0.000240653265864008], mom=[(0.9, 0.999), (0.9, 0.999)] + [2024-03-07 15:27:17,188] [INFO] [timer.py:260:stop] epoch=0/micro_step=200/global_step=200, RunningAvgSamplesPerSec=58.730745476291396, CurrSamplesPerSec=58.75503515561452, MemAllocated=6.01GB, MaxMemAllocated=19.52GB + iteration 200/ 317892 | consumed samples: 153600 | consumed tokens: 629145600 | elapsed time per iteration (ms): 14541.4 | learning rate: 2.407E-04 | global batch size: 768 | lm loss: 5.897035E+00 | loss scale: 8192.0 | actual seqlen: 4096 | number of skipped iterations: 0 | number of nan iterations: 0 | samples per second: 52.815 | tokens per gpu per second (tgs): 1126.713 | TFLOPs: 68.63 | + saving checkpoint at iteration 200 to checkpoints/ds_stage2_nl32_hs4096_mb8_seq4096_gb768_pp1_tp2_fp16 + # ... + ``` + + - Then crashes with: + + ```python + Traceback (most recent call last): + Traceback (most recent call last): + File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/pretrain_gpt_alcf.py", line 575, in + model = main() + File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/pretrain_gpt_alcf.py", line 554, in main + model = pretrain( + File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/training.py", line 226, in pretrain + iteration = train(forward_step_func, + File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/training.py", line 1290, in train + save_checkpoint_and_time(iteration, model, optimizer, + File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/training.py", line 1151, in save_checkpoint_and_time + save_checkpoint(iteration, model, optimizer, opt_param_scheduler) + File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/checkpointing.py", line 259, in save_checkpoint + state_dict[UNIVERSAL_CHECKPOINT_INFO] = _universal_checkpoint_info(model) + File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/checkpointing.py", line 783, in _universal_checkpoint_info + info.update(model[0].universal_checkpoint_info()) + File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/model/gpt_model.py", line 203, in universal_checkpoint_info + info[TP_REPLICATED_PARAMETER_PATTERNS] = self._get_tp_replicated_param_patterns() + File "/lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1695, in __getattr__ + raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'") + AttributeError: 'GPTModel' object has no attribute '_get_tp_replicated_param_patterns' + ``` + + 🤔 + + +- Continue runs on Polaris @ + - [x] 48 Nodes + - [x] 32 Nodes + - [x] 16 Nodes + - [x] 8 Nodes + - [x] 4 Nodes + +- [x] Then, try re-creating ( / fixing) conda with `cuda==12.1` + - 😔, failed. + +- Convergence: + - [ ] Use `bf16` on both systems + - [ ] Will need to track (for each layer): + - [ ] inputs / outputs + - [ ] weights, gradients + - [ ] Start thread in Intel SC23 channel to discuss convergence issues + - [ ] Add hooks to track additional data + +- [ ] Ensure / double check that optimizer settings from `ds_config.json` aren't being overwritten by some defaults in `megatron/arguments.py` + - [ ] specifically, `momentum, beta{1, 2}, etc` + ### Install 1. Clone [`argonne-lcf/Megatron-DeepSpeed`](https://github.com/argonne-lcf/Megatron-DeepSpeed) @@ -16,7 +80,7 @@ ```bash $ module load conda/2023-10-04 $ export MPICC="cc -shared -taret-accel=nvidia80" - $ export DAY=$(date "+%Y-^m-%d") + $ export DAY=$(date "+%Y-%m-%d") $ conda create --solver libmamba -c pytorch -c nvidia --name "${DAY}" "python==3.10" $ export PYTHONUSERBASE="${HOME}/.local/polaris/conda/${DAY}" ``` @@ -65,7 +129,7 @@ modules and launch $ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I # 2. Load conda environment $ module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 - $ export PYTHONUSERBASE=/home/foremans/.local/polaris/conda/2024-03-06 + # $ export PYTHONUSERBASE=/home/foremans/.local/polaris/conda/2024-03-06 # 3. Navigate into `Megatron-DeepSpeed` directory $ cd Megatron-DeepSpeed # 4. Launch: From c272b4d24d8008c79d316f21500fa3a3fab7bdb9 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 17:18:51 -0600 Subject: [PATCH 107/268] Update `ALCF/README.md` --- ALCF/README.md | 26 +++++++++++++++++--------- 1 file changed, 17 insertions(+), 9 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 4b67b59ee2..76bb90ba5c 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -2,6 +2,8 @@ ## Polaris +
📅 2024-03-07 + - Unable to save checkpoints with `torch==2.1` + `cuda==11.8`: - **NEED TO DEBUG / FIX !!** - Training progresses OK: @@ -44,6 +46,19 @@ 🤔 +- Convergence: + - [ ] Use `bf16` on both systems + - [ ] Will need to track (for each layer): + - [ ] inputs / outputs + - [ ] weights, gradients + - [ ] Start thread in Intel SC23 channel to discuss convergence issues + - [ ] Add hooks to track additional data + +- [ ] Ensure / double check that optimizer settings from `ds_config.json` aren't being overwritten by some defaults in `megatron/arguments.py` + - [ ] specifically, `momentum, beta{1, 2}, etc` + + +
✅ Completed - Continue runs on Polaris @ - [x] 48 Nodes @@ -55,16 +70,9 @@ - [x] Then, try re-creating ( / fixing) conda with `cuda==12.1` - 😔, failed. -- Convergence: - - [ ] Use `bf16` on both systems - - [ ] Will need to track (for each layer): - - [ ] inputs / outputs - - [ ] weights, gradients - - [ ] Start thread in Intel SC23 channel to discuss convergence issues - - [ ] Add hooks to track additional data +
-- [ ] Ensure / double check that optimizer settings from `ds_config.json` aren't being overwritten by some defaults in `megatron/arguments.py` - - [ ] specifically, `momentum, beta{1, 2}, etc` +
### Install From d9fc6e2bc4e607a84e633ea69c3ec8fa3e3401c9 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 7 Mar 2024 18:08:35 -0600 Subject: [PATCH 108/268] Update `ALCF/README.md` --- ALCF/README.md | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 76bb90ba5c..9a58b8b056 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -4,7 +4,7 @@
📅 2024-03-07 -- Unable to save checkpoints with `torch==2.1` + `cuda==11.8`: +- ‼️ Unable to save checkpoints with `torch==2.1` + `cuda==11.8`: - **NEED TO DEBUG / FIX !!** - Training progresses OK: @@ -89,14 +89,20 @@ $ module load conda/2023-10-04 $ export MPICC="cc -shared -taret-accel=nvidia80" $ export DAY=$(date "+%Y-%m-%d") - $ conda create --solver libmamba -c pytorch -c nvidia --name "${DAY}" "python==3.10" $ export PYTHONUSERBASE="${HOME}/.local/polaris/conda/${DAY}" + $ conda create --solver libmamba -c pytorch -c nvidia --name "${DAY}" "python==3.10" ``` + > [!NOTE] + > In the `conda create` command above, + > you can replace `--name "${DAY}"` with + > `--prefix /path/to/your/conda/envs`, if you prefer: + 3. Install dependencies: ```bash - $ conda install -c pytorch -c nvidia --solver libmamba mpi4py pytorch-cuda=11.8 ninja torchvision torchaudio pytorch-cuda=11.8 transformers xformers triton + $ conda activate "${DAY}" # e.g. 2024-03-07 + $ conda install -c pytorch -c nvidia --solver libmamba mpi4py ninja transformers xformers triton pytorch torchvision torchaudio pytorch-cuda=11.8 $ python3 -m pip install --upgrade pip pybind11 toolong appdirs wandb sentencepiece ipython setuptools wheel ninja $ python3 -m pip install --upgrade deepspeed wandb ``` @@ -106,6 +112,7 @@ ```bash $ git clone https://github.com/NVIDIA/apex $ cd apex + # NOTE: need GCC < 11 for APEX ¯\_(ツ)_/¯ ?? $ module swap gcc gcc/10.3.0 $ python3 -m pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./ ``` From e21451e1d7be832dae13ff869e761ece17ec2638 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 8 Mar 2024 15:34:53 -0600 Subject: [PATCH 109/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index e657334d23..8b3edf41f2 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -48,11 +48,11 @@ export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit run_cmd=" deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ + --use-flash-attn-v2 \ --$DTYPE \ --num-workers 0 \ --split 100,0,0 \ --log-interval 1 \ - --use-flash-attn-v2 \ --no-bias-gelu-fusion \ --lr-decay-style cosine \ --no-bias-dropout-fusion \ From e3327936be61dd55a953696754b2db27ac24f315 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 8 Mar 2024 15:35:10 -0600 Subject: [PATCH 110/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index ccb7c345ec..1e570ee43b 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -185,9 +185,11 @@ setEnv() { fi elif [[ $(hostname) == x3* ]]; then # ---- [Polaris] --------------------- # ---- [load conda] --------------------- - module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 - export PYTHONUSERBASE="${HOME}/.local/polaris/conda/2024-03-06" - mkdir -p "${PYTHONUSERBASE}" + module load conda/2023-10-04; conda activate cu118-pt221 + # module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/py311-cu118 + # ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 + # export PYTHONUSERBASE="${HOME}/.local/polaris/conda/py311-cu118" + # mkdir -p "${PYTHONUSERBASE}" # if [[ "${VIRTUAL_ENV}" ]]; then # echo "Caught VIRTUAL_ENV = ${VIRTUAL_ENV} from environment!!" # else From a57a21f6b2a8abf847f5ef599e1b1edcb5a5e1b5 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 8 Mar 2024 15:36:18 -0600 Subject: [PATCH 111/268] Fix checkpointing issue with `torch=2.2.1` in `megatron/model/gpt_model.py` --- megatron/model/gpt_model.py | 137 ++++++++++++++++++++++++++---------- 1 file changed, 101 insertions(+), 36 deletions(-) diff --git a/megatron/model/gpt_model.py b/megatron/model/gpt_model.py index 4545131217..4e1892e887 100644 --- a/megatron/model/gpt_model.py +++ b/megatron/model/gpt_model.py @@ -62,6 +62,21 @@ def post_language_model_processing(lm_output, labels, logit_weights, return loss +def CrossEntropy(output, labels): + labels, loss_mask = labels[0], labels[1] + + args = get_args() + + # [b s] => [s b] + labels = labels.transpose(0, 1).contiguous() + losses = tensor_parallel.vocab_parallel_cross_entropy(output.contiguous().float(), labels) + # [s b] => [b, s] + losses = losses.transpose(0, 1).contiguous() + loss_mask = loss_mask.view(-1) + loss = torch.sum(losses.view(-1) * loss_mask) / loss_mask.sum() + return loss + + class GPTModel(MegatronModule): """GPT-2 Language model.""" @@ -190,6 +205,62 @@ def _get_vocab_param_patterns(self): ] return patterns + @staticmethod + def _get_vocab_param_patterns(): + args = get_args() + if args.untie_embeddings_and_output_weights: + patterns = [ + r"\d+.word_embeddings.weight", + r"\d+.lm_head.weight" + ] + else: + patterns = [ + r"tied_modules.embed.word_embeddings.weight" + ] + return patterns + + @staticmethod + def _get_tp_replicated_param_patterns(): + args = get_args() + patterns = [ + r"\d+.input_layernorm.weight", + r"\d+.post_attention_layernorm.weight", + r"\d+.weight", + ] + if args.add_position_embedding: + patterns.append(r"tied_modules.embed.position_embeddings.weight") + if args.add_bias_linear: + patterns.extend([ + r"\d+.self_attention.dense.bias", + r"\d+.mlp.dense_4h_to_h.bias", + ]) + if args.normalization == 'layernorm': + patterns.extend([ + r"\d+.input_layernorm.bias", + r"\d+.post_attention_layernorm.bias", + r"\d+.bias", + ]) + return patterns + + @staticmethod + def _get_row_parallel_param_patterns(): + return [ + r"\d+.mlp.dense_4h_to_h.weight", + r"\d+.self_attention.dense.weight", + ] + + @staticmethod + def _get_swiglu_col_parallel_param_patterns(): + args = get_args() + if not args.swiglu: + return [] + patterns = [ + r"\d+.mlp.dense_h_to_4h.weight", + ] + if args.add_bias_linear: + patterns.append(r"\d+.mlp.dense_h_to_4h.bias") + return patterns + def universal_checkpoint_info(self): info = dict() args = get_args() @@ -197,7 +268,6 @@ def universal_checkpoint_info(self): if DS_UNIVERSAL_CHECKPOINT_INFO: # Vocabulary parameters (embeddings) that require special handling due to padding. info[VOCABULARY_PARAMETER_PATTERNS] = self._get_vocab_param_patterns() - if args.tensor_model_parallel_size > 1: # Parameter slices that should be averaged not concatenated. info[TP_REPLICATED_PARAMETER_PATTERNS] = self._get_tp_replicated_param_patterns() @@ -206,23 +276,9 @@ def universal_checkpoint_info(self): info[PARAMETER_WITH_ROW_PARALLELISM_PATTERNS] = self._get_row_parallel_param_patterns() return info - -def CrossEntropy(output, labels): - labels, loss_mask = labels[0], labels[1] - - args = get_args() - - # [b s] => [s b] - labels = labels.transpose(0, 1).contiguous() - losses = tensor_parallel.vocab_parallel_cross_entropy(output.contiguous().float(), labels) - # [s b] => [b, s] - losses = losses.transpose(0, 1).contiguous() - loss_mask = loss_mask.view(-1) - loss = torch.sum(losses.view(-1) * loss_mask) / loss_mask.sum() - return loss -class GPTModelPipe(PipelineModule,MegatronModule): +class GPTModelPipe(PipelineModule, MegatronModule): """GPT-2 Language model.""" def __init__(self, @@ -236,8 +292,9 @@ def __init__(self, config.init_method = init_method_normal(config.init_method_std) if config.output_layer_init_method is None: - config.output_layer_init_method = scaled_init_method_normal(config.init_method_std, - config.num_layers) + config.output_layer_init_method = scaled_init_method_normal( + config.init_method_std, + config.num_layers) self.specs = [] @@ -253,25 +310,33 @@ def _to_float16(inputs): # Embedding layer if args.untie_embeddings_and_output_weights: - self.specs.append(LayerSpec(EmbeddingPipe, - args.hidden_size, - args.padded_vocab_size, - args.max_position_embeddings, - args.hidden_dropout, - config, - num_tokentypes=num_tokentypes, - embedding_weights_in_fp32=args.embedding_weights_in_fp32,)) + self.specs.append( + LayerSpec( + EmbeddingPipe, + args.hidden_size, + args.padded_vocab_size, + args.max_position_embeddings, + args.hidden_dropout, + config, + num_tokentypes=num_tokentypes, + embedding_weights_in_fp32=args.embedding_weights_in_fp32, + ) + ) else: - self.specs.append(TiedLayerSpec('embed', - EmbeddingPipe, - args.hidden_size, - args.padded_vocab_size, - args.max_position_embeddings, - args.hidden_dropout, - config, - num_tokentypes=num_tokentypes, - embedding_weights_in_fp32=args.embedding_weights_in_fp32, - tied_weight_attr='word_embeddings_weight')) + self.specs.append( + TiedLayerSpec( + 'embed', + EmbeddingPipe, + args.hidden_size, + args.padded_vocab_size, + args.max_position_embeddings, + args.hidden_dropout, + config, + num_tokentypes=num_tokentypes, + embedding_weights_in_fp32=args.embedding_weights_in_fp32, + tied_weight_attr='word_embeddings_weight' + ) + ) for layer_idx in range(args.num_layers): self.specs.append( From fb7eaf7dccab338cdde9b34e9e6c9750755a7b67 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 9 Mar 2024 09:56:39 -0600 Subject: [PATCH 112/268] Update README.md --- ALCF/README.md | 57 +++++++++++++++++++++++++++----------------------- 1 file changed, 31 insertions(+), 26 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 9a58b8b056..bddab06a41 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -2,10 +2,36 @@ ## Polaris -
📅 2024-03-07 +
⬜ TODOs -- ‼️ Unable to save checkpoints with `torch==2.1` + `cuda==11.8`: - - **NEED TO DEBUG / FIX !!** +- Convergence: + - [ ] Use `bf16` on both systems + - [ ] Will need to track (for each layer): + - [ ] inputs / outputs + - [ ] weights, gradients + - [ ] Start thread in Intel SC23 channel to discuss convergence issues + - [ ] Add hooks to track additional data + +- [ ] Ensure / double check that optimizer settings from `ds_config.json` aren't being overwritten by some defaults in `megatron/arguments.py` + - [ ] specifically, `momentum, beta{1, 2}, etc` + +
✅ Completed + +- Continue runs on Polaris @ + - [x] 48 Nodes + - [x] 32 Nodes + - [x] 16 Nodes + - [x] 8 Nodes + - [x] 4 Nodes + +- [x] Then, try re-creating ( / fixing) conda with `cuda==12.1` + - 😔, failed. + +- ~~‼️ Unable to save checkpoints with `torch==2.1` + `cuda==11.8`~~: + - Fixed in [a57a21f](https://github.com/argonne-lcf/Megatron-DeepSpeed/commit/a57a21f6b2a8abf847f5ef599e1b1edcb5a5e1b5) + +
🐛 Bug + - Training progresses OK: ```bash @@ -45,30 +71,9 @@ ``` 🤔 +
-- Convergence: - - [ ] Use `bf16` on both systems - - [ ] Will need to track (for each layer): - - [ ] inputs / outputs - - [ ] weights, gradients - - [ ] Start thread in Intel SC23 channel to discuss convergence issues - - [ ] Add hooks to track additional data - -- [ ] Ensure / double check that optimizer settings from `ds_config.json` aren't being overwritten by some defaults in `megatron/arguments.py` - - [ ] specifically, `momentum, beta{1, 2}, etc` - - -
✅ Completed - -- Continue runs on Polaris @ - - [x] 48 Nodes - - [x] 32 Nodes - - [x] 16 Nodes - - [x] 8 Nodes - - [x] 4 Nodes - -- [x] Then, try re-creating ( / fixing) conda with `cuda==12.1` - - 😔, failed. +
From 99d12f4c62b507b5e5f0d05cadcf70c82333b28d Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Tue, 12 Mar 2024 00:54:28 -0500 Subject: [PATCH 113/268] added support for multiprocessing_context --- megatron/arguments.py | 1 + megatron/data/data_samplers.py | 2 +- train_llama_alcf_polaris_hzheng.sh | 22 +++++++++------------- 3 files changed, 11 insertions(+), 14 deletions(-) diff --git a/megatron/arguments.py b/megatron/arguments.py index faeac611bc..a83c369018 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -1307,6 +1307,7 @@ def _add_data_args(parser): help='Force to use certain index file.') group.add_argument('--repeated-dataloader', action='store_true', help='Once all the data has been loaded, reuse the DataLoader.') + group.add_argument('--multiprocessing-context', type=str, default='fork') return parser diff --git a/megatron/data/data_samplers.py b/megatron/data/data_samplers.py index 8eb2f2a668..0aae13abce 100644 --- a/megatron/data/data_samplers.py +++ b/megatron/data/data_samplers.py @@ -46,7 +46,7 @@ def build_pretraining_data_loader(dataset, consumed_samples): batch_sampler=batch_sampler, num_workers=args.num_workers, pin_memory=True, - # multiprocessing_context='spawn' + multiprocessing_context=args.multiprocessing_context ) if args.repeated_dataloader: loader=RepeatingLoader(loader) diff --git a/train_llama_alcf_polaris_hzheng.sh b/train_llama_alcf_polaris_hzheng.sh index 0ca7cb78bb..1fb5345eda 100755 --- a/train_llama_alcf_polaris_hzheng.sh +++ b/train_llama_alcf_polaris_hzheng.sh @@ -4,25 +4,21 @@ #PBS -q debug-scaling #PBS -l select=2 #PBS -l filesystems=eagle:grand:home -export PPN=4 -export MD=/home/hzheng/ALCF-Megatron-DeepSpeed -module load conda/2023-10-04 -#conda activate /soft/datascience/megatron-deepspeed/2023-10-04 -conda activate $HOME/PolarisAT/pyenvs/megatron/2023-10-04 cd ${PBS_O_WORKDIR} +export PPN=4 +export MD=/eagle/argonne_tpc/soft/Megatron-DeepSpeed +source /eagle/argonne_tpc/soft/conda.sh export PBS_JOBSIZE=$(cat $PBS_NODEFILE | uniq | wc -l) export TP=1 export PP=1 export MBS=1 export BS=$((MBS*PBS_JOBSIZE*PPN/PP/TP)) export SP=$((PBS_JOBSIZE*PPN/PP/TP)) -#export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/" - -export export DATE_TAG=$(date +"%Y-%m-%d-%H-%M-%S") -export DATA_PATH="/eagle/datasets//dolma/data_Llama2Tokenizer/wiki-en-simple/" -#export DATA_FILE_LIST="/eagle/datasets//dolma//data_file_list_select.txt" -DATA_FILE_LIST=$PWD/test.txt -echo "BS: $BS\n PP:$PP \n TP: $TP, PBS_JOBSIZE: $PBS_JOBSIZE" +export DATE_TAG=$(date +"%Y-%m-%d-%H-%M-%S") +export DATA_FILE_LIST="/eagle/datasets//dolma/data_file_list_reweighted.txt" +echo "BS: $BS - PP:$PP - TP: $TP, PBS_JOBSIZE: $PBS_JOBSIZE" +# First time running, it will compile the fused kernels, which will take about 10 mins +# >>> done with compiling and loading fused kernels. Compilation time: 545.468 seconds HIDDEN_SIZE=4096 NUM_LAYERS=32 @@ -32,7 +28,7 @@ TRAIN_ITERS=10 ZERO_STAGE=2 MODEL=LLAMA_7B OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} -MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --cpu-bind depth -d 16 --hostfile $PBS_NODEFILE python3 ./pretrain_gpt_alcf.py \ +MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec --pmi=pmix -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --cpu-bind depth -d 16 --hostfile $PBS_NODEFILE python3 ./pretrain_gpt_alcf.py \ --tensor-model-parallel-size ${TP} \ --pipeline-model-parallel-size ${PP} \ --num-layers ${NUM_LAYERS} \ From d91b237ba1460556f96c04e22d766b741d190e7d Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Tue, 12 Mar 2024 01:12:14 -0500 Subject: [PATCH 114/268] changed script to common environement --- ALCF/test_blend_full.sh | 14 +++++++------- ALCF/test_blendable_dataset.py | 26 +++++++++++++++----------- 2 files changed, 22 insertions(+), 18 deletions(-) diff --git a/ALCF/test_blend_full.sh b/ALCF/test_blend_full.sh index 4245304456..0218383980 100755 --- a/ALCF/test_blend_full.sh +++ b/ALCF/test_blend_full.sh @@ -6,16 +6,16 @@ #PBS -l filesystems=eagle:grand:home cd ${PBS_O_WORKDIR} export PPN=4 -export MD=/home/hzheng/ALCF-Megatron-DeepSpeed -module load conda/2023-10-04 -#conda activate /soft/datascience/megatron-deepspeed/2023-10-04 -conda activate $HOME/PolarisAT/pyenvs/megatron/2023-10-04 +export MD=/eagle/argonne_tpc/soft/Megatron-DeepSpeed +source /eagle/argonne_tpc/soft/conda.sh +export TRITON_CACHE_DIR=/tmp/.cache/ + export TP=1 export PP=1 export SP=128 export MBS=1 export BS=$((MBS*SP)) -export export DATE_TAG=$(date +"%Y-%m-%d-%H-%M-%S") +export DATE_TAG=$(date +"%Y-%m-%d-%H-%M-%S") export DATA_FILE_LIST="/eagle/datasets//dolma/data_file_list_reweighted.txt" HIDDEN_SIZE=4096 @@ -25,8 +25,9 @@ EMBEDDINGS=2048 TRAIN_ITERS=80797 ZERO_STAGE=2 MODEL=LLAMA_7B +export PBS_JOBSIZE=$(cat $PBS_NODEFILE | uniq | wc -l) OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} -python3 ALCF_utils/test_blendable_dataset.py \ +mpiexec --pmi=pmix -n $((PBS_JOBSIZE*PPN)) --ppn $PPN --cpu-bind depth -d 16 python3 ALCF/test_blendable_dataset.py \ --tensor-model-parallel-size ${TP} \ --pipeline-model-parallel-size ${PP} \ --num-layers ${NUM_LAYERS} \ @@ -51,7 +52,6 @@ python3 ALCF_utils/test_blendable_dataset.py \ --lr-warmup-iters 2 \ --optimizer adam \ --adam-beta1 0.9 \ - --mmap_warmup False \ --adam-beta2 0.95 \ --log-interval 1 \ --cpu-optimizer \ diff --git a/ALCF/test_blendable_dataset.py b/ALCF/test_blendable_dataset.py index a0cccbb6cb..503f499fab 100644 --- a/ALCF/test_blendable_dataset.py +++ b/ALCF/test_blendable_dataset.py @@ -5,12 +5,14 @@ from megatron.arguments import parse_args from megatron.initialize import initialize_megatron from megatron.data.data_samplers import build_pretraining_data_loader - +from mpi4py import MPI +comm = MPI.COMM_WORLD initialize_megatron(allow_no_cuda=True) args = get_args() data_file_list = args.data_file_list -print(f"Reading data from {args.data_file_list}") +if comm.rank==0: + print(f"Reading data from {args.data_file_list}") files = [] weights = [] flist = [] @@ -28,10 +30,10 @@ num_samples = args.global_batch_size*args.train_iters num_datasets = len(weights) - -print(f"Number of datasets: {num_datasets}") -print(f"Global batch size: {args.global_batch_size}") -print(f"Training iterations: {args.train_iters}") +if comm.rank==0: + print(f"Number of datasets: {num_datasets}") + print(f"Global batch size: {args.global_batch_size}") + print(f"Training iterations: {args.train_iters}") train_valid_test_num_samples = [num_samples, 0, 0] seed=args.seed data_impl = args.data_impl @@ -48,21 +50,23 @@ ratio_select=np.zeros(num_datasets) #for i in range(num_datasets): # ratio_select[i] = np.sum([i==d for d in dataset_idx])/num_samples - -print(f"Total number of samples: {len(train_ds)}") -print(f"Weights set: {weights[:min(8, num_datasets)]}") +if comm.rank ==0: + print(f"Total number of samples: {len(train_ds)}") + print(f"Weights set: {weights[:min(8, num_datasets)]}") #print(f"Weights across training: {ratio_select[:min(8, num_datasets)]}") for e in range(min(100, args.train_iters)): ratio_select=np.zeros(num_datasets) for i in range(num_datasets): ratio_select[i] = np.sum([i==d for d in dataset_idx[e*args.global_batch_size:(e+1)*args.global_batch_size]])/args.global_batch_size - print(f"iter-{e}: {ratio_select[:min(8, num_datasets)]}") + if comm.rank==0: + print(f"iter-{e}: {ratio_select[:min(8, num_datasets)]}") print("First 10 samples") for i in range(10): - print(f"Sample: {i} \t dataset_idx: {train_ds.dataset_index[i]}, sample_idx: {train_ds.dataset_sample_index[i]}") + if comm.rank==0: + print(f"Sample: {i} \t dataset_idx: {train_ds.dataset_index[i]}, sample_idx: {train_ds.dataset_sample_index[i]}") #### Build data loaders From 7df1664b6c8c61a4a786354b5c2a0ed26113eca7 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 12 Mar 2024 12:17:41 -0500 Subject: [PATCH 115/268] Update README.md --- ALCF/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index bddab06a41..252c2289d5 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -148,11 +148,11 @@ modules and launch # 1. Launch interactive job $ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I # 2. Load conda environment - $ module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 - # $ export PYTHONUSERBASE=/home/foremans/.local/polaris/conda/2024-03-06 + $ module load conda/2023-10-04 ; conda activate /eagle/datascience/foremans/miniconda3/envs/cu118-pt221 ; unset PYTHONUSERBASE # 3. Navigate into `Megatron-DeepSpeed` directory $ cd Megatron-DeepSpeed # 4. Launch: + $ export PBS_O_WORKDIR=$(pwd) $ bash train_llama_alcf_polaris.sh ```
[Output] From 9a954444fdd9dd5dbfb185af44061f95417a0851 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 12 Mar 2024 20:15:51 -0500 Subject: [PATCH 116/268] Pull in changes from `microsoft/Megatron-DeepSpeed@df0e2e4` --- megatron/model/gpt_model.py | 349 +++++++++++++++--------------------- 1 file changed, 144 insertions(+), 205 deletions(-) diff --git a/megatron/model/gpt_model.py b/megatron/model/gpt_model.py index 4e1892e887..0527765f16 100644 --- a/megatron/model/gpt_model.py +++ b/megatron/model/gpt_model.py @@ -62,19 +62,117 @@ def post_language_model_processing(lm_output, labels, logit_weights, return loss -def CrossEntropy(output, labels): - labels, loss_mask = labels[0], labels[1] +class UniversalCheckpointInfo: + def __init__(self, using_model_pipe: bool): + self.using_model_pipe = using_model_pipe + self.args = get_args() + self.info = self._build_universal_checkpoint_info() - args = get_args() + def get(self): + return self.info - # [b s] => [s b] - labels = labels.transpose(0, 1).contiguous() - losses = tensor_parallel.vocab_parallel_cross_entropy(output.contiguous().float(), labels) - # [s b] => [b, s] - losses = losses.transpose(0, 1).contiguous() - loss_mask = loss_mask.view(-1) - loss = torch.sum(losses.view(-1) * loss_mask) / loss_mask.sum() - return loss + def _build_universal_checkpoint_info(self): + info = dict() + if DS_UNIVERSAL_CHECKPOINT_INFO: + # Vocabulary parameters (embeddings) that require special handling due to padding. + info[VOCABULARY_PARAMETER_PATTERNS] = self._get_vocab_param_patterns() + + if self.using_model_pipe: + # Replicated (shared) parameters on the pipeline dimension + info[PIPELINE_REPLICATED_PARAMETER_PATTERNS] = self._get_pp_replicated_param_patterns() + + if self.args.tensor_model_parallel_size > 1: + # Parameter slices that should be averaged not concatenated. + info[TP_REPLICATED_PARAMETER_PATTERNS] = self._get_tp_replicated_param_patterns() + + # Parameter that are sliced on the row dimension + info[PARAMETER_WITH_ROW_PARALLELISM_PATTERNS] = self._get_row_parallel_param_patterns() + + # SWIGLU parameters are first sliced on dim=0 to tp slices + # Then, each tp slice is chunked into 2 to create the linear layers L1, L2 used for silu(L1(x)) * L2(x)) + info[PARAMETER_WITH_2_SUB_PARAMS_CAT_DIM_0] = self._get_swiglu_col_parallel_param_patterns() + return info + + def _get_vocab_param_patterns(self): + if self.using_model_pipe: + if self.args.untie_embeddings_and_output_weights: + patterns = [ + r"\d+.word_embeddings.weight", + r"\d+.lm_head.weight" + ] + else: + patterns = [ + r"tied_modules.embed.word_embeddings.weight" + ] + else: + patterns = [ + "language_model.embedding.word_embeddings.weight" + ] + if self.args.untie_embeddings_and_output_weights: + patterns.append("language_model.output_layer.weight") + return patterns + + def _get_pp_replicated_param_patterns(self): + if self.args.untie_embeddings_and_output_weights: + return [] + patterns = self._get_vocab_param_patterns() + if self.args.add_position_embedding: + patterns.append(r"tied_modules.embed.position_embeddings.weight") + return patterns + + def _layers_prefix(self): + return "" if self.using_model_pipe else "language_model.encoder.layers." + + def _get_tp_replicated_param_patterns(self): + layers_prefix = self._layers_prefix() + patterns = [ + layers_prefix + r"\d+.input_layernorm.weight", + layers_prefix + r"\d+.post_attention_layernorm.weight", + ] + # Add final normalization layer + final_norm_w_pattern = r"\d+.weight" if self.using_model_pipe \ + else "language_model.encoder.final_layernorm.weight" + patterns.append(final_norm_w_pattern) + if self.args.normalization == 'layernorm': + final_norm_b_pattern = r"\d+.bias" if self.using_model_pipe \ + else "language_model.encoder.final_layernorm.bias" + patterns.append(final_norm_b_pattern) + # add Positional Embedding + if self.args.add_position_embedding: + pos_emb_pattern = "tied_modules.embed.position_embeddings.weight" if self.using_model_pipe \ + else "language_model.embedding.position_embeddings.weight" + patterns.append(pos_emb_pattern) + # add Linear bias + if self.args.add_bias_linear: + patterns.extend([ + layers_prefix + r"\d+.self_attention.dense.bias", + layers_prefix + r"\d+.mlp.dense_4h_to_h.bias", + ]) + # add LN bias + if self.args.normalization == 'layernorm': + patterns.extend([ + layers_prefix + r"\d+.input_layernorm.bias", + layers_prefix + r"\d+.post_attention_layernorm.bias", + ]) + return patterns + + def _get_row_parallel_param_patterns(self): + layers_prefix = self._layers_prefix() + return [ + layers_prefix + r"\d+.mlp.dense_4h_to_h.weight", + layers_prefix + r"\d+.self_attention.dense.weight", + ] + + def _get_swiglu_col_parallel_param_patterns(self): + if not self.args.swiglu: + return [] + layers_prefix = self._layers_prefix() + patterns = [ + layers_prefix + r"\d+.mlp.dense_h_to_4h.weight", + ] + if self.args.add_bias_linear: + patterns.append(layers_prefix + r"\d+.mlp.dense_h_to_4h.bias") + return patterns class GPTModel(MegatronModule): @@ -192,93 +290,26 @@ def load_state_dict(self, state_dict, strict=True): state_dict["moe_state_dict"] = moe_state_dict self.language_model.load_state_dict(state_dict, strict=strict) - def _get_vocab_param_patterns(self): - args = get_args() - if args.untie_embeddings_and_output_weights: - patterns = [ - r"\d+.word_embeddings.weight", - r"\d+.lm_head.weight" - ] - else: - patterns = [ - r"tied_modules.embed.word_embeddings.weight" - ] - return patterns - - @staticmethod - def _get_vocab_param_patterns(): - args = get_args() - if args.untie_embeddings_and_output_weights: - patterns = [ - r"\d+.word_embeddings.weight", - r"\d+.lm_head.weight" - ] - else: - patterns = [ - r"tied_modules.embed.word_embeddings.weight" - ] - return patterns - - @staticmethod - def _get_tp_replicated_param_patterns(): - args = get_args() - patterns = [ - r"\d+.input_layernorm.weight", - r"\d+.post_attention_layernorm.weight", - r"\d+.weight", - ] - if args.add_position_embedding: - patterns.append(r"tied_modules.embed.position_embeddings.weight") - if args.add_bias_linear: - patterns.extend([ - r"\d+.self_attention.dense.bias", - r"\d+.mlp.dense_4h_to_h.bias", - ]) - if args.normalization == 'layernorm': - patterns.extend([ - r"\d+.input_layernorm.bias", - r"\d+.post_attention_layernorm.bias", - r"\d+.bias", - ]) - return patterns - - @staticmethod - def _get_row_parallel_param_patterns(): - return [ - r"\d+.mlp.dense_4h_to_h.weight", - r"\d+.self_attention.dense.weight", - ] - - @staticmethod - def _get_swiglu_col_parallel_param_patterns(): - args = get_args() - if not args.swiglu: - return [] - patterns = [ - r"\d+.mlp.dense_h_to_4h.weight", - ] - if args.add_bias_linear: - patterns.append(r"\d+.mlp.dense_h_to_4h.bias") - return patterns - def universal_checkpoint_info(self): - info = dict() - args = get_args() + return UniversalCheckpointInfo(using_model_pipe=False).get() - if DS_UNIVERSAL_CHECKPOINT_INFO: - # Vocabulary parameters (embeddings) that require special handling due to padding. - info[VOCABULARY_PARAMETER_PATTERNS] = self._get_vocab_param_patterns() - if args.tensor_model_parallel_size > 1: - # Parameter slices that should be averaged not concatenated. - info[TP_REPLICATED_PARAMETER_PATTERNS] = self._get_tp_replicated_param_patterns() - # Parameter that are sliced on the row dimension - info[PARAMETER_WITH_ROW_PARALLELISM_PATTERNS] = self._get_row_parallel_param_patterns() +def CrossEntropy(output, labels): + labels, loss_mask = labels[0], labels[1] - return info + args = get_args() + + # [b s] => [s b] + labels = labels.transpose(0, 1).contiguous() + losses = tensor_parallel.vocab_parallel_cross_entropy(output.contiguous().float(), labels) + # [s b] => [b, s] + losses = losses.transpose(0, 1).contiguous() + loss_mask = loss_mask.view(-1) + loss = torch.sum(losses.view(-1) * loss_mask) / loss_mask.sum() + return loss -class GPTModelPipe(PipelineModule, MegatronModule): +class GPTModelPipe(PipelineModule,MegatronModule): """GPT-2 Language model.""" def __init__(self, @@ -292,9 +323,8 @@ def __init__(self, config.init_method = init_method_normal(config.init_method_std) if config.output_layer_init_method is None: - config.output_layer_init_method = scaled_init_method_normal( - config.init_method_std, - config.num_layers) + config.output_layer_init_method = scaled_init_method_normal(config.init_method_std, + config.num_layers) self.specs = [] @@ -310,33 +340,25 @@ def _to_float16(inputs): # Embedding layer if args.untie_embeddings_and_output_weights: - self.specs.append( - LayerSpec( - EmbeddingPipe, - args.hidden_size, - args.padded_vocab_size, - args.max_position_embeddings, - args.hidden_dropout, - config, - num_tokentypes=num_tokentypes, - embedding_weights_in_fp32=args.embedding_weights_in_fp32, - ) - ) + self.specs.append(LayerSpec(EmbeddingPipe, + args.hidden_size, + args.padded_vocab_size, + args.max_position_embeddings, + args.hidden_dropout, + config, + num_tokentypes=num_tokentypes, + embedding_weights_in_fp32=args.embedding_weights_in_fp32,)) else: - self.specs.append( - TiedLayerSpec( - 'embed', - EmbeddingPipe, - args.hidden_size, - args.padded_vocab_size, - args.max_position_embeddings, - args.hidden_dropout, - config, - num_tokentypes=num_tokentypes, - embedding_weights_in_fp32=args.embedding_weights_in_fp32, - tied_weight_attr='word_embeddings_weight' - ) - ) + self.specs.append(TiedLayerSpec('embed', + EmbeddingPipe, + args.hidden_size, + args.padded_vocab_size, + args.max_position_embeddings, + args.hidden_dropout, + config, + num_tokentypes=num_tokentypes, + embedding_weights_in_fp32=args.embedding_weights_in_fp32, + tied_weight_attr='word_embeddings_weight')) for layer_idx in range(args.num_layers): self.specs.append( @@ -401,88 +423,5 @@ def _logits_helper(embedding, lm_output): activation_checkpoint_interval=interval, partition_method='type:transformer') - @staticmethod - def _get_vocab_param_patterns(): - args = get_args() - if args.untie_embeddings_and_output_weights: - patterns = [ - r"\d+.word_embeddings.weight", - r"\d+.lm_head.weight" - ] - else: - patterns = [ - r"tied_modules.embed.word_embeddings.weight" - ] - return patterns - - def _get_pp_replicated_param_patterns(self): - args = get_args() - if args.untie_embeddings_and_output_weights: - return [] - patterns = self._get_vocab_param_patterns() - if args.add_position_embedding: - patterns.append(r"tied_modules.embed.position_embeddings.weight") - return patterns - - @staticmethod - def _get_tp_replicated_param_patterns(): - args = get_args() - patterns = [ - r"\d+.input_layernorm.weight", - r"\d+.post_attention_layernorm.weight", - r"\d+.weight", - ] - if args.add_position_embedding: - patterns.append(r"tied_modules.embed.position_embeddings.weight") - if args.add_bias_linear: - patterns.extend([ - r"\d+.self_attention.dense.bias", - r"\d+.mlp.dense_4h_to_h.bias", - ]) - if args.normalization == 'layernorm': - patterns.extend([ - r"\d+.input_layernorm.bias", - r"\d+.post_attention_layernorm.bias", - r"\d+.bias", - ]) - return patterns - - @staticmethod - def _get_row_parallel_param_patterns(): - return [ - r"\d+.mlp.dense_4h_to_h.weight", - r"\d+.self_attention.dense.weight", - ] - - @staticmethod - def _get_swiglu_col_parallel_param_patterns(): - args = get_args() - if not args.swiglu: - return [] - patterns = [ - r"\d+.mlp.dense_h_to_4h.weight", - ] - if args.add_bias_linear: - patterns.append(r"\d+.mlp.dense_h_to_4h.bias") - return patterns - - def universal_checkpoint_info(self): - info = dict() - if DS_UNIVERSAL_CHECKPOINT_INFO: - # Vocabulary parameters (embeddings) that require special handling due to padding. - info[VOCABULARY_PARAMETER_PATTERNS] = self._get_vocab_param_patterns() - - # Replicated (shared) parameters on the pipeline dimension - info[PIPELINE_REPLICATED_PARAMETER_PATTERNS] = self._get_pp_replicated_param_patterns() - - # Parameter slices that should be averaged not concatenated. - info[TP_REPLICATED_PARAMETER_PATTERNS] = self._get_tp_replicated_param_patterns() - - # Parameter that are sliced on the row dimension - info[PARAMETER_WITH_ROW_PARALLELISM_PATTERNS] = self._get_row_parallel_param_patterns() - - # SWIGLU parameters are first sliced on dim=0 to tp slices - # Then, each tp slice is chunked into 2 to create the linear layers L1, L2 used for silu(L1(x)) * L2(x)) - info[PARAMETER_WITH_2_SUB_PARAMS_CAT_DIM_0] = self._get_swiglu_col_parallel_param_patterns() - return info + return UniversalCheckpointInfo(using_model_pipe=True).get() From 79c3067a125df5f8dc03558b5771acf55dd4fb7e Mon Sep 17 00:00:00 2001 From: Venkat Vishwanath Date: Wed, 13 Mar 2024 10:50:21 -0400 Subject: [PATCH 117/268] Update README.md --- ALCF/README.md | 10 ---------- 1 file changed, 10 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 252c2289d5..49b583aa24 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -2,16 +2,6 @@ ## Polaris -
⬜ TODOs - -- Convergence: - - [ ] Use `bf16` on both systems - - [ ] Will need to track (for each layer): - - [ ] inputs / outputs - - [ ] weights, gradients - - [ ] Start thread in Intel SC23 channel to discuss convergence issues - - [ ] Add hooks to track additional data - - [ ] Ensure / double check that optimizer settings from `ds_config.json` aren't being overwritten by some defaults in `megatron/arguments.py` - [ ] specifically, `momentum, beta{1, 2}, etc` From 15d422e306d97c6aab6cd0e4e42383a2039604b5 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Thu, 14 Mar 2024 19:20:00 -0500 Subject: [PATCH 118/268] fixing some NCCL issue and updated the script with the common environment --- ALCF/test_blend_full.sh | 4 ++-- ALCF/test_blendable_dataset.py | 11 +++++++---- megatron/data/gpt_dataset.py | 6 ++++-- pretrain_gpt_alcf.py | 3 ++- train_llama_alcf_polaris_hzheng.sh | 7 +++++-- 5 files changed, 20 insertions(+), 11 deletions(-) diff --git a/ALCF/test_blend_full.sh b/ALCF/test_blend_full.sh index 0218383980..459652a2ee 100755 --- a/ALCF/test_blend_full.sh +++ b/ALCF/test_blend_full.sh @@ -27,7 +27,7 @@ ZERO_STAGE=2 MODEL=LLAMA_7B export PBS_JOBSIZE=$(cat $PBS_NODEFILE | uniq | wc -l) OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} -mpiexec --pmi=pmix -n $((PBS_JOBSIZE*PPN)) --ppn $PPN --cpu-bind depth -d 16 python3 ALCF/test_blendable_dataset.py \ +APRUN_PMI=pmix aprun -n $((PBS_JOBSIZE*PPN)) -N $PPN --cc depth -d 16 ${MD}/local_rank.sh python3 ALCF/test_blendable_dataset.py \ --tensor-model-parallel-size ${TP} \ --pipeline-model-parallel-size ${PP} \ --num-layers ${NUM_LAYERS} \ @@ -70,4 +70,4 @@ mpiexec --pmi=pmix -n $((PBS_JOBSIZE*PPN)) --ppn $PPN --cpu-bind depth -d 16 py --data-path ${DATA_PATH} \ --data-cache-path /tmp/hzheng-megatron-deepspeed-cache/ \ --vocab-file ${MD}/dataset/gpt2-vocab.json --merge-file ${MD}/dataset/gpt2-merges.txt \ - --zero-stage=${ZERO_STAGE} --deepspeed_config=${MD}/ds_config-gpt.json --deepspeed + --zero-stage=${ZERO_STAGE} --deepspeed_config=${MD}/ds_config-gpt.json --deepspeed diff --git a/ALCF/test_blendable_dataset.py b/ALCF/test_blendable_dataset.py index 503f499fab..9681198251 100644 --- a/ALCF/test_blendable_dataset.py +++ b/ALCF/test_blendable_dataset.py @@ -6,6 +6,7 @@ from megatron.initialize import initialize_megatron from megatron.data.data_samplers import build_pretraining_data_loader from mpi4py import MPI +from megatron.core import mpu comm = MPI.COMM_WORLD initialize_megatron(allow_no_cuda=True) args = get_args() @@ -68,10 +69,12 @@ if comm.rank==0: print(f"Sample: {i} \t dataset_idx: {train_ds.dataset_index[i]}, sample_idx: {train_ds.dataset_sample_index[i]}") - #### Build data loaders -train_dataloader = build_pretraining_data_loader( +rank_in_parallel_group = mpu.get_sequence_parallel_rank() +print(rank_in_parallel_group) +if rank_in_parallel_group == 0: + train_dataloader = build_pretraining_data_loader( train_ds, args.consumed_train_samples) -valid_dataloader = build_pretraining_data_loader( + valid_dataloader = build_pretraining_data_loader( valid_ds, args.consumed_valid_samples) -test_dataloader = build_pretraining_data_loader(test_ds, 0) + test_dataloader = build_pretraining_data_loader(test_ds, 0) diff --git a/megatron/data/gpt_dataset.py b/megatron/data/gpt_dataset.py index 210a92c85e..84ccff9a8b 100644 --- a/megatron/data/gpt_dataset.py +++ b/megatron/data/gpt_dataset.py @@ -504,8 +504,10 @@ def _build_index_mappings(name, data_prefix, documents, sizes, data_cache_success = False counts = get_accelerator().LongTensor([data_cache_success]) - torch.distributed.all_reduce(counts, group=mpu.get_data_parallel_group()) - torch.distributed.all_reduce(counts, group=mpu.get_pipeline_model_parallel_group()) + if mpu.get_data_parallel_world_size() > 1: + torch.distributed.all_reduce(counts, group=mpu.get_data_parallel_group()) + if mpu.get_pipeline_model_parallel_world_size() > 1: + torch.distributed.all_reduce(counts, group=mpu.get_pipeline_model_parallel_group()) if counts[0].item() != ( torch.distributed.get_world_size() // torch.distributed.get_world_size(group=mpu.get_tensor_model_parallel_group()) // diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 4fefef795f..fae3309d5c 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -466,6 +466,7 @@ def train_valid_test_datasets_provider(train_val_test_num_samples): 'for GPT ...') files = [] if args.data_file_list is not None: + print_rank_0(f"Reading datasets from {args.data_file_list}") with open(args.data_file_list, 'r') as flist: for f in flist.readlines(): w, fname = f.split() @@ -479,7 +480,7 @@ def train_valid_test_datasets_provider(train_val_test_num_samples): files.append(path + f.split(".bin")[0]) else: files = args.data_path - print_rank_0(f"file list {files}") + train_ds, valid_ds, test_ds = build_train_valid_test_datasets( data_prefix=files, data_impl=args.data_impl, diff --git a/train_llama_alcf_polaris_hzheng.sh b/train_llama_alcf_polaris_hzheng.sh index 1fb5345eda..83d8a2c5a7 100755 --- a/train_llama_alcf_polaris_hzheng.sh +++ b/train_llama_alcf_polaris_hzheng.sh @@ -8,6 +8,7 @@ cd ${PBS_O_WORKDIR} export PPN=4 export MD=/eagle/argonne_tpc/soft/Megatron-DeepSpeed source /eagle/argonne_tpc/soft/conda.sh + export PBS_JOBSIZE=$(cat $PBS_NODEFILE | uniq | wc -l) export TP=1 export PP=1 @@ -27,8 +28,9 @@ EMBEDDINGS=2048 TRAIN_ITERS=10 ZERO_STAGE=2 MODEL=LLAMA_7B +#LAUNCHER="//eagle/argonne_tpc/soft/Megatron-DeepSpeed/..//conda/2024-03-11/lib/python3.10/site-packages/deepspeed/launcher/launcher_helper.py --launcher mpich " OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_mp${MP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} -MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec --pmi=pmix -n $((PBS_JOBSIZE*PPN)) -ppn $PPN --cpu-bind depth -d 16 --hostfile $PBS_NODEFILE python3 ./pretrain_gpt_alcf.py \ +APRUN_PMI=pmix aprun -n $((PBS_JOBSIZE*PPN)) -N $PPN --cc depth -d 16 /eagle/argonne_tpc/soft/Megatron-DeepSpeed/local_rank.sh python3 $LAUNCHER ./pretrain_gpt_alcf.py \ --tensor-model-parallel-size ${TP} \ --pipeline-model-parallel-size ${PP} \ --num-layers ${NUM_LAYERS} \ @@ -70,4 +72,5 @@ MASTER_ADDR=localhost MASTER_PORT=6543 mpiexec --pmi=pmix -n $((PBS_JOBSIZE*PPN) --data-file-list ${DATA_FILE_LIST} \ --data-path ${DATA_PATH} \ --vocab-file ${MD}/dataset/gpt2-vocab.json --merge-file ${MD}/dataset/gpt2-merges.txt \ - --zero-stage=${ZERO_STAGE} --deepspeed_config=${MD}/ds_config-gpt.json --deepspeed + --zero-stage=${ZERO_STAGE} --deepspeed_config=${MD}/ds_config-gpt.json --deepspeed \ + --data-cache-path ./data_cache_path/ From 73dc82a532d4d5b55cdcaf151887f7e867aeab96 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Thu, 14 Mar 2024 21:35:53 -0500 Subject: [PATCH 119/268] further allreduce check --- megatron/data/blendable_dataset.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/megatron/data/blendable_dataset.py b/megatron/data/blendable_dataset.py index f3276c6823..0220fa22e7 100644 --- a/megatron/data/blendable_dataset.py +++ b/megatron/data/blendable_dataset.py @@ -80,8 +80,10 @@ def _build_indices(): counts = get_accelerator().LongTensor([cache_success]) - torch.distributed.all_reduce(counts, group=mpu.get_data_parallel_group()) - torch.distributed.all_reduce(counts, group=mpu.get_pipeline_model_parallel_group()) + if mpu.get_data_parallel_world_size() > 1: + torch.distributed.all_reduce(counts, group=mpu.get_data_parallel_group()) + if mpu.get_pipeline_model_parallel_world_size() > 1: + torch.distributed.all_reduce(counts, group=mpu.get_pipeline_model_parallel_group()) if counts[0].item() != ( torch.distributed.get_world_size() // torch.distributed.get_world_size(group=mpu.get_tensor_model_parallel_group()) // From 4fe87d0f71708404a437684593442607558e4bb4 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Thu, 14 Mar 2024 23:41:38 -0500 Subject: [PATCH 120/268] Update gpt_dataset.py --- megatron/data/gpt_dataset.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/megatron/data/gpt_dataset.py b/megatron/data/gpt_dataset.py index 84ccff9a8b..210a92c85e 100644 --- a/megatron/data/gpt_dataset.py +++ b/megatron/data/gpt_dataset.py @@ -504,10 +504,8 @@ def _build_index_mappings(name, data_prefix, documents, sizes, data_cache_success = False counts = get_accelerator().LongTensor([data_cache_success]) - if mpu.get_data_parallel_world_size() > 1: - torch.distributed.all_reduce(counts, group=mpu.get_data_parallel_group()) - if mpu.get_pipeline_model_parallel_world_size() > 1: - torch.distributed.all_reduce(counts, group=mpu.get_pipeline_model_parallel_group()) + torch.distributed.all_reduce(counts, group=mpu.get_data_parallel_group()) + torch.distributed.all_reduce(counts, group=mpu.get_pipeline_model_parallel_group()) if counts[0].item() != ( torch.distributed.get_world_size() // torch.distributed.get_world_size(group=mpu.get_tensor_model_parallel_group()) // From 39be39565aceb16dbb8b2e04d41b45d183cfee71 Mon Sep 17 00:00:00 2001 From: Huihuo Zheng Date: Thu, 14 Mar 2024 23:47:58 -0500 Subject: [PATCH 121/268] Update blendable_dataset.py --- megatron/data/blendable_dataset.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/megatron/data/blendable_dataset.py b/megatron/data/blendable_dataset.py index 0220fa22e7..f3276c6823 100644 --- a/megatron/data/blendable_dataset.py +++ b/megatron/data/blendable_dataset.py @@ -80,10 +80,8 @@ def _build_indices(): counts = get_accelerator().LongTensor([cache_success]) - if mpu.get_data_parallel_world_size() > 1: - torch.distributed.all_reduce(counts, group=mpu.get_data_parallel_group()) - if mpu.get_pipeline_model_parallel_world_size() > 1: - torch.distributed.all_reduce(counts, group=mpu.get_pipeline_model_parallel_group()) + torch.distributed.all_reduce(counts, group=mpu.get_data_parallel_group()) + torch.distributed.all_reduce(counts, group=mpu.get_pipeline_model_parallel_group()) if counts[0].item() != ( torch.distributed.get_world_size() // torch.distributed.get_world_size(group=mpu.get_tensor_model_parallel_group()) // From b0c21335e23f16c3dcb0b666cec6b01376e66cc8 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 15 Mar 2024 14:51:41 -0500 Subject: [PATCH 122/268] Update `ALCF/helpers.sh` for SunSpot --- ALCF/helpers.sh | 181 ++++++++++++++++++++++++++++-------------------- 1 file changed, 105 insertions(+), 76 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 1e570ee43b..ccd24209c4 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -31,21 +31,23 @@ function setDSlauncher() { } setParams() { - # [Parallelism Settings] {{{ - if [[ $(hostname) == x4* ]]; then # ---- [AURORA] ---- - TP=${TP:-1} # • TP = 1 - PP=${PP:-1} # • PP = 1 - export CCL=${CCL:-ccl} # • CCL - export BE="${CCL}" # • BE = CCL - export DTYPE=${DTYPE:-bf16} # • DTYPE: bf16 - elif [[ $(hostname) == x3* ]]; then # ---- [POLARIS] ---- - PP=${PP:-1} # • PP = 1 - TP=${TP:-2} # • TP = 2 - export NCCL=${NCCL:-nccl} # • NCCL - export BE="${NCCL}" # • BE = NCCL - export DTYPE=${DTYPE:-fp16} # • DTYPE: FP16 + # ---- [Parallelism Settings] -------------------------------------------- + # -------- [Aurora] ---- || ----- [SunSpot] ------------ + if [[ $(hostname) == x4* || $(hostname) == x1* ]]; then + TP=${TP:-1} # TP = 1 + PP=${PP:-1} # PP = 1 + export CCL=${CCL:-ccl} # CCL + export BE="${CCL}" # BE = CCL + export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 + # -------- [Polaris] ----------------------------------- + elif [[ $(hostname) == x3* ]]; then + TP=${TP:-2} # TP = 2 + PP=${PP:-1} # PP = 1 + export NCCL=${NCCL:-nccl} # NCCL + export BE="${NCCL}" # BE = NCCL + export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 fi - # }}} + # ------------------------------------------------------------------------ export PP="${PP}" export TP="${TP}" export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" @@ -69,8 +71,10 @@ setParams() { export SAVE_INTERVAL=${SAVE_INTERVAL:-200} export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} - export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) - export TOKENIZER_MODEL="${TOKENIZER_MODEL:-"/eagle/datasets/dolma/utils/tokenizer.model"}" + # export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) + export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) + export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" + export TOKENIZER_MODEL="${TOKENIZER_MODEL:-"/home/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/tokenizer.model"}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" # ---------------------------------------------------- @@ -120,8 +124,9 @@ ezpz() { echo "Using $(which python3) to install \`ezpz\`:" python3 -m pip install -e ezpz > ezpz-install.log 2>&1 fi - source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit - source ezpz/src/ezpz/bin/getjobenv || exit + echo "Done with ezpz." + # source ezpz/src/ezpz/bin/savejobenv || exit # > /tmp/savejobenv.log 2>&1 || exit + # source ezpz/src/ezpz/bin/getjobenv || exit } saveDSenv() { @@ -151,7 +156,10 @@ setOutput() { buildDSconfig() { # ---- Build DeepSpeed Config --------------------------------- export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" - bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit 1 + echo "DS_CONFIG: ${DS_CONFIG}" + printf "ZS: %s, MB: %s, GB: %s, PP: %s, DTYPE: %s" ${ZERO_STAGE} ${MICRO_BATCH} ${GLOBAL_BATCH} ${PP} ${DTYPE} + # generateConfig "${DS_CONFIG}" + bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" #|| exit 1 # ------------------------------------------------------------- } @@ -174,18 +182,24 @@ sumFiles() { setEnv() { - if [[ $(hostname) == x4* ]]; then # ---- [Aurora] ---------------------- - SETENV_FILE="${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" - if [[ "${SETENV_FILE}" ]]; then - # shellcheck source=/home/foremans/anl_24_release_q4/llm.devkit/setenv.sh - source "${HOME}/anl_24_release_q4/llm.devkit/setenv.sh" || exit - else - echo "Unable to source ${SETENV_FILE}, exiting!" - exit + # ---- [SunSpot] ------- || ---- [Aurora] -------------- + if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then + PBS_PARENT=$(dirname ${PBS_O_WORKDIR}) + echo "Sourcing ${PBS_PARENT}/setenv.sh..." + source "${PBS_PARENT}/setenv.sh" || exit + # ----- [Aurora] ----------------------------------- + if [[ $(hostname) == x4* ]]; then + eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate anl_release_q4v2 + # ----- [SunSpot] ---------------------------------- + elif [[ $(hostname) == x1* ]]; then + echo "Running on SunSpot !!" + eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate q4-drop fi - elif [[ $(hostname) == x3* ]]; then # ---- [Polaris] --------------------- + # ----- [Polaris] --------------------------------------- + elif [[ $(hostname) == x3* ]]; then + echo "Running on Polaris !!" # ---- [load conda] --------------------- - module load conda/2023-10-04; conda activate cu118-pt221 + module load conda/2023-10-04; conda activate cu118-pt221 ; unset PYTHONUSERBASE # module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/py311-cu118 # ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 # export PYTHONUSERBASE="${HOME}/.local/polaris/conda/py311-cu118" @@ -203,8 +217,13 @@ setEnv() { } makeHostfiles() { - GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') - export GPUS_PER_NODE="${GPUS_PER_NODE}" + # GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') + # source $(python3 -c 'import ezpz; print(ezpz.SAVEJOBENV.as_posix())') || exit + # source $(python3 -c 'import ezpz; print(ezpz.GETJOBENV.as_posix())') || exit + source ezpz/src/ezpz/bin/savejobenv || exit #> /tmp/savejobenv.log 2>&1 & + source ezpz/src/ezpz/bin/getjobenv || exit + export GPUS_PER_NODE="${NGPU_PER_HOST}" + # export GPUS_PER_NODE="${GPUS_PER_NODE}" # ---- Make MPICH hostfile ---------------- export hostfile_mpich=hostfile_mpich cat "$PBS_NODEFILE" > "${hostfile_mpich}" @@ -215,7 +234,16 @@ makeHostfiles() { } setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- - dfl="${1:-/eagle/datasets/dolma/data_file_list_reweighted.txt}" + if [[ $(hostname) == x4* ]]; then # ---- [AURORA] ---- + dfl_fallback="/home/foremans/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed/data_file_list_reweighted.txt" + elif [[ $(hostname) == x1* ]]; then + dfl_fallback="/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_file_list_reweighted.txt" + elif [[ $(hostname) == x3* ]]; then + dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" + else + echo "Unknown hostname. Must manually specify DATA_FILE_LIST." + fi + dfl="${1:-${dfl_fallback}}" # dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" printf "Calling: \`setData()\` with %s\n" "${dfl}" ndocs=$(wc -l < "${dfl}") @@ -238,50 +266,51 @@ setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- echo "--------------------" } -buildCLIargs() { # ---- [BROKEN] ------------------------------------------- - custom_args=" $@" - export CLI_ARGS=" - --$DTYPE \ - --num-workers 0 \ - --split 100,0,0 \ - --log-interval 1 \ - --use-flash-attn-v2 \ - --no-bias-gelu-fusion \ - --lr-decay-style cosine \ - --no-bias-dropout-fusion \ - --no-masked-softmax-fusion \ - --tokenizer-type Llama2Tokenizer \ - --no-gradient-accumulation-fusion \ - --accumulate-allreduce-grads-in-fp32 \ - --use-checkpoint-opt_param-scheduler \ - --lr ${LR} \ - --save ${CKPT_DIR} \ - --load ${CKPT_DIR} \ - --seq-length ${SEQ} \ - --num-layers ${NLAYERS} \ - --hidden-size ${HIDDEN} \ - --train-iters ${TRAIN_ITER} \ - --eval-iters ${EVAL_ITERS} \ - --distributed-backend ${NCCL} \ - --num-attention-heads ${HEADS} \ - --save-interval ${SAVE_INTERVAL} \ - --eval-interval ${EVAL_INTERVAL} \ - --max-position-embeddings ${SEQ} \ - --micro-batch-size ${MICRO_BATCH} \ - --data-file-list ${DATA_FILE_LIST} \ - --tensor-model-parallel-size ${TP} \ - --global-batch-size ${GLOBAL_BATCH} \ - --pipeline-model-parallel-size ${PP} \ - --num-key-value-heads ${NUM_KV_HEAD} \ - --data-cache-path ${DATA_CACHE_PATH} \ - --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ - --tokenizer-model ${TOKENIZER_MODEL} \ - $ds_args \ - ${LLAMA_ARGS} \ - ${gpt_args[*]} \ - ${custom_args} \ - " -} +# buildCLIargs() { # ---- [BROKEN] ------------------------------------------- +# custom_args=" $@" +# export CLI_ARGS=" +# --$DTYPE \ +# --num-workers 0 \ +# --split 100,0,0 \ +# --log-interval 1 \ +# --use-flash-attn-v2 \ +# --no-bias-gelu-fusion \ +# --lr-decay-style cosine \ +# --no-bias-dropout-fusion \ +# --no-masked-softmax-fusion \ +# --tokenizer-type Llama2Tokenizer \ +# --no-gradient-accumulation-fusion \ +# --accumulate-allreduce-grads-in-fp32 \ +# --use-checkpoint-opt_param-scheduler \ +# --lr ${LR} \ +# --save ${CKPT_DIR} \ +# --load ${CKPT_DIR} \ +# --seq-length ${SEQ} \ +# --num-layers ${NLAYERS} \ +# --hidden-size ${HIDDEN} \ +# --train-iters ${TRAIN_ITER} \ +# --eval-iters ${EVAL_ITERS} \ +# --distributed-backend ${BE} \ +# --num-attention-heads ${HEADS} \ +# --save-interval ${SAVE_INTERVAL} \ +# --eval-interval ${EVAL_INTERVAL} \ +# --max-position-embeddings ${SEQ} \ +# --micro-batch-size ${MICRO_BATCH} \ +# --data-file-list ${DATA_FILE_LIST} \ +# --tensor-model-parallel-size ${TP} \ +# --global-batch-size ${GLOBAL_BATCH} \ +# --pipeline-model-parallel-size ${PP} \ +# --num-key-value-heads ${NUM_KV_HEAD} \ +# --data-cache-path ${DATA_CACHE_PATH} \ +# --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ +# --tokenizer-model ${TOKENIZER_MODEL} \ +# $ds_args \ +# ${LLAMA_ARGS} \ +# ${gpt_args[*]} \ +# ${custom_args} \ +# " +# } + printBlack() { printf "\e[1;30m%s\e[0m\n" "$@" From e27f381da714402ed417dd4a5e0339682f8f1be8 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 15 Mar 2024 17:58:54 -0500 Subject: [PATCH 123/268] Add `train_llama_alcf_sunspot.sh` --- train_llama_alcf_sunspot.sh | 167 ++++++++++++++++++++++++++++++++++++ 1 file changed, 167 insertions(+) create mode 100644 train_llama_alcf_sunspot.sh diff --git a/train_llama_alcf_sunspot.sh b/train_llama_alcf_sunspot.sh new file mode 100644 index 0000000000..ad45ee8ba2 --- /dev/null +++ b/train_llama_alcf_sunspot.sh @@ -0,0 +1,167 @@ +#!/bin/bash --login +#PBS -l walltime=06:00:00 +#PBS -A argonne_tpc +#PBS -q prod +#PBS -l select=48 +#PBS -l filesystems=eagle:home + +function sourceFile() { + fp="$1" + echo "source-ing ${fp}" + if [[ -f "${fp}" ]]; then + # shellcheck source="${fp}" + source "${fp}" + else + echo "ERROR: UNABLE TO SOURCE ${fp}" + fi +} + +module () { + if [ -z "${LMOD_SH_DBG_ON+x}" ] + then + case "$-" in + (*v*x*) __lmod_sh_dbg='vx' ;; + (*v*) __lmod_sh_dbg='v' ;; + (*x*) __lmod_sh_dbg='x' ;; + esac + fi + if [ -n "${__lmod_sh_dbg:-}" ] + then + set +$__lmod_sh_dbg + echo "Shell debugging temporarily silenced: export LMOD_SH_DBG_ON=1 for Lmod's output" >&2 + fi + eval "$($LMOD_CMD $LMOD_SHELL_PRGM "$@")" && eval "$(${LMOD_SETTARG_CMD:-:} -s sh)" + __lmod_my_status=$? + if [ -n "${__lmod_sh_dbg:-}" ] + then + echo "Shell debugging restarted" >&2 + set -$__lmod_sh_dbg + fi + unset __lmod_sh_dbg + return $__lmod_my_status +} + +# +# eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" +# conda activate q4-drop + + + +# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +# ---- 0. Navigate into `$PBS_O_WORKDIR` ------------------------------------- +cd "${PBS_O_WORKDIR}" || exit +HERE=$(python3 -c 'import os; print(os.getcwd())') +export HERE + +# PARENT="$(dirname "${HERE}")" +# source "${PARENT}/setenv.sh" || exit +# ---- 1. Assert `./pretrain_gpt_alcf.py` exists: ----------------------------- +export EXEC="${HERE}/pretrain_gpt_alcf.py" +[ -f "${EXEC}" ] || exit +# ---- 2. `source ./ALCF/helpers_alcf.sh`: ------------------------------------ +sourceFile "${HERE}/ALCF/helpers.sh" || exit +# ---- 3. Call fns from `./ALCF/helpers_alcf.sh` ------------------------------ +setEnv || exit # 1. load `conda` environment +saveDSenv || exit # 2. save env vars to `.deepspeed_env` +ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars +makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` +buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ +setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} +setArgs || exit # 8. specify additional `deepspeed` arguments +setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset +setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` +printJobInfo || exit # 11. print job info +# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + +# Take custom args +custom_args=" $@" + +# Assert `./hostfile_deepspeed` exists +export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit + +# hf="${HOSTFILE:-${PBS_NODEFILE}}" +# nh=$(wc -l "${hf}") +# if [[ "${nh}" -gt 1 ]]; then +# launch_cmd="deepspeed --hostfile $hfds --launcher MPICH ${EXEC}" +# else +# launch_cmd="python3 ${EXEC}" +# fi +# +# echo "launch_cmd: ${launch_cmd}" + + # --use-flash-attn-v2 \ + # python3 ${EXEC} \ +run_cmd=" + deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ + --$DTYPE \ + --num-workers 0 \ + --split 100,0,0 \ + --log-interval 1 \ + --no-bias-gelu-fusion \ + --lr-decay-style cosine \ + --no-bias-dropout-fusion \ + --no-masked-softmax-fusion \ + --tokenizer-type Llama2Tokenizer \ + --no-gradient-accumulation-fusion \ + --accumulate-allreduce-grads-in-fp32 \ + --use-checkpoint-opt_param-scheduler \ + --lr ${LR} \ + --seq-length $SEQ \ + --save ${CKPT_DIR} \ + --load ${CKPT_DIR} \ + --num-layers ${NLAYERS} \ + --hidden-size ${HIDDEN} \ + --train-iters ${TRAIN_ITER} \ + --eval-iters ${EVAL_ITERS} \ + --distributed-backend ${BE} \ + --num-attention-heads ${HEADS} \ + --save-interval ${SAVE_INTERVAL} \ + --eval-interval ${EVAL_INTERVAL} \ + --max-position-embeddings ${SEQ} \ + --micro-batch-size ${MICRO_BATCH} \ + --data-file-list ${DATA_FILE_LIST} \ + --tensor-model-parallel-size ${TP} \ + --global-batch-size ${GLOBAL_BATCH} \ + --pipeline-model-parallel-size ${PP} \ + --num-key-value-heads ${NUM_KV_HEAD} \ + --data-cache-path ${DATA_CACHE_PATH} \ + --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ + --tokenizer-model ${TOKENIZER_MODEL} \ + ${LLAMA_ARGS} \ + $ds_args \ + ${gpt_args[*]} \ + $custom_args \ + |& tee ${OUTPUT_LOG} + " + + # --------------------------------------------------- + # --vocab-file $VOCAB_FILE \ + # --merge-file $MERGE_FILE \ + # --lr-decay-iters 320000 \ + # --lr-warmup-iters 5000 \ + # --lr-decay-iters 10000 \ + # --num-workers 4 \ + # launch python3 ${EXEC} \ + # --data-impl mmap \ + # source ./ezpz/src/ezpz/bin/getjobenv || exit + # --------------------------------------------------- + # ${DIST_LAUNCH} ./local_rank.sh python3 ${EXEC} \ + # ${DIST_LAUNCH} python3 ${EXEC} \ + # deepspeed $launcher ${EXEC} \ + # >> ${OUTPUT_LOG} 2>&1 & + # >> ${OUTPUT_LOG} 2>&1 & + # |& tee $OUTPUT_DIR/output.log + # ${EXTRA_ARGS} \ + +echo "All DeepSpeed(s): $(which -a deepspeed)" +echo "Using $(which deepspeed)" +ds_report + +echo "${run_cmd}" + +printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" +printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" +# echo "${OUTPUT_LOG}" +eval "${run_cmd}" +set +x From 7bfef8f559c42cb2d9e1b523ca864278ad293de0 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 16 Mar 2024 02:05:39 -0500 Subject: [PATCH 124/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index ccd24209c4..5cefe4829d 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -39,6 +39,7 @@ setParams() { export CCL=${CCL:-ccl} # CCL export BE="${CCL}" # BE = CCL export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 + MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 # -------- [Polaris] ----------------------------------- elif [[ $(hostname) == x3* ]]; then TP=${TP:-2} # TP = 2 @@ -46,6 +47,7 @@ setParams() { export NCCL=${NCCL:-nccl} # NCCL export BE="${NCCL}" # BE = NCCL export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 + MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 fi # ------------------------------------------------------------------------ export PP="${PP}" @@ -74,7 +76,9 @@ setParams() { # export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" - export TOKENIZER_MODEL="${TOKENIZER_MODEL:-"/home/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/tokenizer.model"}" + tm_a=/home/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/tokenizer.model + tm_p="/eagle/datasets/dolma/utils/tokenizer.model" + export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm_p:-${tm_a}}}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" # ---------------------------------------------------- @@ -222,14 +226,14 @@ makeHostfiles() { # source $(python3 -c 'import ezpz; print(ezpz.GETJOBENV.as_posix())') || exit source ezpz/src/ezpz/bin/savejobenv || exit #> /tmp/savejobenv.log 2>&1 & source ezpz/src/ezpz/bin/getjobenv || exit - export GPUS_PER_NODE="${NGPU_PER_HOST}" - # export GPUS_PER_NODE="${GPUS_PER_NODE}" + export GPUS_PER_NODE="${GPUS_PER_NODE:-${NGPU_PER_HOST}}" # ---- Make MPICH hostfile ---------------- + hf="${HOSTFILE:-${PBS_NODEFILE}}" export hostfile_mpich=hostfile_mpich - cat "$PBS_NODEFILE" > "${hostfile_mpich}" + cat "${hf}" > "${hostfile_mpich}" # ---- Make DeepSpeed hostfile ------------------- export hostfile_deepspeed=hostfile_deepspeed - cat "$PBS_NODEFILE" > "${hostfile_deepspeed}" + cat "${hf}" > "${hostfile_deepspeed}" sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" } From 9c6b8932d24ecaf42c9a9d9c339ac7034a29383c Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 16 Mar 2024 09:39:50 -0500 Subject: [PATCH 125/268] Update `train_llama_alcf_sunspot.sh` --- train_llama_alcf_sunspot.sh | 1 + 1 file changed, 1 insertion(+) diff --git a/train_llama_alcf_sunspot.sh b/train_llama_alcf_sunspot.sh index ad45ee8ba2..d4cec63e33 100644 --- a/train_llama_alcf_sunspot.sh +++ b/train_llama_alcf_sunspot.sh @@ -95,6 +95,7 @@ export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit run_cmd=" deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ --$DTYPE \ + --cpu-optimizer \ --num-workers 0 \ --split 100,0,0 \ --log-interval 1 \ From 41a23f16f5741c5cef37254486be5b27f1d91513 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 16 Mar 2024 09:40:10 -0500 Subject: [PATCH 126/268] Add `ALCF/tokenizer.model` --- ALCF/helpers.sh | 8 +++++--- ALCF/tokenizer.model | Bin 0 -> 499723 bytes 2 files changed, 5 insertions(+), 3 deletions(-) create mode 100644 ALCF/tokenizer.model diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 5cefe4829d..c328f0ec63 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -76,9 +76,11 @@ setParams() { # export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" - tm_a=/home/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/tokenizer.model - tm_p="/eagle/datasets/dolma/utils/tokenizer.model" - export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm_p:-${tm_a}}}" + tm="${PBS_O_WORKDIR}/ALCF/tokenizer.model" + # tm_a=/home/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/tokenizer.model + # tm_p="/eagle/datasets/dolma/utils/tokenizer.model" + # export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm_p:-${tm_a}}}" + export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" # ---------------------------------------------------- diff --git a/ALCF/tokenizer.model b/ALCF/tokenizer.model new file mode 100644 index 0000000000000000000000000000000000000000..22bccbcb41ec929cf0c9dbe8f41036db82e5e773 GIT binary patch literal 499723 zcma%^36x~lS>GSn7-+l{i^1$=Sy&@mmP^t|8X3ucJu^Mhh#5^;J+d&i>{s1gJyTM5 zSE-j7jck!8gN*?L#b(T21_Ksg(w5}~OSYfYh7dwXH6er$LMjd+gb>mpgb+eVe*f?P 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zOgEcfQ->L*e?qj*6!)HEyw4Ixa;V#EvA-YtIWP^p!62C{Ioiy?n`b5;F(J(t$I8AS z)r-9bW`l)hvm5^{GOi^$78@53=u6E00x_}F_#y*lnKNsD)Iw19nZJSzi1-t;r0BD(G|w-K3k>Oa|7svIMkd+!WT!}BN5f&XcMEk zM(ppW%u~khGUsV=-zn^CjonmNC-&T(f_iZ>K;0U|sbiFLA!9@Q2E|eLshuWq>>zD# z5hrT!TbnrP9+|%^?saDd?c!7gz1t!7-NPo=#IXW0?{#tCDaz~=N8LNfH^d?L%te>k zySJ&k#or#J{x?nkfwz21fGh0 zw?KU+j=Q&Bp8wmmVee-T{;N0m^_ic){T4sJ$3f^sed}HKgW7NX`ILWpYs%!wZ@$H^ zrEdAhUu>KFm;C+3TkP_SfBxx@|L(1~woMt4Jv#7Wz~rnM1Gm1ted|veU;g*MSsutg z^Va6e`G5T{Sy{9HCNN-e!GP@I0p94c0Rt)ryjnA0K;3`=!2ts<56HScU_keP0fFoR z1=$0Nv$M*w2b{>xx}2SLJ$pcRc6Lwp|IPdj2xtGn=y1;aqkFUeU?#uEGV4k9_h!B~ z>qYj!nQy!|EBAYUFmv Date: Sat, 16 Mar 2024 12:32:35 -0500 Subject: [PATCH 127/268] Add `generate_config_cpu_optimizer.sh` + Update `ALCF/helpers.sh` to toggle between --- ALCF/helpers.sh | 8 +- generate_config_cpu_optimizer.sh | 151 +++++++++++++++++++++++++++++++ 2 files changed, 158 insertions(+), 1 deletion(-) create mode 100644 generate_config_cpu_optimizer.sh diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index c328f0ec63..be3764450c 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -165,7 +165,13 @@ buildDSconfig() { echo "DS_CONFIG: ${DS_CONFIG}" printf "ZS: %s, MB: %s, GB: %s, PP: %s, DTYPE: %s" ${ZERO_STAGE} ${MICRO_BATCH} ${GLOBAL_BATCH} ${PP} ${DTYPE} # generateConfig "${DS_CONFIG}" - bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" #|| exit 1 + use_cpu_opt=$1 + if [[ $use_cpu_opt ]]; then + echo "!!! Using CPU Optimizer !!!" + bash "${PBS_O_WORKDIR}/generate_config_cpu_optimizer.sh" "${DS_CONFIG}" + else + bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" #|| exit 1 + fi # ------------------------------------------------------------- } diff --git a/generate_config_cpu_optimizer.sh b/generate_config_cpu_optimizer.sh new file mode 100644 index 0000000000..99dec97958 --- /dev/null +++ b/generate_config_cpu_optimizer.sh @@ -0,0 +1,151 @@ +#!/bin/bash --login + +for v in "$GLOBAL_BATCH" "$MICRO_BATCH" "$GRAD_ACC_STEPS" "$ZERO_STAGE" \ + "$PP" "$DTYPE" +do + if [ -z $v ]; then + echo "Please export required envs before execute $0" + exit 1 + fi +done + +if [ $# -ne 1 ]; then + echo "Usage: $0 config_file" + exit 1 +fi + +extra="" +common="\ + \"train_batch_size\": $GLOBAL_BATCH, + \"train_micro_batch_size_per_gpu\": $MICRO_BATCH, + \"steps_per_print\": 1, + \"gradient_accumulation_steps\": $GRAD_ACC_STEPS, + \"optimizer\": { + \"type\": \"AdamW\", + \"params\": { + \"lr\": ${LR}, + \"beta1\": 0.9, + \"beta2\": 0.95, + \"eps\": 1e-5, + \"weight_decay\": 1e-1 + } + }, + \"scheduler\": { + \"type\": \"WarmupLR\", + \"params\": { + \"warmup_min_lr\": 0.00003, + \"warmup_max_lr\": 0.0003, + \"warmup_num_steps\": 5000 + } + }, + \"zero_allow_untested_optimizer\": true, + \"gradient_clipping\": 1.0, + \"activation_checkpointing\": { + \"partition_activations\": true, + \"contiguous_memory_optimization\": false + }, + \"wall_clock_breakdown\": false," + +flops_profiler="\ + \"flops_profiler\": { + \"enabled\": false, + \"profile_step\": 45, + \"module_depth\": -1, + \"top_modules\": 1, + \"detailed\": true, + \"output_file\": null + }" + +if [[ $DTYPE == "bf16" ]]; then +dtype="\ + \"communication_data_type\": \"bfp16\", + \"fp16\": { + \"enabled\": false, + \"loss_scale\": 0, + \"loss_scale_window\": 1000, + \"hysteresis\": 2, + \"min_loss_scale\": 1 + }, + \"bfloat16\": { + \"enabled\": true, + \"loss_scale\": 1.0 + }," +else +dtype="\ + \"communication_data_type\": \"fp16\", + \"fp16\": { + \"enabled\": true, + \"loss_scale\": 0, + \"loss_scale_window\": 1000, + \"hysteresis\": 2, + \"min_loss_scale\": 1 + }, + \"bfloat16\": { + \"enabled\": false, + \"loss_scale\": 1.0 + }," +fi + +if [ $ZERO_STAGE == 3 ]; then +zero="\ + \"zero_optimization\": { + \"stage\": 3, + \"reduce_scatter\": false, + \"stage3_max_live_parameters\": 3e9, + \"stage3_max_reuse_distance\": 3e9, + \"stage3_param_persistence_threshold\": 1e5, + \"stage3_prefetch_bucket_size\": 5e7, + \"contiguous_gradients\": true, + \"overlap_comm\": true, + \"reduce_bucket_size\": 90000000, + \"sub_group_size\": 1e9, + \"offload_optimizer\": { + \"device\": \"none\", + \"buffer_count\": 4, + \"pipeline_read\": false, + \"pipeline_write\": false, + \"pin_memory\": true + } + }," +elif [ $ZERO_STAGE == 2 ] || [ $ZERO_STAGE == 1 ]; then +zero="\ + \"zero_optimization\": { + \"stage\": $ZERO_STAGE, + \"offload_optimizer\": { + \"device\": \"cpu\", + \"buffer_count\": 4, + \"pipeline_read\": false, + \"pipeline_write\": false, + \"pin_memory\": true + } + }," + if [ $ZERO_STAGE == 1 ]; then + if [ $PP > 1 ]; then + extra="\ + \"data_types\": { + \"grad_accum_dtype\": \"fp32\" + }, + \"comms_logger\": { + \"enabled\": true, + \"verbose\": false, + \"prof_all\": true, + \"debug\": false + }," + else + echo 'please add the config for zero_stage 1 without pipeline-parallelism' + fi + fi +else + echo 'Please add the correct config set!!!' +fi + +# flops_profiler must at the end because no ',' is allowed at the end +cat < $1 +{ +$common +$zero +$dtype +$extra +$flops_profiler +} +EOT From 20492989b48a16855c3b4cbc4b9b522ee9a960eb Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 16 Mar 2024 12:52:17 -0500 Subject: [PATCH 128/268] Catch `CPU_OPTIMIZER` in `ALCF/helpers.sh` @ `setParams()` --- ALCF/helpers.sh | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index be3764450c..c0c68b3537 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -83,6 +83,10 @@ setParams() { export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" + if [[ "${CPU_OPTIMIZER:-0}" ]]; then + echo "\n!!! Appending \`--cpu-optimizer\` to LLAMA_ARGS..." + export LLAMA_ARGS="${LLAMA_ARGS} --cpu-optimizer" + fi # ---------------------------------------------------- } From f44f61afd2d11fd8c340139c6db71894ca4b5d01 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 16 Mar 2024 12:52:49 -0500 Subject: [PATCH 129/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 29 ++++++++--------------------- 1 file changed, 8 insertions(+), 21 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index 8b3edf41f2..915b5435c8 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -32,7 +32,7 @@ saveDSenv || exit # 2. save env vars to `.deepspeed_env` ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` -buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ +buildDSconfig "${CPU_OPTIMIZER:-0}" || exit # 6. create `deepspeed_config.json` from runtime params from ^ setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} setArgs || exit # 8. specify additional `deepspeed` arguments setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset @@ -46,8 +46,13 @@ custom_args=" $@" # Assert `./hostfile_deepspeed` exists export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit +# source "${HERE}/venvs/polaris/2024-03-14/bin/activate" || exit +# echo "Using $(which python3)" +# --launcher_args='--pmi=pmix' + # deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ + # ${launch_cmd} \ run_cmd=" - deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ + deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ --use-flash-attn-v2 \ --$DTYPE \ --num-workers 0 \ @@ -69,7 +74,7 @@ run_cmd=" --hidden-size ${HIDDEN} \ --train-iters ${TRAIN_ITER} \ --eval-iters ${EVAL_ITERS} \ - --distributed-backend ${NCCL} \ + --distributed-backend ${BE} \ --num-attention-heads ${HEADS} \ --save-interval ${SAVE_INTERVAL} \ --eval-interval ${EVAL_INTERVAL} \ @@ -90,24 +95,6 @@ run_cmd=" |& tee ${OUTPUT_LOG} " - # --------------------------------------------------- - # --vocab-file $VOCAB_FILE \ - # --merge-file $MERGE_FILE \ - # --lr-decay-iters 320000 \ - # --lr-warmup-iters 5000 \ - # --lr-decay-iters 10000 \ - # --num-workers 4 \ - # launch python3 ${EXEC} \ - # --data-impl mmap \ - # source ./ezpz/src/ezpz/bin/getjobenv || exit - # --------------------------------------------------- - # ${DIST_LAUNCH} ./local_rank.sh python3 ${EXEC} \ - # ${DIST_LAUNCH} python3 ${EXEC} \ - # deepspeed $launcher ${EXEC} \ - # >> ${OUTPUT_LOG} 2>&1 & - # >> ${OUTPUT_LOG} 2>&1 & - # |& tee $OUTPUT_DIR/output.log - # ${EXTRA_ARGS} \ echo "All DeepSpeed(s): $(which -a deepspeed)" echo "Using $(which deepspeed)" From 0527c71d7eccf3b9c9dddafd0c4c0d48b6ae4eef Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 18 Mar 2024 07:12:24 -0500 Subject: [PATCH 130/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index c0c68b3537..bc2adb26fa 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -40,12 +40,15 @@ setParams() { export BE="${CCL}" # BE = CCL export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 + echo "!!!! Using CPU_OPTIMIZER on Intel XPU by Default !!!!" + export CPU_OPTIMIZER=${CPU_OPTIMIZER:-1} # CPU OPTIMIZER ON INTEL XPU # -------- [Polaris] ----------------------------------- elif [[ $(hostname) == x3* ]]; then TP=${TP:-2} # TP = 2 PP=${PP:-1} # PP = 1 export NCCL=${NCCL:-nccl} # NCCL export BE="${NCCL}" # BE = NCCL + # export DTYPE=${DTYPE:-bf16} # DTYPE: BF16 ?? export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 fi @@ -83,7 +86,8 @@ setParams() { export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" - if [[ "${CPU_OPTIMIZER:-0}" ]]; then + # if [[ "${CPU_OPTIMIZER:-0}" ]]; then + if [[ -n "${CPU_OPTIMIZER}" ]]; then echo "\n!!! Appending \`--cpu-optimizer\` to LLAMA_ARGS..." export LLAMA_ARGS="${LLAMA_ARGS} --cpu-optimizer" fi @@ -168,13 +172,11 @@ buildDSconfig() { export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" echo "DS_CONFIG: ${DS_CONFIG}" printf "ZS: %s, MB: %s, GB: %s, PP: %s, DTYPE: %s" ${ZERO_STAGE} ${MICRO_BATCH} ${GLOBAL_BATCH} ${PP} ${DTYPE} - # generateConfig "${DS_CONFIG}" - use_cpu_opt=$1 - if [[ $use_cpu_opt ]]; then + if [[ -z "${CPU_OPTIMIZER}" ]]; then + bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" #|| exit 1 + else echo "!!! Using CPU Optimizer !!!" bash "${PBS_O_WORKDIR}/generate_config_cpu_optimizer.sh" "${DS_CONFIG}" - else - bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" #|| exit 1 fi # ------------------------------------------------------------- } From cb54fed036ef153cbfbdc018be797f67f78df8a3 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 18 Mar 2024 07:12:44 -0500 Subject: [PATCH 131/268] Update `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index 915b5435c8..2e1a23010c 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -32,7 +32,7 @@ saveDSenv || exit # 2. save env vars to `.deepspeed_env` ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` -buildDSconfig "${CPU_OPTIMIZER:-0}" || exit # 6. create `deepspeed_config.json` from runtime params from ^ +buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} setArgs || exit # 8. specify additional `deepspeed` arguments setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset From b4b101d37f30c25d863d0562dcbd9748a055a1a4 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 18 Mar 2024 09:59:49 -0500 Subject: [PATCH 132/268] Update `train_llama_alcf_sunspot.sh` --- train_llama_alcf_sunspot.sh | 34 +++++++++++++++++----------------- 1 file changed, 17 insertions(+), 17 deletions(-) diff --git a/train_llama_alcf_sunspot.sh b/train_llama_alcf_sunspot.sh index d4cec63e33..d5e83c57a0 100644 --- a/train_llama_alcf_sunspot.sh +++ b/train_llama_alcf_sunspot.sh @@ -45,6 +45,10 @@ module () { # eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" # conda activate q4-drop +if [[ $(hostname) == x1* || $(hostname) == x4* ]] ; then + echo "!!!! Caught Intel XPU, using CPU_OPTIMIZER !!!!" + export CPU_OPTIMIZER=1; +fi # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ @@ -52,27 +56,24 @@ module () { cd "${PBS_O_WORKDIR}" || exit HERE=$(python3 -c 'import os; print(os.getcwd())') export HERE - -# PARENT="$(dirname "${HERE}")" -# source "${PARENT}/setenv.sh" || exit # ---- 1. Assert `./pretrain_gpt_alcf.py` exists: ----------------------------- export EXEC="${HERE}/pretrain_gpt_alcf.py" [ -f "${EXEC}" ] || exit # ---- 2. `source ./ALCF/helpers_alcf.sh`: ------------------------------------ sourceFile "${HERE}/ALCF/helpers.sh" || exit -# ---- 3. Call fns from `./ALCF/helpers_alcf.sh` ------------------------------ -setEnv || exit # 1. load `conda` environment -saveDSenv || exit # 2. save env vars to `.deepspeed_env` -ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars -makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` -setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` -buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ -setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} -setArgs || exit # 8. specify additional `deepspeed` arguments -setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset -setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` -printJobInfo || exit # 11. print job info -# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +# ---- 3. Call fns from `./ALCF/helpers_alcf.sh` ------------------------------------------------------------------ +setEnv || exit # 1. load `conda` environment +saveDSenv || exit # 2. save env vars to `.deepspeed_env` +ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars +makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` +buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ +setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} +setArgs || exit # 8. specify additional `deepspeed` arguments +setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset +setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` +printJobInfo || exit # 11. print job info +# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ # Take custom args custom_args=" $@" @@ -95,7 +96,6 @@ export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit run_cmd=" deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ --$DTYPE \ - --cpu-optimizer \ --num-workers 0 \ --split 100,0,0 \ --log-interval 1 \ From 315382519de59b243f9ece73e5cc2a94f9886453 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 18 Mar 2024 14:58:52 -0500 Subject: [PATCH 133/268] Update README.md --- ALCF/README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/ALCF/README.md b/ALCF/README.md index 49b583aa24..1a8612ed8a 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -98,6 +98,7 @@ ```bash $ conda activate "${DAY}" # e.g. 2024-03-07 $ conda install -c pytorch -c nvidia --solver libmamba mpi4py ninja transformers xformers triton pytorch torchvision torchaudio pytorch-cuda=11.8 + $ conda install --solver libmamba mpi4py -c conda-forge -c pytorch -c nvidia $ python3 -m pip install --upgrade pip pybind11 toolong appdirs wandb sentencepiece ipython setuptools wheel ninja $ python3 -m pip install --upgrade deepspeed wandb ``` From 2d46039a7d58188bb66816030c60f2f9ef389fc6 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 22 Mar 2024 10:47:41 -0500 Subject: [PATCH 134/268] Add `--train-iters-to-skip` option for skipping backprop on certain train iters --- megatron/arguments.py | 8 +++++--- megatron/core/pipeline_parallel/schedules.py | 11 +++++++++++ 2 files changed, 16 insertions(+), 3 deletions(-) diff --git a/megatron/arguments.py b/megatron/arguments.py index d83fe99856..3b83d16299 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -959,6 +959,11 @@ def _add_training_args(parser): group.add_argument('--use-dataset-only', type=bool, required=False, default=False, help='If set to True, only use the megatron dataset for external trainer ') group.add_argument('--profile', action='store_true', help='Enable Torch Profiler') + group.add_argument('--train-iters-to-skip', action="extend", nargs="+", type=str, + help=( + "Specific train iterations to skip when training. " + "Load the data and just perform a noop." + )) return parser @@ -1510,7 +1515,6 @@ def _add_activation_checkpoint_args(parser): def _add_distillation_args(parser): group = parser.add_argument_group('Knowledge distillation', 'Distillation Configurations') - group.add_argument('--num-layers-teacher', type=int, default=None, help='Number of the teacher transformer layers.') group.add_argument('--num-experts-teacher', type=int, nargs='+', default=[1,], @@ -1519,7 +1523,6 @@ def _add_distillation_args(parser): help='Tansformer teacher hidden size.') group.add_argument('--num-attention-heads-teacher', type=int, default=None, help='Number of teacher transformer attention heads.') - group.add_argument('--mos', action='store_true', help='Enable Mixture-of-Students via knolwedge distillation.') group.add_argument('--kd', action='store_true', @@ -1529,7 +1532,6 @@ def _add_distillation_args(parser): group.add_argument('--kd-temp', default=1.0, type=float) group.add_argument('--reset-iteration', action='store_true', help='Reset the iteration count.') - group.add_argument('--load-teacher', type=str, default=None, help='Directory containing a teacher model checkpoint.') diff --git a/megatron/core/pipeline_parallel/schedules.py b/megatron/core/pipeline_parallel/schedules.py index 407bb16d56..bb876481ac 100644 --- a/megatron/core/pipeline_parallel/schedules.py +++ b/megatron/core/pipeline_parallel/schedules.py @@ -241,6 +241,17 @@ def backward_step(input_tensor, output_tensor, output_tensor_grad, model_type, c # needs to be modified slightly to support arbitrary numbers of skip # connections. args = get_args() + assert args is not None + if config.timers is not None: + config.timers('backward-compute', log_level=2).start() + # if (to_skip := args.train_iters_to_skip) is not None and len(to_skip) > 0: + to_skip = getattr(args, 'train_iters_to_skip', None) + if to_skip is not None: + if config.timers is not None: + config.timers('backward-compute').stop() + if args.iteration in [int(i) for i in to_skip]: + print(f'Caught {args.iteration=} in `iters_to_skip`! Skipping!') + return [None] if args.deepspeed: assert model is not None From d96a58535327ac0ef3bdead29ffd833a0661a631 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 22 Mar 2024 12:23:08 -0500 Subject: [PATCH 135/268] [fix] `megatron/training.py` Fix bug when passing `--train-iters-to-skip` when running **without** setting `CPU_OPTIMIZER=1` --- megatron/training.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/megatron/training.py b/megatron/training.py index 7e6c7dc6bb..e987eb158d 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -728,8 +728,11 @@ def train_step(forward_step_func, data_iterator, increment = get_num_microbatches() * \ args.micro_batch_size * \ args.data_parallel_size - model[0].step(lr_kwargs={'increment': increment}) - update_successful = model[0].was_step_applied() + try: + model[0].step(lr_kwargs={'increment': increment}) + update_successful = model[0].was_step_applied() + except Exception: + update_successful = False else: update_successful, grad_norm, num_zeros_in_grad = optimizer.step(args, timers) timers('optimizer').stop() From 038109af825d62029f00c9717a2948b2adafa362 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 25 Mar 2024 20:33:52 -0500 Subject: [PATCH 136/268] Add `--optimizer adamw` for `torch.optim.AdamW` --- megatron/arguments.py | 4 +-- megatron/optimizer/__init__.py | 50 ++++++++++++++++++++++------------ 2 files changed, 34 insertions(+), 20 deletions(-) diff --git a/megatron/arguments.py b/megatron/arguments.py index 3b83d16299..cd618b285e 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -800,7 +800,7 @@ def _add_training_args(parser): ' ' ' ' 'For example:' - ' --rampup-batch-size 16 8 300000 \ ' + ' --rampup-batch-size 16 8 300000 \\ ' ' --global-batch-size 1024' 'will start with global batch size 16 and over ' ' (1024 - 16) / 8 = 126 intervals will increase' @@ -914,7 +914,7 @@ def _add_training_args(parser): help='Disable bias in the linear layers', dest='add_bias_linear') group.add_argument('--optimizer', type=str, default='adam', - choices=['adam', 'sgd'], + choices=['adam', 'adamw', 'sgd'], help='Optimizer function') group.add_argument('--dataloader-type', type=str, default=None, choices=['single', 'cyclic'], diff --git a/megatron/optimizer/__init__.py b/megatron/optimizer/__init__.py index 12a458375d..e7400c39b5 100644 --- a/megatron/optimizer/__init__.py +++ b/megatron/optimizer/__init__.py @@ -1,12 +1,13 @@ # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. from deepspeed.accelerator import get_accelerator -if get_accelerator().device_name() == 'cuda': - from apex.optimizers import FusedAdam as Adam - from apex.optimizers import FusedSGD as SGD -else: - from torch.optim import Adam - from torch.optim import SGD +# if get_accelerator().device_name() == 'cuda': +# from apex.optimizers import FusedAdam as Adam +# from apex.optimizers import FusedSGD as SGD +# else: +# from torch.optim import Adam +# from torch.optim import SGD +import torch from megatron import get_args @@ -93,24 +94,37 @@ def get_megatron_optimizer(model, betas=(args.adam_beta1, args.adam_beta2), eps=args.adam_eps) else: - if args.optimizer == 'adam': + if str(args.optimizer).lower() == 'adamw': + optimizer = torch.optim.AdamW( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps + ) + elif args.optimizer == 'adam': if args.ds_fused_adam: global Adam from deepspeed.ops.adam import FusedAdam Adam = FusedAdam - optimizer = Adam(param_groups, - lr=args.lr, - weight_decay=args.weight_decay, - betas=(args.adam_beta1, args.adam_beta2), - eps=args.adam_eps) + else: + Adam = torch.optim.Adam + optimizer = Adam( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps + ) elif args.optimizer == 'sgd': - optimizer = SGD(param_groups, - lr=args.lr, - weight_decay=args.weight_decay, - momentum=args.sgd_momentum) + optimizer = torch.optim.SGD( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + momentum=args.sgd_momentum + ) else: - raise Exception('{} optimizer is not supported.'.format( - args.optimizer)) + raise Exception(f'{args.optimizer} optimizer is not supported.') if args.deepspeed: return optimizer From 66401b8e197dbcc649f779119e5cb8f2303ea929 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 26 Mar 2024 08:42:02 -0500 Subject: [PATCH 137/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 4fefef795f..e296a637be 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -153,12 +153,14 @@ def model_provider(pre_process=True, post_process=True): see_memory_usage("After Building Model", force=True) if wandb.run is not None: wandb.run.config.update({'num_params': num_params}) - # wandb.run.watch( - # model, - # log='all', - # log_graph=True, - # ) - # wandb.run.config.update({'num_params': num_params}) + try: + wandb.run.watch( + model, + log='all', + log_graph=True, + ) + except Exception: + pass return model From c87ea6aafe82924e4b9b44c066ebcd238572d722 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 26 Mar 2024 09:22:50 -0500 Subject: [PATCH 138/268] Remove redundant `generate_config_cpu_optimizer.sh` --- generate_config_cpu_optimizer.sh | 151 ------------------------------- 1 file changed, 151 deletions(-) delete mode 100644 generate_config_cpu_optimizer.sh diff --git a/generate_config_cpu_optimizer.sh b/generate_config_cpu_optimizer.sh deleted file mode 100644 index 99dec97958..0000000000 --- a/generate_config_cpu_optimizer.sh +++ /dev/null @@ -1,151 +0,0 @@ -#!/bin/bash --login - -for v in "$GLOBAL_BATCH" "$MICRO_BATCH" "$GRAD_ACC_STEPS" "$ZERO_STAGE" \ - "$PP" "$DTYPE" -do - if [ -z $v ]; then - echo "Please export required envs before execute $0" - exit 1 - fi -done - -if [ $# -ne 1 ]; then - echo "Usage: $0 config_file" - exit 1 -fi - -extra="" -common="\ - \"train_batch_size\": $GLOBAL_BATCH, - \"train_micro_batch_size_per_gpu\": $MICRO_BATCH, - \"steps_per_print\": 1, - \"gradient_accumulation_steps\": $GRAD_ACC_STEPS, - \"optimizer\": { - \"type\": \"AdamW\", - \"params\": { - \"lr\": ${LR}, - \"beta1\": 0.9, - \"beta2\": 0.95, - \"eps\": 1e-5, - \"weight_decay\": 1e-1 - } - }, - \"scheduler\": { - \"type\": \"WarmupLR\", - \"params\": { - \"warmup_min_lr\": 0.00003, - \"warmup_max_lr\": 0.0003, - \"warmup_num_steps\": 5000 - } - }, - \"zero_allow_untested_optimizer\": true, - \"gradient_clipping\": 1.0, - \"activation_checkpointing\": { - \"partition_activations\": true, - \"contiguous_memory_optimization\": false - }, - \"wall_clock_breakdown\": false," - -flops_profiler="\ - \"flops_profiler\": { - \"enabled\": false, - \"profile_step\": 45, - \"module_depth\": -1, - \"top_modules\": 1, - \"detailed\": true, - \"output_file\": null - }" - -if [[ $DTYPE == "bf16" ]]; then -dtype="\ - \"communication_data_type\": \"bfp16\", - \"fp16\": { - \"enabled\": false, - \"loss_scale\": 0, - \"loss_scale_window\": 1000, - \"hysteresis\": 2, - \"min_loss_scale\": 1 - }, - \"bfloat16\": { - \"enabled\": true, - \"loss_scale\": 1.0 - }," -else -dtype="\ - \"communication_data_type\": \"fp16\", - \"fp16\": { - \"enabled\": true, - \"loss_scale\": 0, - \"loss_scale_window\": 1000, - \"hysteresis\": 2, - \"min_loss_scale\": 1 - }, - \"bfloat16\": { - \"enabled\": false, - \"loss_scale\": 1.0 - }," -fi - -if [ $ZERO_STAGE == 3 ]; then -zero="\ - \"zero_optimization\": { - \"stage\": 3, - \"reduce_scatter\": false, - \"stage3_max_live_parameters\": 3e9, - \"stage3_max_reuse_distance\": 3e9, - \"stage3_param_persistence_threshold\": 1e5, - \"stage3_prefetch_bucket_size\": 5e7, - \"contiguous_gradients\": true, - \"overlap_comm\": true, - \"reduce_bucket_size\": 90000000, - \"sub_group_size\": 1e9, - \"offload_optimizer\": { - \"device\": \"none\", - \"buffer_count\": 4, - \"pipeline_read\": false, - \"pipeline_write\": false, - \"pin_memory\": true - } - }," -elif [ $ZERO_STAGE == 2 ] || [ $ZERO_STAGE == 1 ]; then -zero="\ - \"zero_optimization\": { - \"stage\": $ZERO_STAGE, - \"offload_optimizer\": { - \"device\": \"cpu\", - \"buffer_count\": 4, - \"pipeline_read\": false, - \"pipeline_write\": false, - \"pin_memory\": true - } - }," - if [ $ZERO_STAGE == 1 ]; then - if [ $PP > 1 ]; then - extra="\ - \"data_types\": { - \"grad_accum_dtype\": \"fp32\" - }, - \"comms_logger\": { - \"enabled\": true, - \"verbose\": false, - \"prof_all\": true, - \"debug\": false - }," - else - echo 'please add the config for zero_stage 1 without pipeline-parallelism' - fi - fi -else - echo 'Please add the correct config set!!!' -fi - -# flops_profiler must at the end because no ',' is allowed at the end -cat < $1 -{ -$common -$zero -$dtype -$extra -$flops_profiler -} -EOT From 37f6d3a757e7393751cdbaa48bea6e4754024a9e Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 26 Mar 2024 09:23:08 -0500 Subject: [PATCH 139/268] Update `train_llama_alcf_sunspot.sh` --- train_llama_alcf_sunspot.sh | 35 +++++++++-------------------------- 1 file changed, 9 insertions(+), 26 deletions(-) diff --git a/train_llama_alcf_sunspot.sh b/train_llama_alcf_sunspot.sh index d5e83c57a0..f000506bb9 100644 --- a/train_llama_alcf_sunspot.sh +++ b/train_llama_alcf_sunspot.sh @@ -41,15 +41,6 @@ module () { return $__lmod_my_status } -# -# eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" -# conda activate q4-drop - -if [[ $(hostname) == x1* || $(hostname) == x4* ]] ; then - echo "!!!! Caught Intel XPU, using CPU_OPTIMIZER !!!!" - export CPU_OPTIMIZER=1; -fi - # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ # ---- 0. Navigate into `$PBS_O_WORKDIR` ------------------------------------- @@ -67,7 +58,7 @@ saveDSenv || exit # 2. save env vars to `.deepspeed_ ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` -buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ +buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} setArgs || exit # 8. specify additional `deepspeed` arguments setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset @@ -81,21 +72,15 @@ custom_args=" $@" # Assert `./hostfile_deepspeed` exists export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit -# hf="${HOSTFILE:-${PBS_NODEFILE}}" -# nh=$(wc -l "${hf}") -# if [[ "${nh}" -gt 1 ]]; then -# launch_cmd="deepspeed --hostfile $hfds --launcher MPICH ${EXEC}" -# else -# launch_cmd="python3 ${EXEC}" -# fi -# -# echo "launch_cmd: ${launch_cmd}" - # --use-flash-attn-v2 \ - # python3 ${EXEC} \ + # --use-flash-attn \ + # --$DTYPE \ + # --optimizer adamw \ + # --adam-beta1 0.9 \ + # --adam-beta2 0.95 \ run_cmd=" deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ - --$DTYPE \ + --optimizer ${OPT} \ --num-workers 0 \ --split 100,0,0 \ --log-interval 1 \ @@ -108,9 +93,9 @@ run_cmd=" --accumulate-allreduce-grads-in-fp32 \ --use-checkpoint-opt_param-scheduler \ --lr ${LR} \ - --seq-length $SEQ \ --save ${CKPT_DIR} \ --load ${CKPT_DIR} \ + --seq-length ${SEQ} \ --num-layers ${NLAYERS} \ --hidden-size ${HIDDEN} \ --train-iters ${TRAIN_ITER} \ @@ -155,12 +140,10 @@ run_cmd=" # |& tee $OUTPUT_DIR/output.log # ${EXTRA_ARGS} \ -echo "All DeepSpeed(s): $(which -a deepspeed)" -echo "Using $(which deepspeed)" +echo "! Using $(which deepspeed)" ds_report echo "${run_cmd}" - printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" # echo "${OUTPUT_LOG}" From 7befd20801d4f62e9e217636a9e1ed3e73c13f71 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 26 Mar 2024 09:24:03 -0500 Subject: [PATCH 140/268] Update `megatron/core/pipeline_parallel/schedules.py` --- megatron/core/pipeline_parallel/schedules.py | 32 +++++++++----------- 1 file changed, 14 insertions(+), 18 deletions(-) diff --git a/megatron/core/pipeline_parallel/schedules.py b/megatron/core/pipeline_parallel/schedules.py index bb876481ac..453019f8c9 100644 --- a/megatron/core/pipeline_parallel/schedules.py +++ b/megatron/core/pipeline_parallel/schedules.py @@ -14,7 +14,7 @@ from megatron.core.enums import ModelType from megatron.core.utils import get_attr_wrapped_model, get_model_type, get_model_config -from megatron.utils import unwrap_model +from megatron.utils import print_rank_0, unwrap_model from megatron.model import DistributedDataParallel as LocalDDP from megatron.model import Float16Module @@ -228,7 +228,14 @@ def forward_step(forward_step_func, return [output_tensor] -def backward_step(input_tensor, output_tensor, output_tensor_grad, model_type, config, model=None): +def backward_step( + input_tensor, + output_tensor, + output_tensor_grad, + model_type, + config, + model=None +): """Backward step through passed-in output tensor. If last stage, output_tensor_grad is None, otherwise gradient of loss @@ -244,20 +251,16 @@ def backward_step(input_tensor, output_tensor, output_tensor_grad, model_type, c assert args is not None if config.timers is not None: config.timers('backward-compute', log_level=2).start() - # if (to_skip := args.train_iters_to_skip) is not None and len(to_skip) > 0: - to_skip = getattr(args, 'train_iters_to_skip', None) - if to_skip is not None: + if (to_skip := getattr(args, 'train_iters_to_skip', None)) is not None: if config.timers is not None: config.timers('backward-compute').stop() - if args.iteration in [int(i) for i in to_skip]: - print(f'Caught {args.iteration=} in `iters_to_skip`! Skipping!') + if len(to_skip) > 0 and args.iteration in [int(i) for i in to_skip]: + print_rank_0( + f'Caught {args.iteration=} in `iters_to_skip`! Skipping!' + ) return [None] if args.deepspeed: assert model is not None - - if config.timers is not None: - config.timers('backward-compute', log_level=2).start() - # Retain the grad on the input_tensor. unwrap_input_tensor_grad = False if not isinstance(input_tensor, list): @@ -266,24 +269,20 @@ def backward_step(input_tensor, output_tensor, output_tensor_grad, model_type, c for x in input_tensor: if x is not None: x.retain_grad() - if not isinstance(output_tensor, list): output_tensor = [output_tensor] if not isinstance(output_tensor_grad, list): output_tensor_grad = [output_tensor_grad] - # Backward pass. if args.deepspeed: model.backward(output_tensor[0]) else: if output_tensor_grad[0] is None and config.grad_scale_func is not None: output_tensor[0] = config.grad_scale_func(output_tensor[0]) - if config.deallocate_pipeline_outputs: custom_backward(output_tensor[0], output_tensor_grad[0]) else: torch.autograd.backward(output_tensor[0], grad_tensors=output_tensor_grad[0]) - # Collect the grad of the input_tensor. input_tensor_grad = [None] if input_tensor is not None: @@ -293,7 +292,6 @@ def backward_step(input_tensor, output_tensor, output_tensor_grad, model_type, c input_tensor_grad.append(None) else: input_tensor_grad.append(x.grad) - # Handle single skip connection if it exists (encoder_hidden_state in # model with encoder and decoder). if parallel_state.get_pipeline_model_parallel_world_size() > 1 and \ @@ -303,10 +301,8 @@ def backward_step(input_tensor, output_tensor, output_tensor_grad, model_type, c input_tensor_grad[-1].add_(output_tensor_grad[1]) if unwrap_input_tensor_grad: input_tensor_grad = input_tensor_grad[0] - if config.timers is not None: config.timers('backward-compute').stop() - return input_tensor_grad From 25353fda499d23bd3d6b42986cbf0f5353537eab Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 26 Mar 2024 09:24:30 -0500 Subject: [PATCH 141/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 31 +++++++++++++++++++++---------- 1 file changed, 21 insertions(+), 10 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index bc2adb26fa..30d9add286 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -40,8 +40,11 @@ setParams() { export BE="${CCL}" # BE = CCL export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 - echo "!!!! Using CPU_OPTIMIZER on Intel XPU by Default !!!!" - export CPU_OPTIMIZER=${CPU_OPTIMIZER:-1} # CPU OPTIMIZER ON INTEL XPU + # if [[ -z "${CPU_OPTIMIZER}" ]]; then + # CPU_OPTIMIZER=1 + # fi + # echo "!!!! Using CPU_OPTIMIZER on Intel XPU by Default !!!!" + # export CPU_OPTIMIZER=${CPU_OPTIMIZER:-1} # CPU OPTIMIZER ON INTEL XPU # -------- [Polaris] ----------------------------------- elif [[ $(hostname) == x3* ]]; then TP=${TP:-2} # TP = 2 @@ -53,8 +56,10 @@ setParams() { MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 fi # ------------------------------------------------------------------------ + # export OFFLOAD_DEVICE="${OFFLOAD_DEVICE:-none}" export PP="${PP}" export TP="${TP}" + export OPT="${OPT:-adamw}" export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} # ---- Llama2 7B Config ------------------------------ @@ -87,9 +92,13 @@ setParams() { export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" # if [[ "${CPU_OPTIMIZER:-0}" ]]; then - if [[ -n "${CPU_OPTIMIZER}" ]]; then + # if [[ -n "${CPU_OPTIMIZER}" ]]; then + if [[ "${CPU_OPTIMIZER}" == 1 ]]; then + export OFFLOAD_DEVICE="cpu" echo "\n!!! Appending \`--cpu-optimizer\` to LLAMA_ARGS..." export LLAMA_ARGS="${LLAMA_ARGS} --cpu-optimizer" + else + export OFFLOAD_DEVICE="none" fi # ---------------------------------------------------- } @@ -171,13 +180,15 @@ buildDSconfig() { # ---- Build DeepSpeed Config --------------------------------- export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" echo "DS_CONFIG: ${DS_CONFIG}" - printf "ZS: %s, MB: %s, GB: %s, PP: %s, DTYPE: %s" ${ZERO_STAGE} ${MICRO_BATCH} ${GLOBAL_BATCH} ${PP} ${DTYPE} - if [[ -z "${CPU_OPTIMIZER}" ]]; then - bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" #|| exit 1 - else - echo "!!! Using CPU Optimizer !!!" - bash "${PBS_O_WORKDIR}/generate_config_cpu_optimizer.sh" "${DS_CONFIG}" - fi + printf "ZS: %s, CPU_OPTIMIZER: %s, MB: %s, GB: %s, PP: %s, DTYPE: %s" "${ZERO_STAGE}" "${CPU_OPTIMIZER}" "${MICRO_BATCH}" "${GLOBAL_BATCH}" "${PP}" "${DTYPE}" + bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" + # if [[ -z "${CPU_OPTIMIZER}" ]]; then + # echo "!!! Using GPU Optimizer !!!" + # bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" #|| exit 1 + # else + # echo "!!! Using CPU Optimizer !!!" + # bash "${PBS_O_WORKDIR}/generate_config_cpu_optimizer.sh" "${DS_CONFIG}" + # fi # ------------------------------------------------------------- } From 29f1e307095188a750da7ba3f97d1697055f2809 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 26 Mar 2024 09:24:46 -0500 Subject: [PATCH 142/268] Update `generate_config.sh` --- generate_config.sh | 75 +++++++++++++++++++++++++++++----------------- 1 file changed, 47 insertions(+), 28 deletions(-) diff --git a/generate_config.sh b/generate_config.sh index 6bea420a2a..64f0161087 100644 --- a/generate_config.sh +++ b/generate_config.sh @@ -14,22 +14,23 @@ if [ $# -ne 1 ]; then exit 1 fi +# \"optimizer\": { +# \"type\": \"AdamW\", +# \"params\": { +# \"lr\": ${LR}, +# \"beta1\": 0.9, +# \"beta2\": 0.95, +# \"eps\": 1e-5, +# \"weight_decay\": 1e-1 +# } +# }, + extra="" common="\ \"train_batch_size\": $GLOBAL_BATCH, \"train_micro_batch_size_per_gpu\": $MICRO_BATCH, \"steps_per_print\": 1, \"gradient_accumulation_steps\": $GRAD_ACC_STEPS, - \"optimizer\": { - \"type\": \"AdamW\", - \"params\": { - \"lr\": ${LR}, - \"beta1\": 0.9, - \"beta2\": 0.95, - \"eps\": 1e-5, - \"weight_decay\": 1e-1 - } - }, \"scheduler\": { \"type\": \"WarmupLR\", \"params\": { @@ -70,7 +71,7 @@ dtype="\ \"enabled\": true, \"loss_scale\": 1.0 }," -else +elif [[ $DTYPE == "fp16" ]]; then dtype="\ \"communication_data_type\": \"fp16\", \"fp16\": { @@ -84,6 +85,8 @@ dtype="\ \"enabled\": false, \"loss_scale\": 1.0 }," +else + dtype="\"communication_data_type\": \"fp32\"," fi if [ $ZERO_STAGE == 3 ]; then @@ -107,27 +110,43 @@ zero="\ \"pin_memory\": true } }," -elif [ $ZERO_STAGE == 2 ] || [ $ZERO_STAGE == 1 ]; then + +# elif [[ $ZERO_STAGE == 2 ]]; then +elif [ "${ZERO_STAGE}" == 2 ] || [ "${ZERO_STAGE}" == 1 ]; then + +if [[ -n "${CPU_OPTIMIZER}" ]]; then +echo "!!!! CAUGHT CPU_OPTIMIZER !!!!" + +zero="\ + \"zero_optimization\": { + \"stage\": $ZERO_STAGE, + \"offload_optimizer\": { + \"device\": \"cpu\" + } + }," + +else zero="\ \"zero_optimization\": { \"stage\": $ZERO_STAGE }," - if [ $ZERO_STAGE == 1 ]; then - if [ $PP > 1 ]; then - extra="\ - \"data_types\": { - \"grad_accum_dtype\": \"fp32\" - }, - \"comms_logger\": { - \"enabled\": true, - \"verbose\": false, - \"prof_all\": true, - \"debug\": false - }," - else - echo 'please add the config for zero_stage 1 without pipeline-parallelism' - fi - fi +fi + +# elif [[ $ZERO_STAGE == 1 ]]; then +if [[ $PP > 1 ]]; then + extra="\ + \"data_types\": { + \"grad_accum_dtype\": \"fp32\" + }, + \"comms_logger\": { + \"enabled\": true, + \"verbose\": false, + \"prof_all\": true, + \"debug\": false + }," +else + echo 'please add the config for zero_stage 1 without pipeline-parallelism' +fi else echo 'Please add the correct config set!!!' fi From 336332508baeb4e51dc7dfcd480749a13f01b38f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 26 Mar 2024 09:25:37 -0500 Subject: [PATCH 143/268] `assert args is not None` in `megatron/training.py` --- megatron/training.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/megatron/training.py b/megatron/training.py index e987eb158d..f511efc4ff 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -143,6 +143,8 @@ def pretrain(train_valid_test_dataset_provider, args = get_args() timers = get_timers() + assert args is not None + assert timers is not None if args.deepspeed: args.deepspeed_config_dict = _create_ds_config_dict() @@ -319,6 +321,7 @@ def setup_teacher_model(args, model_provider): def get_model(model_provider_func, model_type=ModelType.encoder_or_decoder, wrap_with_ddp=True): """Build the model.""" args = get_args() + assert args is not None args.model_type = model_type # Build model. From 0dcba4ff4c8262a0fe30412509a22792896d552f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 26 Mar 2024 11:08:51 -0500 Subject: [PATCH 144/268] Remove `"scheduler": {...}` from `generate_config.sh` --- generate_config.sh | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/generate_config.sh b/generate_config.sh index 64f0161087..e140b7a274 100644 --- a/generate_config.sh +++ b/generate_config.sh @@ -24,6 +24,14 @@ fi # \"weight_decay\": 1e-1 # } # }, +# \"scheduler\": { +# \"type\": \"WarmupLR\", +# \"params\": { +# \"warmup_min_lr\": 0.00003, +# \"warmup_max_lr\": 0.0003, +# \"warmup_num_steps\": 5000 +# } +# }, extra="" common="\ @@ -31,14 +39,6 @@ common="\ \"train_micro_batch_size_per_gpu\": $MICRO_BATCH, \"steps_per_print\": 1, \"gradient_accumulation_steps\": $GRAD_ACC_STEPS, - \"scheduler\": { - \"type\": \"WarmupLR\", - \"params\": { - \"warmup_min_lr\": 0.00003, - \"warmup_max_lr\": 0.0003, - \"warmup_num_steps\": 5000 - } - }, \"zero_allow_untested_optimizer\": true, \"gradient_clipping\": 1.0, \"activation_checkpointing\": { From 367e4ae534090dd6f016c123bab9f04db1b32b67 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 27 Mar 2024 09:33:57 -0500 Subject: [PATCH 145/268] Track optimizer states --- train_llama_alcf_polaris.sh | 2 ++ 1 file changed, 2 insertions(+) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index 2e1a23010c..7cc1454f60 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -51,6 +51,7 @@ export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit # --launcher_args='--pmi=pmix' # deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ # ${launch_cmd} \ + # --optimizer adam \ run_cmd=" deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ --use-flash-attn-v2 \ @@ -66,6 +67,7 @@ run_cmd=" --no-gradient-accumulation-fusion \ --accumulate-allreduce-grads-in-fp32 \ --use-checkpoint-opt_param-scheduler \ + --log-optimizer-states-to-tensorboard \ --lr ${LR} \ --seq-length $SEQ \ --save ${CKPT_DIR} \ From 31644f068b962cf03479d1c8840254921ef240f1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 27 Mar 2024 09:34:20 -0500 Subject: [PATCH 146/268] Track optimizer states with W&B in `megatron/training.py` --- megatron/training.py | 147 +++++++++++++++++++++++++++---------------- 1 file changed, 93 insertions(+), 54 deletions(-) diff --git a/megatron/training.py b/megatron/training.py index f511efc4ff..bf87e7b52c 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -755,7 +755,6 @@ def train_step(forward_step_func, data_iterator, skipped_iter = 0 grad_norm = None num_zeros_in_grad = None - loss_reduced = {} for key in losses_reduced[0]: losses_reduced_for_key = [x[key] for x in losses_reduced] @@ -793,7 +792,7 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, args = get_args() timers = get_timers() writer = get_tensorboard_writer() - + wandb_metrics = {} # Advanced, skipped, and Nan iterations. advanced_iters_key = 'advanced iterations' skipped_iters_key = 'skipped iterations' @@ -852,11 +851,15 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, 'optimizer'] # Calculate batch size. - batch_size = args.micro_batch_size * args.data_parallel_size * \ - get_num_microbatches() - - total_iterations = total_loss_dict[advanced_iters_key] + \ - total_loss_dict[skipped_iters_key] + batch_size = ( + args.micro_batch_size + * args.data_parallel_size + * get_num_microbatches() + ) + total_iterations = ( + total_loss_dict[advanced_iters_key] + + total_loss_dict[skipped_iters_key] + ) # Tensorboard values. # Timer requires all the ranks to call. @@ -870,6 +873,10 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, writer.add_scalar('steps-vs-tokens/y=steps,x=tokens', iteration, args.consumed_train_tokens) writer.add_scalar('steps-vs-tokens/y=tokens,x=steps', args.consumed_train_tokens, iteration) if args.log_learning_rate_to_tensorboard: + wandb_metrics |= { + 'learning-rate/iteration': iteration, + 'learning-rate/learning-rate': learning_rate, + } writer.add_scalar('learning-rate/learning-rate', learning_rate, iteration) writer.add_scalar('learning-rate/learning-rate vs samples', learning_rate, args.consumed_train_samples) @@ -881,7 +888,12 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, args.consumed_train_samples) writer.add_scalar('batch-size/batch-size vs tokens', batch_size, args.consumed_train_tokens) + wandb_metrics |= { + 'lm-loss-training/iteration': iteration, + 'lm-loss-training/consumed_train_tokens': args.consumed_train_tokens, + } for key in loss_dict: + wandb_metrics |= {f'lm-loss-training/{key}': loss_dict[key]} writer.add_scalar(f"lm-loss-training/{key}", loss_dict[key], iteration) writer.add_scalar(f"lm-loss-training/{key}" + ' vs samples', loss_dict[key], args.consumed_train_samples) @@ -900,18 +912,21 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, writer.add_scalar('world-size/world-size vs tokens', args.world_size, args.consumed_train_tokens) if grad_norm is not None: + wandb_metrics |= {'training/grad-norm': grad_norm} writer.add_scalar('grad-norm/grad-norm', grad_norm, iteration) writer.add_scalar('grad-norm/grad-norm vs samples', grad_norm, args.consumed_train_samples) writer.add_scalar('grad-norm/grad-norm vs tokens', grad_norm, args.consumed_train_tokens) if num_zeros_in_grad is not None: + wandb_metrics |= {'training/num-zeros': num_zeros_in_grad} writer.add_scalar('num-zeros/num-zeros', num_zeros_in_grad, iteration) writer.add_scalar('num-zeros/num-zeros vs samples', num_zeros_in_grad, args.consumed_train_samples) writer.add_scalar('num-zeros/num-zeros vs tokens', num_zeros_in_grad, args.consumed_train_tokens) if params_norm is not None: + wandb_metrics |= {'training/params-norm': params_norm} writer.add_scalar('params-norm/params-norm', params_norm, iteration) writer.add_scalar('params-norm/params-norm vs samples', params_norm, args.consumed_train_samples) @@ -955,7 +970,6 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, mem_stats["allocation.all.current"], iteration, ) - if iteration % args.tensorboard_log_interval == 0: # This logging write various optimizer states to tensorboard. This # feature may consume extra GPU memory thus is set at false by default. @@ -979,26 +993,49 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, # print('step {} rank {} before sync opt_stats {}, {}'.format(iteration, torch.distributed.get_rank(), opt_stats_2, opt_stats)) if args.zero_stage > 0: # ZeRO partiions optimizer states + # opt_stats = opt_stats.clone().detach() + # opt_stats = get_accelerator().FloatTensor opt_stats = get_accelerator().FloatTensor(opt_stats) torch.distributed.all_reduce(opt_stats, group=mpu.get_sequence_data_parallel_group()) + # opt_stats_2 = get_accelerator().FloatTensor(opt_stats_2) + # opt_stats_2 = opt_stats_2.clone().detach() opt_stats_2 = get_accelerator().FloatTensor(opt_stats_2) torch.distributed.all_reduce(opt_stats_2, op=torch.distributed.ReduceOp.MAX, group=mpu.get_sequence_data_parallel_group()) if args.tensor_model_parallel_size > 1: + # opt_stats = opt_stats.clone().detach() opt_stats = get_accelerator().FloatTensor(opt_stats) torch.distributed.all_reduce(opt_stats, group=mpu.get_tensor_model_parallel_group()) + # opt_stats_2 = opt_stats_2.clone().detach() opt_stats_2 = get_accelerator().FloatTensor(opt_stats_2) torch.distributed.all_reduce(opt_stats_2, op=torch.distributed.ReduceOp.MAX, group=mpu.get_tensor_model_parallel_group()) if args.pipeline_model_parallel_size > 1: + # opt_stats = opt_stats.clone().detach() opt_stats = get_accelerator().FloatTensor(opt_stats) torch.distributed.all_reduce(opt_stats, group=mpu.get_pipeline_model_parallel_group()) + # opt_stats_2 = opt_stats_2.clone().detach() opt_stats_2 = get_accelerator().FloatTensor(opt_stats_2) torch.distributed.all_reduce(opt_stats_2, op=torch.distributed.ReduceOp.MAX, group=mpu.get_pipeline_model_parallel_group()) - + wandb_metrics |= { + 'optimizer/iteration': args.iteration, + 'optimizer/consumed_train_tokens': args.consumed_train_tokens, + 'optimizer/variance_l2': opt_stats[0]**0.5, + 'optimizer/variance_sqrt_l2': opt_stats[1]**0.5, + 'optimizer/momentum_l2': opt_stats[2]**0.5, + 'optimizer/weight_l2': opt_stats[3]**0.5, + 'optimizer/variance_l1': opt_stats[4], + 'optimizer/variance_sqrt_l1': opt_stats[5], + 'optimizer/momentum_l1': opt_stats[6], + 'optimizer/weight_l1': opt_stats[7], + 'optimizer/variance_abs_max': opt_stats_2[0], + 'optimizer/variance_sqrt_abs_max': opt_stats_2[1], + 'optimizer/momentum_abs_max': opt_stats_2[2], + 'optimizer/weight_abs_max': opt_stats_2[3], + } # print('step {} rank {} after sync opt_stats {}, {}'.format(iteration, torch.distributed.get_rank(), opt_stats_2, opt_stats)) if writer and is_last_rank(): writer.add_scalar('optimizer/variance_l2 vs tokens', opt_stats[0]**0.5, args.consumed_train_tokens) @@ -1045,27 +1082,24 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, tokens_per_sec_per_replica = tokens_per_sec / args.data_parallel_size tokens_per_gpu_per_second = tokens_per_sec / args.world_size tokens_per_gpu_per_second_per_replica = tokens_per_gpu_per_second / args.data_parallel_size - wandb_metrics = {} - if wandb is not None and getattr(wandb, 'run', None) is not None: - assert wandb.run is not None - wandb_metrics = { - 'throughput/iteration-time': elapsed_time_per_iteration, # 1000 ms / s - 'throughput/samples_per_sec': samples_per_sec, - 'throughput/samples_per_sec_per_replica': samples_per_sec_per_replica, - 'throughput/tokens_per_sec': tokens_per_sec, - 'throughput/tokens_per_sec_per_replica': tokens_per_sec_per_replica, - 'throughput/tokens_per_gpu_per_sec': tokens_per_gpu_per_second, - 'throughput/tokens_per_gpu_per_sec_per_replica': tokens_per_gpu_per_second_per_replica, - 'throughput/tflops': tflops, - 'throughput/approx_params_in_billions': approx_parameters_in_billions, - 'throughput/elapsed_ms_per_iteration': elapsed_time_per_iteration, - 'throughput/iteration': iteration, + wandb_metrics |= { + 'throughput/iteration-time': elapsed_time_per_iteration, # 1000 ms / s + 'throughput/samples_per_sec': samples_per_sec, + 'throughput/samples_per_sec_per_replica': samples_per_sec_per_replica, + 'throughput/tokens_per_sec': tokens_per_sec, + 'throughput/tokens_per_sec_per_replica': tokens_per_sec_per_replica, + 'throughput/tokens_per_gpu_per_sec': tokens_per_gpu_per_second, + 'throughput/tokens_per_gpu_per_sec_per_replica': tokens_per_gpu_per_second_per_replica, + 'throughput/tflops': tflops, + 'throughput/approx_params_in_billions': approx_parameters_in_billions, + 'throughput/elapsed_ms_per_iteration': elapsed_time_per_iteration, + 'throughput/iteration': iteration, + } + if loss_dict is not None: + wandb_metrics |= { + 'loss/iteration': iteration, + **{f'loss/{k}': v for k, v in loss_dict.items()} } - if loss_dict is not None: - wandb_metrics |= { - 'loss/iteration': iteration, - **{f'loss/{k}': v for k, v in loss_dict.items()} - } if writer and args.log_timers_to_tensorboard: writer.add_scalar('iteration-time/iteration-time', elapsed_time_per_iteration, iteration) @@ -1073,31 +1107,36 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, elapsed_time_per_iteration, args.consumed_train_samples) writer.add_scalar('iteration-time/iteration-time vs tokens', elapsed_time_per_iteration, args.consumed_train_tokens) - log_string = ' iteration {:8d}/{:8d} |'.format( - iteration, args.train_iters) - log_string += ' consumed samples: {:12d} |'.format( - args.consumed_train_samples) - log_string += ' consumed tokens: {:12d} |'.format( - args.consumed_train_tokens) - log_string += ' elapsed time per iteration (ms): {:.1f} |'.format( - elapsed_time_per_iteration * 1000.0) - log_string += ' learning rate: {:.3E} |'.format(learning_rate) - log_string += ' global batch size: {:5d} |'.format(batch_size) - if wandb is not None and getattr(wandb, 'run', None) is not None: - wandb_metrics |= { - 'training/iteration': iteration, - 'training/iteration_time': elapsed_time_per_iteration, - 'training/iteration_time_vs_tokens': ( - (elapsed_time_per_iteration - / args.consumed_train_tokens) - ), - 'training/iteration_time_vs_samples': ( - (elapsed_time_per_iteration - / args.consumed_train_samples), - ), - 'training/consumed_samples': args.consumed_train_samples, - 'training/consumed_tokens': args.consumed_train_tokens, - } + log_string = f' iteration {iteration:8d}/{args.train_iters:8d} |' + # .format( iteration, args.train_iters) + log_string += ( + f' consumed samples: {args.consumed_train_samples:12d} |' + # .format(args.consumed_train_samples) + ) + log_string += f' consumed tokens: {args.consumed_train_tokens:12d} |' + # .format( args.consumed_train_tokens) + log_string += ( + ' elapsed time per iteration (ms): ' + f'{elapsed_time_per_iteration * 1000.0:.1f} |' + # .format( elapsed_time_per_iteration * 1000.0) + ) + log_string += f' learning rate: {learning_rate:.3E} |' + log_string += f' global batch size: {batch_size:5d} |' + # if wandb is not None and getattr(wandb, 'run', None) is not None: + wandb_metrics |= { + 'training/iteration': iteration, + 'training/iteration_time': elapsed_time_per_iteration, + 'training/iteration_time_vs_tokens': ( + (elapsed_time_per_iteration + / args.consumed_train_tokens) + ), + 'training/iteration_time_vs_samples': ( + (elapsed_time_per_iteration + / args.consumed_train_samples), + ), + 'training/consumed_samples': args.consumed_train_samples, + 'training/consumed_tokens': args.consumed_train_tokens, + } for key in total_loss_dict: if key not in [advanced_iters_key, skipped_iters_key, nan_iters_key]: From 5273630333e0b4024f50b01f5741dae869182773 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 27 Mar 2024 13:18:34 -0500 Subject: [PATCH 147/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 37 ++++++++++++++++++++++++++++++------- 1 file changed, 30 insertions(+), 7 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index e296a637be..af88c83a0f 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -25,6 +25,7 @@ checkpoint_throughput_calculator ) from pathlib import Path +from enrich import get_logger import deepspeed from deepspeed.runtime.utils import see_memory_usage @@ -43,6 +44,7 @@ # backend='deepspeed', # port='5432', # ) +log = get_logger(__name__) RANK = get_rank() WORLD_SIZE = get_world_size() LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" @@ -51,6 +53,10 @@ DISABLE_WANDB = ( WANDB_MODE is not None and str(WANDB_MODE).lower() == 'disabled' ) +if RANK == 0: + log.setLevel("INFO") +else: + log.setLevel("CRITICAL") if RANK == 0 and not DISABLE_WANDB: project_name = ( @@ -74,9 +80,18 @@ def model_provider(pre_process=True, post_process=True): see_memory_usage("Before Building Model", force=True) args = get_args() config = core_transformer_config_from_args(args) - if wandb.run is not None: - print(f"Updating WandB run: [{wandb.run.name}]({wandb.run.url})") - wandb.run.config.update({"args": vars(args)}) + # if wandb.run is not None and RANK == 0: + # print(f"Updating WandB run: [{wandb.run.name}]({wandb.run.url})") + # try: + # wandb.run.config.update({"args": vars(args)}) + # except Exception: + # log.error( + # 'Unable to `wandb.run.config.update({"args": vars(args)})`' + # ) + # if wandb is not None and wandb.run is not None: + # assert wandb is not None and wandb.run is not None + # print(f'Updating {wandb.run.name=} at {wandb.run.url=}') + # wandb.run.config.update({'args': vars(args)}) if RANK == 0: git_ds_info() if hasattr(mpu, 'get_sequence_parallel_group'): @@ -85,10 +100,6 @@ def model_provider(pre_process=True, post_process=True): dpg = mpu.get_data_parallel_group() else: dpg = None - if wandb is not None and wandb.run is not None: - assert wandb is not None and wandb.run is not None - print(f'Updating {wandb.run.name=} at {wandb.run.url=}') - wandb.run.config.update({'args': vars(args)}) with deepspeed.zero.Init( data_parallel_group=dpg, remote_device=( @@ -153,6 +164,18 @@ def model_provider(pre_process=True, post_process=True): see_memory_usage("After Building Model", force=True) if wandb.run is not None: wandb.run.config.update({'num_params': num_params}) + if "args" not in wandb.run.config: + log.info( + f"Updating WandB run.config: [{wandb.run.name}]({wandb.run.get_url()})" + ) + try: + wandb.run.config.update( + {"args": dict(sorted(vars(args).items()))} + ) + except Exception: + log.error( + 'Unable to `wandb.run.config.update({"args": vars(args)})`' + ) try: wandb.run.watch( model, From b4a310ad19aeba318bd2238fc09796a93549ac57 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 27 Mar 2024 13:18:51 -0500 Subject: [PATCH 148/268] Update `train_llama_alcf_sunspot.sh` --- train_llama_alcf_sunspot.sh | 2 ++ 1 file changed, 2 insertions(+) diff --git a/train_llama_alcf_sunspot.sh b/train_llama_alcf_sunspot.sh index f000506bb9..ea4115aacd 100644 --- a/train_llama_alcf_sunspot.sh +++ b/train_llama_alcf_sunspot.sh @@ -92,6 +92,8 @@ run_cmd=" --no-gradient-accumulation-fusion \ --accumulate-allreduce-grads-in-fp32 \ --use-checkpoint-opt_param-scheduler \ + --log-timers-to-tensorboard \ + --log-optimizer-states-to-tensorboard \ --lr ${LR} \ --save ${CKPT_DIR} \ --load ${CKPT_DIR} \ From 4f7ee536f14601f3febbd18f6f6da9f3c1945ed7 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 27 Mar 2024 13:19:53 -0500 Subject: [PATCH 149/268] Update `megatron/training.py` --- megatron/training.py | 46 +++++++++++++++++++++++++++++++++++++++----- 1 file changed, 41 insertions(+), 5 deletions(-) diff --git a/megatron/training.py b/megatron/training.py index bf87e7b52c..a0dd659b7c 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -63,26 +63,55 @@ def print_datetime(string): time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') print_rank_0('[' + string + '] datetime: {} '.format(time_str)) + +def num_floating_point_operations(args, batch_size): + # Group Query Attention. + # if not args.group_query_attention: + if not args.num_key_value_heads: + args.num_key_value_heads = args.num_attention_heads + # args.num_query_groups = args.num_attention_heads + # MoE. + # num_experts_routed_to = 1 if args.num_experts is None else args.moe_router_topk + num_experts_routed_to = 1 if args.num_experts is None else args.topk + gated_linear_multiplier = 3 / 2 if args.swiglu else 1 + return ( + 12 + * batch_size + * args.seq_length + * args.num_layers + * args.hidden_size + * args.hidden_size + * ( + 1 + + ( + (args.ffn_hidden_size / args.hidden_size) + * num_experts_routed_to + * gated_linear_multiplier + ) + + (args.num_key_value_heads / args.num_attention_heads) + + (args.seq_length / args.hidden_size) + + (args.padded_vocab_size / (2 * args.num_layers * args.hidden_size)) + ) + ) + ''' Since v0.9.0, deepspeed.initialize() has forbidden simultaneous setting of args.deepspeed_config (Path) and ds_config dict. So, we use ds_config dict which is the more flexible option. ''' def _create_ds_config_dict(): args = get_args() + assert args is not None if isinstance(args.deepspeed_config, dict) : ds_config_dict = args.deepspeed_config else: with open(args.deepspeed_config, 'r', encoding='utf-8') as config_file: ds_config_dict = json.load(config_file) - if args.universal_checkpoint: ds_config_dict["checkpoint"] = {"load_universal": True} - # Clear config path - args.deepspeed_config = None - + args.deepspeed_config = None return ds_config_dict - + def pretrain(train_valid_test_dataset_provider, model_provider, @@ -1021,6 +1050,7 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, torch.distributed.all_reduce(opt_stats_2, op=torch.distributed.ReduceOp.MAX, group=mpu.get_pipeline_model_parallel_group()) wandb_metrics |= { + 'optimizer/learning_rate': learning_rate, 'optimizer/iteration': args.iteration, 'optimizer/consumed_train_tokens': args.consumed_train_tokens, 'optimizer/variance_l2': opt_stats[0]**0.5, @@ -1077,6 +1107,10 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, elapsed_time, total_iterations ) + num_flops = num_floating_point_operations(args, batch_size) + # throughput = ( + # num_floating_point_operations_so_far - arg + # ) samples_per_sec_per_replica = samples_per_sec / args.data_parallel_size tokens_per_sec = samples_per_sec * seq_len tokens_per_sec_per_replica = tokens_per_sec / args.data_parallel_size @@ -1091,6 +1125,8 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, 'throughput/tokens_per_gpu_per_sec': tokens_per_gpu_per_second, 'throughput/tokens_per_gpu_per_sec_per_replica': tokens_per_gpu_per_second_per_replica, 'throughput/tflops': tflops, + 'throughput/flops': num_flops, + 'throughput/tflops-new': num_flops / elapsed_time_per_iteration, 'throughput/approx_params_in_billions': approx_parameters_in_billions, 'throughput/elapsed_ms_per_iteration': elapsed_time_per_iteration, 'throughput/iteration': iteration, From 2f9cf05ce56149d3d492914e1c3fe1fd11a5a209 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 27 Mar 2024 13:33:11 -0500 Subject: [PATCH 150/268] Update `train_llama_alcf_{polaris,sunspot}.sh` --- train_llama_alcf_polaris.sh | 13 +++++++++---- train_llama_alcf_sunspot.sh | 5 +++++ 2 files changed, 14 insertions(+), 4 deletions(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index 7cc1454f60..aae931fdba 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -45,6 +45,8 @@ custom_args=" $@" # Assert `./hostfile_deepspeed` exists export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit +TBDIR="${CKPT_DIR}/tensorboard" +mkdir -p "${TBDIR}" # source "${HERE}/venvs/polaris/2024-03-14/bin/activate" || exit # echo "Using $(which python3)" @@ -52,10 +54,11 @@ export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit # deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ # ${launch_cmd} \ # --optimizer adam \ + # --use-flash-attn-v2 \ run_cmd=" deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ - --use-flash-attn-v2 \ --$DTYPE \ + --optimizer ${OPT} \ --num-workers 0 \ --split 100,0,0 \ --log-interval 1 \ @@ -67,11 +70,13 @@ run_cmd=" --no-gradient-accumulation-fusion \ --accumulate-allreduce-grads-in-fp32 \ --use-checkpoint-opt_param-scheduler \ + --tensorboard-dir ${TBDIR} \ + --log-timers-to-tensorboard \ --log-optimizer-states-to-tensorboard \ --lr ${LR} \ - --seq-length $SEQ \ --save ${CKPT_DIR} \ --load ${CKPT_DIR} \ + --seq-length ${SEQ} \ --num-layers ${NLAYERS} \ --hidden-size ${HIDDEN} \ --train-iters ${TRAIN_ITER} \ @@ -98,8 +103,8 @@ run_cmd=" " -echo "All DeepSpeed(s): $(which -a deepspeed)" -echo "Using $(which deepspeed)" +# echo "All DeepSpeed(s): $(which -a deepspeed)" +echo "! Using $(which deepspeed)" ds_report echo "${run_cmd}" diff --git a/train_llama_alcf_sunspot.sh b/train_llama_alcf_sunspot.sh index ea4115aacd..700f5dbfdb 100644 --- a/train_llama_alcf_sunspot.sh +++ b/train_llama_alcf_sunspot.sh @@ -72,6 +72,9 @@ custom_args=" $@" # Assert `./hostfile_deepspeed` exists export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit +TBDIR="${CKPT_DIR}/tensorboard" +mkdir -p "${TBDIR}" + # --use-flash-attn-v2 \ # --use-flash-attn \ # --$DTYPE \ @@ -80,6 +83,7 @@ export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit # --adam-beta2 0.95 \ run_cmd=" deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ + --${DTYPE} \ --optimizer ${OPT} \ --num-workers 0 \ --split 100,0,0 \ @@ -92,6 +96,7 @@ run_cmd=" --no-gradient-accumulation-fusion \ --accumulate-allreduce-grads-in-fp32 \ --use-checkpoint-opt_param-scheduler \ + --tensorboard-dir ${TBDIR} \ --log-timers-to-tensorboard \ --log-optimizer-states-to-tensorboard \ --lr ${LR} \ From 5b9ad9a91d71c9b0573e6ba678ff1d2355a587f1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 1 Apr 2024 23:16:47 -0500 Subject: [PATCH 151/268] Add support for `--optimizer={apex.adam,apex.sgd,adamw,adam,sgd}` --- megatron/optimizer/__init__.py | 31 +++++++++++++++++++++---------- 1 file changed, 21 insertions(+), 10 deletions(-) diff --git a/megatron/optimizer/__init__.py b/megatron/optimizer/__init__.py index e7400c39b5..cdcc344541 100644 --- a/megatron/optimizer/__init__.py +++ b/megatron/optimizer/__init__.py @@ -1,12 +1,6 @@ # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. from deepspeed.accelerator import get_accelerator -# if get_accelerator().device_name() == 'cuda': -# from apex.optimizers import FusedAdam as Adam -# from apex.optimizers import FusedSGD as SGD -# else: -# from torch.optim import Adam -# from torch.optim import SGD import torch from megatron import get_args @@ -94,7 +88,25 @@ def get_megatron_optimizer(model, betas=(args.adam_beta1, args.adam_beta2), eps=args.adam_eps) else: - if str(args.optimizer).lower() == 'adamw': + if str(args.optimizer).lower() == 'apex.adam': + assert get_accelerator().device_name() == 'cuda' + from apex.optimizers import FusedAdam as Adam + optimizer = Adam( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps + ) + elif str(args.optimizer).lower() == 'apex.sgd': + from apex.optimizers import FusedSGD as SGD + optimizer = SGD( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + momentum=args.sgd_momentum + ) + elif str(args.optimizer).lower() == 'adamw': optimizer = torch.optim.AdamW( param_groups, lr=args.lr, @@ -104,7 +116,7 @@ def get_megatron_optimizer(model, ) elif args.optimizer == 'adam': if args.ds_fused_adam: - global Adam + # global Adam from deepspeed.ops.adam import FusedAdam Adam = FusedAdam else: @@ -124,8 +136,7 @@ def get_megatron_optimizer(model, momentum=args.sgd_momentum ) else: - raise Exception(f'{args.optimizer} optimizer is not supported.') - + raise TypeError(f'{args.optimizer} optimizer is not supported.') if args.deepspeed: return optimizer From 294d81f2678f99a747f2bb30238a574e9e6fd5e1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 1 Apr 2024 23:17:17 -0500 Subject: [PATCH 152/268] Add support for \`--optimizer={apex.adam,apex.sgd,adamw,adam,sgd}\` - Updates: - `megatron/arguments.py` --- megatron/arguments.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/megatron/arguments.py b/megatron/arguments.py index cd618b285e..c26bac6fe9 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -914,7 +914,7 @@ def _add_training_args(parser): help='Disable bias in the linear layers', dest='add_bias_linear') group.add_argument('--optimizer', type=str, default='adam', - choices=['adam', 'adamw', 'sgd'], + choices=['adam', 'adamw', 'sgd', 'apex.adam', 'apex.sgd'], help='Optimizer function') group.add_argument('--dataloader-type', type=str, default=None, choices=['single', 'cyclic'], From bed55a033e79bd98e9ffe917dda78926a43c33d1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 08:13:21 -0500 Subject: [PATCH 153/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 23 +++++++++-------------- 1 file changed, 9 insertions(+), 14 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 30d9add286..27e2a65d45 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -80,26 +80,21 @@ setParams() { export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" export SAVE_INTERVAL=${SAVE_INTERVAL:-200} export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} - # export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} - # export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" tm="${PBS_O_WORKDIR}/ALCF/tokenizer.model" - # tm_a=/home/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/tokenizer.model - # tm_p="/eagle/datasets/dolma/utils/tokenizer.model" - # export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm_p:-${tm_a}}}" export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" - # if [[ "${CPU_OPTIMIZER:-0}" ]]; then - # if [[ -n "${CPU_OPTIMIZER}" ]]; then - if [[ "${CPU_OPTIMIZER}" == 1 ]]; then - export OFFLOAD_DEVICE="cpu" - echo "\n!!! Appending \`--cpu-optimizer\` to LLAMA_ARGS..." - export LLAMA_ARGS="${LLAMA_ARGS} --cpu-optimizer" - else - export OFFLOAD_DEVICE="none" - fi + # # if [[ "${CPU_OPTIMIZER:-0}" ]]; then + # # if [[ -n "${CPU_OPTIMIZER}" ]]; then + # if [[ "${CPU_OPTIMIZER}" == 1 ]]; then + # export OFFLOAD_DEVICE="cpu" + # echo "\n!!! Appending \`--cpu-optimizer\` to LLAMA_ARGS..." + # export LLAMA_ARGS="${LLAMA_ARGS} --cpu-optimizer" + # else + # export OFFLOAD_DEVICE="none" + # fi # ---------------------------------------------------- } From fceb3738351b08671053d2d87cba02a256e7c748 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 08:37:21 -0500 Subject: [PATCH 154/268] Update `megatron/data/data_samplers.py` --- megatron/data/data_samplers.py | 89 +++++++++++++++++++++++----------- 1 file changed, 61 insertions(+), 28 deletions(-) diff --git a/megatron/data/data_samplers.py b/megatron/data/data_samplers.py index 0aae13abce..b242101b3a 100644 --- a/megatron/data/data_samplers.py +++ b/megatron/data/data_samplers.py @@ -2,7 +2,6 @@ """Dataloaders.""" - import random import torch import numpy as np @@ -46,7 +45,10 @@ def build_pretraining_data_loader(dataset, consumed_samples): batch_sampler=batch_sampler, num_workers=args.num_workers, pin_memory=True, - multiprocessing_context=args.multiprocessing_context + multiprocessing_context=( + args.multiprocessing_context if args.num_workers > 0 + else None + ) ) if args.repeated_dataloader: loader=RepeatingLoader(loader) @@ -54,28 +56,39 @@ def build_pretraining_data_loader(dataset, consumed_samples): class MegatronPretrainingSampler: - def __init__(self, total_samples, consumed_samples, micro_batch_size, - data_parallel_rank, data_parallel_size, drop_last=True): + def __init__( + self, + total_samples, + consumed_samples, + micro_batch_size, + data_parallel_rank, + data_parallel_size, + drop_last=True + ): # Keep a copy of input params for later use. self.total_samples = total_samples self.consumed_samples = consumed_samples self.micro_batch_size = micro_batch_size self.data_parallel_rank = data_parallel_rank - self.micro_batch_times_data_parallel_size = \ + self.micro_batch_times_data_parallel_size = ( self.micro_batch_size * data_parallel_size + ) self.drop_last = drop_last # Sanity checks. - assert self.total_samples > 0, \ - 'no sample to consume: {}'.format(self.total_samples) - assert self.consumed_samples < self.total_samples, \ - 'no samples left to consume: {}, {}'.format(self.consumed_samples, - self.total_samples) + assert self.total_samples > 0, ( + f'no sample to consume: {self.total_samples}' + ) + assert self.consumed_samples < self.total_samples, ( + 'no samples left to consume: ' + f'{self.consumed_samples}, {self.total_samples}' + ) assert self.micro_batch_size > 0 assert data_parallel_size > 0 - assert self.data_parallel_rank < data_parallel_size, \ - 'data_parallel_rank should be smaller than data size: {}, ' \ - '{}'.format(self.data_parallel_rank, data_parallel_size) + assert self.data_parallel_rank < data_parallel_size, ( + f'data_parallel_rank should be smaller than data size: ' + f'{self.data_parallel_rank}, {data_parallel_size}' + ) def __len__(self): return self.total_samples @@ -125,8 +138,16 @@ def __getitem__(self, idx): class MegatronPretrainingRandomSampler: - def __init__(self, dataset, total_samples, consumed_samples, micro_batch_size, - data_parallel_rank, data_parallel_size, data_sharding): + def __init__( + self, + dataset, + total_samples, + consumed_samples, + micro_batch_size, + data_parallel_rank, + data_parallel_size, + data_sharding + ): # Keep a copy of input params for later use. self.dataset = dataset self.total_samples = total_samples @@ -135,19 +156,23 @@ def __init__(self, dataset, total_samples, consumed_samples, micro_batch_size, self.data_parallel_rank = data_parallel_rank self.data_parallel_size = data_parallel_size self.data_sharding = data_sharding - self.micro_batch_times_data_parallel_size = \ + self.micro_batch_times_data_parallel_size = ( self.micro_batch_size * data_parallel_size - self.last_batch_size = \ + ) + self.last_batch_size = ( self.total_samples % self.micro_batch_times_data_parallel_size + ) # Sanity checks. - assert self.total_samples > 0, \ - 'no sample to consume: {}'.format(self.total_samples) + assert self.total_samples > 0, ( + f'no sample to consume: {self.total_samples}' + ) assert self.micro_batch_size > 0 assert data_parallel_size > 0 - assert self.data_parallel_rank < data_parallel_size, \ - 'data_parallel_rank should be smaller than data size: {}, ' \ - '{}'.format(self.data_parallel_rank, data_parallel_size) + assert self.data_parallel_rank < data_parallel_size, ( + f'data_parallel_rank should be smaller than data size: ' + f'{self.data_parallel_rank}, {data_parallel_size}' + ) def __len__(self): return self.total_samples @@ -163,23 +188,31 @@ def __iter__(self): # data sharding and random sampling if self.data_sharding: - bucket_size = (self.total_samples // self.micro_batch_times_data_parallel_size) \ - * self.micro_batch_size + bucket_size = ( + self.micro_batch_size * ( + self.total_samples + // self.micro_batch_times_data_parallel_size + ) + ) bucket_offset = current_epoch_samples // self.data_parallel_size start_idx = self.data_parallel_rank * bucket_size - g = torch.Generator() g.manual_seed(self.epoch) random_idx = torch.randperm(bucket_size, generator=g).tolist() idx_range = [start_idx + x for x in random_idx[bucket_offset:]] else: - full_bucket_size = (self.total_samples // self.micro_batch_size) \ - * self.micro_batch_size + full_bucket_size = ( + self.micro_batch_size * ( + self.total_samples + // self.micro_batch_size + ) + ) full_bucket_offset = current_epoch_samples g = torch.Generator() g.manual_seed(self.epoch) - idx_range_total = \ + idx_range_total = ( torch.randperm(full_bucket_size, generator=g).tolist() + ) idx_range_active = idx_range_total[full_bucket_offset:] idx_range = idx_range_active[self.data_parallel_rank::self.data_parallel_size] From 07bb7bf87a7710a114645840de8ffe60dd854467 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 08:40:39 -0500 Subject: [PATCH 155/268] Add `train_llama_alcf.sh` --- train_llama_alcf.sh | 112 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 112 insertions(+) create mode 100644 train_llama_alcf.sh diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh new file mode 100644 index 0000000000..0a2e7e5643 --- /dev/null +++ b/train_llama_alcf.sh @@ -0,0 +1,112 @@ +#!/bin/bash --login +#PBS -l walltime=06:00:00 +#PBS -A argonne_tpc +#PBS -q prod +#PBS -l select=48 +#PBS -l filesystems=eagle:home + +function sourceFile() { + fp="$1" + echo "source-ing ${fp}" + if [[ -f "${fp}" ]]; then + # shellcheck source="${fp}" + source "${fp}" + else + echo "ERROR: UNABLE TO SOURCE ${fp}" + fi +} + +# ----[0. Navigate into `$PBS_O_WORKDIR`]------------------------------------- +cd "${PBS_O_WORKDIR}" || exit +HERE=$(python3 -c 'import os; print(os.getcwd())') +export HERE +# ----[1. Assert `./pretrain_gpt_alcf.py` exists:]----------------------------- +export EXEC="${HERE}/pretrain_gpt_alcf.py" +[ -f "${EXEC}" ] || exit +# ----[2. `source ./ALCF/helpers_alcf.sh`:]------------------------------------ +sourceFile "${HERE}/ALCF/helpers.sh" || exit +# ----[3. Call fns from `./ALCF/helpers_alcf.sh`]------------------------------ +setEnv || exit # 1. load `conda` environment +saveDSenv || exit # 2. save env vars to `.deepspeed_env` +ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars +makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` +buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ +setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} +setArgs || exit # 8. specify additional `deepspeed` arguments +setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset +setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` +printJobInfo || exit # 11. print job info +# ----------------------------------------------------------------------------- + +# Take custom args +custom_args=" $@" + +# Assert `./hostfile_deepspeed` exists +export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit +TBDIR="${CKPT_DIR}/tensorboard" +mkdir -p "${TBDIR}" + +# source "${HERE}/venvs/polaris/2024-03-14/bin/activate" || exit +# echo "Using $(which python3)" +# --launcher_args='--pmi=pmix' + # deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ + # ${launch_cmd} \ + # --optimizer adam \ + # --use-flash-attn-v2 \ + # --num-workers 0 \ +run_cmd=" + deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ + --$DTYPE \ + --optimizer ${OPT} \ + --split 100,0,0 \ + --log-interval 1 \ + --no-bias-gelu-fusion \ + --lr-decay-style cosine \ + --no-bias-dropout-fusion \ + --no-masked-softmax-fusion \ + --tokenizer-type Llama2Tokenizer \ + --no-gradient-accumulation-fusion \ + --accumulate-allreduce-grads-in-fp32 \ + --use-checkpoint-opt_param-scheduler \ + --tensorboard-dir ${TBDIR} \ + --log-timers-to-tensorboard \ + --log-optimizer-states-to-tensorboard \ + --lr ${LR} \ + --save ${CKPT_DIR} \ + --load ${CKPT_DIR} \ + --seq-length ${SEQ} \ + --num-layers ${NLAYERS} \ + --hidden-size ${HIDDEN} \ + --train-iters ${TRAIN_ITER} \ + --eval-iters ${EVAL_ITERS} \ + --distributed-backend ${BE} \ + --num-attention-heads ${HEADS} \ + --save-interval ${SAVE_INTERVAL} \ + --eval-interval ${EVAL_INTERVAL} \ + --max-position-embeddings ${SEQ} \ + --micro-batch-size ${MICRO_BATCH} \ + --data-file-list ${DATA_FILE_LIST} \ + --tensor-model-parallel-size ${TP} \ + --global-batch-size ${GLOBAL_BATCH} \ + --pipeline-model-parallel-size ${PP} \ + --num-key-value-heads ${NUM_KV_HEAD} \ + --data-cache-path ${DATA_CACHE_PATH} \ + --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ + --tokenizer-model ${TOKENIZER_MODEL} \ + ${LLAMA_ARGS} \ + $ds_args \ + ${gpt_args[*]} \ + $custom_args \ + |& tee ${OUTPUT_LOG} + " + +echo "! Using $(which deepspeed)" +ds_report + +echo "${run_cmd}" + +printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" +printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" +eval "${run_cmd}" +set +x From 3c1cdb4c31bdde9503f0fe9f0a7869704b52bc2b Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 08:41:18 -0500 Subject: [PATCH 156/268] Update `megatron/global_vars.py` --- megatron/global_vars.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/megatron/global_vars.py b/megatron/global_vars.py index cb284b3c34..9f833fbd19 100644 --- a/megatron/global_vars.py +++ b/megatron/global_vars.py @@ -96,7 +96,7 @@ def set_global_variables(args): if args.exit_signal_handler: _set_signal_handler() - + def set_args(args): global _GLOBAL_ARGS @@ -137,11 +137,10 @@ def _set_tensorboard_writer(args): global _GLOBAL_TENSORBOARD_WRITER _ensure_var_is_not_initialized(_GLOBAL_TENSORBOARD_WRITER, 'tensorboard writer') - if hasattr(args, 'tensorboard_dir') and \ args.tensorboard_dir and args.rank == (args.world_size - 1): try: - from torch.utils.tensorboard import SummaryWriter + from torch.utils.tensorboard.writer import SummaryWriter print('> setting tensorboard ...') _GLOBAL_TENSORBOARD_WRITER = SummaryWriter( log_dir=args.tensorboard_dir, @@ -179,9 +178,9 @@ def _set_timers(args): def _ensure_var_is_initialized(var, name): """Make sure the input variable is not None.""" - assert var is not None, '{} is not initialized.'.format(name) + assert var is not None, f'{name} is not initialized.' def _ensure_var_is_not_initialized(var, name): """Make sure the input variable is not None.""" - assert var is None, '{} is already initialized.'.format(name) + assert var is None, f'{name} is already initialized.' From 5fe64ac06fa31a735d146b1154e82665850f92f5 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 08:45:55 -0500 Subject: [PATCH 157/268] Turn on flops profiler in `generate_config.sh` --- generate_config.sh | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/generate_config.sh b/generate_config.sh index e140b7a274..d5b1264219 100644 --- a/generate_config.sh +++ b/generate_config.sh @@ -49,7 +49,7 @@ common="\ flops_profiler="\ \"flops_profiler\": { - \"enabled\": false, + \"enabled\": true, \"profile_step\": 45, \"module_depth\": -1, \"top_modules\": 1, @@ -94,6 +94,8 @@ zero="\ \"zero_optimization\": { \"stage\": 3, \"reduce_scatter\": false, + \"mics_shard_size\": 4, + \"mics_hierarchical_params_gather\": true, \"stage3_max_live_parameters\": 3e9, \"stage3_max_reuse_distance\": 3e9, \"stage3_param_persistence_threshold\": 1e5, @@ -145,7 +147,14 @@ if [[ $PP > 1 ]]; then \"debug\": false }," else - echo 'please add the config for zero_stage 1 without pipeline-parallelism' + # echo 'please add the config for zero_stage 1 without pipeline-parallelism' + extra="\ + \"comms_logger\": { + \"enabled\": true, + \"verbose\": false, + \"prof_all\": true, + \"debug\": false + }," fi else echo 'Please add the correct config set!!!' From 316fd938f076ef7e75ba692c2ac4ca0fa99bc857 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 08:46:31 -0500 Subject: [PATCH 158/268] Update `megatron/model/language_model.py` --- megatron/model/language_model.py | 132 +++++++++++++++++++++---------- 1 file changed, 89 insertions(+), 43 deletions(-) diff --git a/megatron/model/language_model.py b/megatron/model/language_model.py index ec2ae1877a..ceef5be725 100644 --- a/megatron/model/language_model.py +++ b/megatron/model/language_model.py @@ -389,10 +389,16 @@ def __init__(self, post_process=True, num_experts=[1]): args = get_args() - # TODO: passing share_embeddings_and_output_weights=False will not work correctly for T5 and embeddings will not be synced. Fix later for T5. - if args.untie_embeddings_and_output_weights: assert not add_decoder - super(TransformerLanguageModel, self).__init__(share_embeddings_and_output_weights=not args.untie_embeddings_and_output_weights) - + # TODO: passing `share_embeddings_and_output_weights=False` + # will not work correctly for T5 and embeddings will not be synced. + # Fix later for T5. + if args.untie_embeddings_and_output_weights: + assert not add_decoder + super(TransformerLanguageModel, self).__init__( + share_embeddings_and_output_weights=( + not args.untie_embeddings_and_output_weights + ) + ) self.pre_process = pre_process self.post_process = post_process self.hidden_size = config.hidden_size @@ -405,27 +411,35 @@ def __init__(self, self.add_pooler = add_pooler self.encoder_hidden_state = None self.add_retriever = args.retro_add_retriever - self.untie_embeddings_and_output_weights = args.untie_embeddings_and_output_weights + self.untie_embeddings_and_output_weights = ( + args.untie_embeddings_and_output_weights + ) self.num_experts = num_experts # Embeddings. if self.pre_process: - self.embedding = Embedding(self.hidden_size, - args.padded_vocab_size, - args.max_position_embeddings, - args.hidden_dropout, - config, - self.num_tokentypes, - args.embedding_weights_in_fp32) + self.embedding = Embedding( + self.hidden_size, + args.padded_vocab_size, + args.max_position_embeddings, + args.hidden_dropout, + config, + self.num_tokentypes, + args.embedding_weights_in_fp32 + ) self._embedding_key = 'embedding' # Rotary positional embeddings - self.use_rotary_position_embeddings = \ - args.use_rotary_position_embeddings + self.use_rotary_position_embeddings = ( + args.use_rotary_position_embeddings + ) if args.use_rotary_position_embeddings: self.seq_length = args.seq_length - rotary_dim = args.hidden_size // args.num_attention_heads \ - if args.kv_channels is None else args.kv_channels + rotary_dim = ( + args.hidden_size // args.num_attention_heads + if args.kv_channels is None + else args.kv_channels + ) if args.rotary_percent < 1.0: rotary_dim = int(rotary_dim * args.rotary_percent) @@ -433,15 +447,22 @@ def __init__(self, # partial rotary embeddings, which is better than full rotary # Wang and Komatsuzaki et al # https://github.com/kingoflolz/mesh-transformer-jax/ - self.rotary_pos_emb = RotaryEmbedding(rotary_dim, theta=args.rope_theta) + self.rotary_pos_emb = RotaryEmbedding( + rotary_dim, + theta=args.rope_theta + ) # Encoder (usually set to True, False if part of an encoder-decoder # architecture and in encoder-only stage). if self.add_encoder: self.encoder = ParallelTransformer( config, - model_type=args.model_type if not args.retro_add_retriever \ - else ModelType.retro_decoder, + # args.model_type if not args.retro_add_retriever + # else ModelType.retro_decoder + model_type=( + ModelType.retro_decoder if args.retro_add_retriever + else args.model_type + ), self_attn_mask_type=self.encoder_attn_mask_type, pre_process=self.pre_process, post_process=self.post_process, @@ -461,7 +482,8 @@ def __init__(self, self_attn_mask_type=self.decoder_attn_mask_type, pre_process=self.pre_process, post_process=self.post_process, - num_experts=self.num_experts) + num_experts=self.num_experts + ) self._decoder_key = 'decoder' else: self.decoder = None @@ -478,24 +500,30 @@ def __init__(self, args.padded_vocab_size, config=config, init_method=self.init_method, - bias=False) # Setting bias to False always to keep it consistent with embedding tying that also does not have a bias. + # Setting bias to False always to keep it consistent with + # embedding tying that also does not have a bias. + bias=False + ) self._output_layer_key = 'output_layer' def set_input_tensor(self, input_tensor): """ See megatron.model.transformer.set_input_tensor()""" - # This is usually handled in schedules.py but some inference code still # gives us non-lists or None if not isinstance(input_tensor, list): input_tensor = [input_tensor] if self.add_encoder and self.add_decoder: - assert len(input_tensor) == 1, \ - 'input_tensor should only be length 1 for stage with both encoder and decoder' + assert len(input_tensor) == 1, ( + 'input_tensor should only be length 1 ' + 'for stage with both encoder and decoder' + ) self.encoder.set_input_tensor(input_tensor[0]) elif self.add_encoder: - assert len(input_tensor) == 1, \ - 'input_tensor should only be length 1 for stage with only encoder' + assert len(input_tensor) == 1, ( + 'input_tensor should only be length 1 ' + 'for stage with only encoder' + ) self.encoder.set_input_tensor(input_tensor[0]) elif self.add_decoder: if len(input_tensor) == 2: @@ -505,32 +533,50 @@ def set_input_tensor(self, input_tensor): self.decoder.set_input_tensor(None) self.encoder_hidden_state = input_tensor[0] else: - raise Exception('input_tensor must have either length 1 or 2') + raise Exception( + 'input_tensor must have either length 1 or 2' + ) else: - raise Exception('Stage must have at least either encoder or decoder') - - def forward(self, enc_input_ids, enc_position_ids, enc_attn_mask, - dec_input_ids=None, dec_position_ids=None, dec_attn_mask=None, - retriever_input_ids=None, - retriever_position_ids=None, - retriever_attn_mask=None, - enc_dec_attn_mask=None, tokentype_ids=None, - inference_params=None, - pooling_sequence_index=0, - enc_hidden_states=None, output_enc_hidden=False): + raise Exception( + 'Stage must have at least either encoder or decoder' + ) + + def forward( + self, + enc_input_ids, + enc_position_ids, + enc_attn_mask, + dec_input_ids=None, + dec_position_ids=None, + dec_attn_mask=None, + retriever_input_ids=None, + retriever_position_ids=None, + retriever_attn_mask=None, + enc_dec_attn_mask=None, + tokentype_ids=None, + inference_params=None, + pooling_sequence_index=0, + enc_hidden_states=None, + output_enc_hidden=False + ): args = get_args() # Encoder embedding. if self.pre_process: - encoder_input = self.embedding(enc_input_ids, enc_position_ids, - tokentype_ids=tokentype_ids) + encoder_input = self.embedding( + enc_input_ids, + enc_position_ids, + tokentype_ids=tokentype_ids + ) else: encoder_input = None # Retriever embedding. if self.add_retriever and self.pre_process: - retriever_input = self.embedding(retriever_input_ids, - retriever_position_ids, - tokentype_ids=tokentype_ids) + retriever_input = self.embedding( + retriever_input_ids, + retriever_position_ids, + tokentype_ids=tokentype_ids + ) else: retriever_input = None From 69bb53e70f6ce27233b24e39633adde9f94c6e89 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 08:47:03 -0500 Subject: [PATCH 159/268] Remove `--num-workers 0` in `train_llama_alcf_polaris.sh` --- train_llama_alcf_polaris.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh index aae931fdba..06f268f10e 100644 --- a/train_llama_alcf_polaris.sh +++ b/train_llama_alcf_polaris.sh @@ -55,11 +55,11 @@ mkdir -p "${TBDIR}" # ${launch_cmd} \ # --optimizer adam \ # --use-flash-attn-v2 \ + # --num-workers 0 \ run_cmd=" deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ --$DTYPE \ --optimizer ${OPT} \ - --num-workers 0 \ --split 100,0,0 \ --log-interval 1 \ --no-bias-gelu-fusion \ From 2a36f142296bd4a3da3cccdb50cdc22dc6786663 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 08:54:18 -0500 Subject: [PATCH 160/268] Update `megatron/timers.py` --- megatron/timers.py | 28 +++++++++++++++++++++++++--- 1 file changed, 25 insertions(+), 3 deletions(-) diff --git a/megatron/timers.py b/megatron/timers.py index 384c7c37a3..870ba8996f 100644 --- a/megatron/timers.py +++ b/megatron/timers.py @@ -8,8 +8,14 @@ import torch from deepspeed.accelerator import get_accelerator +from tensorboard.summary import Writer from packaging import version +try: + import wandb +except Exception: + wandb = None + class TimerBase(ABC): @@ -292,8 +298,15 @@ def log(self, names, rank=None, normalizer=1.0, reset=True, barrier=False): print(output_string, flush=True) - def write(self, names, writer, iteration, normalizer=1.0, - reset=False, barrier=False): + def write( + self, + names: list[str], + writer: Writer, + iteration: int, + normalizer: float = 1.0, + reset: bool = False, + barrier: bool = False + ): """Write timers to a tensorboard writer Note that we only report maximum time across ranks to tensorboard. """ @@ -303,7 +316,16 @@ def write(self, names, writer, iteration, normalizer=1.0, assert normalizer > 0.0 name_to_min_max_time = self._get_global_min_max_time( names, reset, barrier, normalizer) + timer_data = { + 'timers/iteration': iteration, + **{ + f'timers/{k}-time': name_to_min_max_time[k][1] + for k in name_to_min_max_time + } + } + if wandb is not None and getattr(wandb, 'run', None) is not None: + wandb.log(timer_data, commit=False) if writer is not None: for name in name_to_min_max_time: _, max_time = name_to_min_max_time[name] - writer.add_scalar(name + '-time', max_time, iteration) + writer.add_scalar(f'{name}-time', max_time, iteration) From 58b1696fe3e349b9c29a223886e103bf23f5c196 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 07:07:26 -0700 Subject: [PATCH 161/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 71 ++++++++++++++++++++++++------------------------- 1 file changed, 35 insertions(+), 36 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 27e2a65d45..d5d7042089 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -12,6 +12,19 @@ printJobInfo() { echo "++++++++++++++++++++++++++++++++++++++++++++++++++" } + +function setupSrun() { + if [[ $(hostname) == login* || $(hostname) == nid* ]]; then + export NHOSTS="${SLURM_NNODES:-1}" + export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" + export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + export SRUN_EXEC="srun --gpus ${NGPUS} --gpus-per-node ${NGPU_PER_HOST} -N ${NHOSTS} -n ${NGPUS} -l -u --verbose" + else + echo "Skipping setupSrun() on $(hostname)" + fi +} + + function setDSlauncher() { # launcher setting outdir=$1 @@ -35,11 +48,11 @@ setParams() { # -------- [Aurora] ---- || ----- [SunSpot] ------------ if [[ $(hostname) == x4* || $(hostname) == x1* ]]; then TP=${TP:-1} # TP = 1 - PP=${PP:-1} # PP = 1 export CCL=${CCL:-ccl} # CCL export BE="${CCL}" # BE = CCL export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 + export WORKING_DIR="${PBS_O_WORKDIR}" # if [[ -z "${CPU_OPTIMIZER}" ]]; then # CPU_OPTIMIZER=1 # fi @@ -48,17 +61,24 @@ setParams() { # -------- [Polaris] ----------------------------------- elif [[ $(hostname) == x3* ]]; then TP=${TP:-2} # TP = 2 - PP=${PP:-1} # PP = 1 export NCCL=${NCCL:-nccl} # NCCL export BE="${NCCL}" # BE = NCCL # export DTYPE=${DTYPE:-bf16} # DTYPE: BF16 ?? export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 + export WORKING_DIR="${PBS_O_WORKDIR}" + elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then + TP="${TP:-2}" + export NCCL="${NCCL:-nccl}" + export BE="${CCL}" + export DTYPE="${DTYPE:-bf16}" + MICRO_BATCH="${MICRO_BATCH:-8}" + export WORKING_DIR="${SLURM_SUBMIT_DIR}" fi # ------------------------------------------------------------------------ - # export OFFLOAD_DEVICE="${OFFLOAD_DEVICE:-none}" - export PP="${PP}" export TP="${TP}" + export PP="${PP:-1}" + export DTYPE="${DTYPE:-bf16}" export OPT="${OPT:-adamw}" export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} @@ -82,19 +102,10 @@ setParams() { export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" - tm="${PBS_O_WORKDIR}/ALCF/tokenizer.model" + tm="${WORKING_DIR}/ALCF/tokenizer.model" export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" - # # if [[ "${CPU_OPTIMIZER:-0}" ]]; then - # # if [[ -n "${CPU_OPTIMIZER}" ]]; then - # if [[ "${CPU_OPTIMIZER}" == 1 ]]; then - # export OFFLOAD_DEVICE="cpu" - # echo "\n!!! Appending \`--cpu-optimizer\` to LLAMA_ARGS..." - # export LLAMA_ARGS="${LLAMA_ARGS} --cpu-optimizer" - # else - # export OFFLOAD_DEVICE="none" - # fi # ---------------------------------------------------- } @@ -176,14 +187,8 @@ buildDSconfig() { export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" echo "DS_CONFIG: ${DS_CONFIG}" printf "ZS: %s, CPU_OPTIMIZER: %s, MB: %s, GB: %s, PP: %s, DTYPE: %s" "${ZERO_STAGE}" "${CPU_OPTIMIZER}" "${MICRO_BATCH}" "${GLOBAL_BATCH}" "${PP}" "${DTYPE}" - bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" - # if [[ -z "${CPU_OPTIMIZER}" ]]; then - # echo "!!! Using GPU Optimizer !!!" - # bash "${PBS_O_WORKDIR}/generate_config.sh" "${DS_CONFIG}" #|| exit 1 - # else - # echo "!!! Using CPU Optimizer !!!" - # bash "${PBS_O_WORKDIR}/generate_config_cpu_optimizer.sh" "${DS_CONFIG}" - # fi + working_dir="${PBS_O_WORKDIR:-${SLURM_SUBMIT_DIR:-$(pwd)}}" + bash "${working_dir}/generate_config.sh" "${DS_CONFIG}" # ------------------------------------------------------------- } @@ -224,29 +229,21 @@ setEnv() { echo "Running on Polaris !!" # ---- [load conda] --------------------- module load conda/2023-10-04; conda activate cu118-pt221 ; unset PYTHONUSERBASE - # module load conda/2023-10-04 ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/py311-cu118 - # ; conda activate /lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06 - # export PYTHONUSERBASE="${HOME}/.local/polaris/conda/py311-cu118" - # mkdir -p "${PYTHONUSERBASE}" - # if [[ "${VIRTUAL_ENV}" ]]; then - # echo "Caught VIRTUAL_ENV = ${VIRTUAL_ENV} from environment!!" - # else - # echo "Not using VIRTUAL_ENV" - # # sourceFile "${HERE}/venvs/polaris/2023-10-04/bin/activate" || exit - # fi + elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then + echo "Running on Perlmutter !!" + module load pytorch + source "${SLURM_SUBMIT_DIR}/venvs/perlmutter/pytorch-2.1.0-cu12/bin/activate" else # ------------------------------------- [Unknown] ------------------- echo "Unknown hostname $(hostname)" exit 1 fi + echo "[python] Using: $(which python3)" } makeHostfiles() { - # GPUS_PER_NODE=$(python3 -Wignore -c 'import ezpz; print(ezpz.get_gpus_per_node())') - # source $(python3 -c 'import ezpz; print(ezpz.SAVEJOBENV.as_posix())') || exit - # source $(python3 -c 'import ezpz; print(ezpz.GETJOBENV.as_posix())') || exit source ezpz/src/ezpz/bin/savejobenv || exit #> /tmp/savejobenv.log 2>&1 & source ezpz/src/ezpz/bin/getjobenv || exit - export GPUS_PER_NODE="${GPUS_PER_NODE:-${NGPU_PER_HOST}}" + export GPUS_PER_NODE="${GPUS_PER_NODE:-${NGPU_PER_HOST:-${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}}}" # ---- Make MPICH hostfile ---------------- hf="${HOSTFILE:-${PBS_NODEFILE}}" export hostfile_mpich=hostfile_mpich @@ -264,6 +261,8 @@ setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- dfl_fallback="/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_file_list_reweighted.txt" elif [[ $(hostname) == x3* ]]; then dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" + elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then + dfl_fallback="${SLURM_SUBMIT_DIR}/genslm-subsample.txt" else echo "Unknown hostname. Must manually specify DATA_FILE_LIST." fi From 9ac01590afc89016a3cfb699fc5c5d15e42f15a0 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 07:31:56 -0700 Subject: [PATCH 162/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index d5d7042089..c0976bd6de 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -53,11 +53,6 @@ setParams() { export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 export WORKING_DIR="${PBS_O_WORKDIR}" - # if [[ -z "${CPU_OPTIMIZER}" ]]; then - # CPU_OPTIMIZER=1 - # fi - # echo "!!!! Using CPU_OPTIMIZER on Intel XPU by Default !!!!" - # export CPU_OPTIMIZER=${CPU_OPTIMIZER:-1} # CPU OPTIMIZER ON INTEL XPU # -------- [Polaris] ----------------------------------- elif [[ $(hostname) == x3* ]]; then TP=${TP:-2} # TP = 2 @@ -67,10 +62,11 @@ setParams() { export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 export WORKING_DIR="${PBS_O_WORKDIR}" + # -------- [Perlmutter] --------------------------------- elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then TP="${TP:-2}" export NCCL="${NCCL:-nccl}" - export BE="${CCL}" + export BE="${NCCL}" export DTYPE="${DTYPE:-bf16}" MICRO_BATCH="${MICRO_BATCH:-8}" export WORKING_DIR="${SLURM_SUBMIT_DIR}" From e54063b8267a00c5328dd4a4ef966b13537e6227 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 07:33:04 -0700 Subject: [PATCH 163/268] Add `train_llama_nersc_perlmutter.sh` --- train_llama_nersc_perlmutter.sh | 141 ++++++++++++++++++++++++++++++++ 1 file changed, 141 insertions(+) create mode 100644 train_llama_nersc_perlmutter.sh diff --git a/train_llama_nersc_perlmutter.sh b/train_llama_nersc_perlmutter.sh new file mode 100644 index 0000000000..8131579809 --- /dev/null +++ b/train_llama_nersc_perlmutter.sh @@ -0,0 +1,141 @@ +#!/bin/bash --login +#SBATCH -A m4388_g +#SBATCH -C 'gpu&hbm80g' +#SBATCH -q regular +#SBATCH -t 00:30:00 +#SBATCH --nodes 128 +#SBATCH --gpus 512 +# + +function sourceFile() { + fp="$1" + echo "source-ing ${fp}" + if [[ -f "${fp}" ]]; then + # shellcheck source="${fp}" + source "${fp}" + else + echo "ERROR: UNABLE TO SOURCE ${fp}" + fi +} + +# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +# ---- 0. Navigate into `$PBS_O_WORKDIR` ------------------------------------- +# cd "${PBS_O_WORKDIR}" || exit +cd "${SLURM_SUBMIT_DIR}" || exit +HERE=$(python3 -c 'import os; print(os.getcwd())') +export HERE +# dflfb="${HERE}/genslm-subsample.txt" +# ---- 1. Assert `./pretrain_gpt_alcf.py` exists: ----------------------------- +export EXEC="${HERE}/pretrain_gpt_alcf.py" +[ -f "${EXEC}" ] || exit +# ---- 2. `source ./ALCF/helpers_alcf.sh`: ------------------------------------ +sourceFile "${HERE}/ALCF/helpers.sh" || exit +# ---- 3. Call fns from `./ALCF/helpers_alcf.sh` ------------------------------ +setEnv || exit # 1. load `conda` environment +saveDSenv || exit # 2. save env vars to `.deepspeed_env` +ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars +makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` +buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ +setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} +setArgs || exit # 8. specify additional `deepspeed` arguments +setData "${DATA_FILE_LIST:-${dflfb}}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset +setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` +printJobInfo || exit # 11. print job info +# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + +# Take custom args +custom_args=" $@" + +# Assert `./hostfile_deepspeed` exists +export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit +TBDIR="${CKPT_DIR}/tensorboard" +mkdir -p "${TBDIR}" + +# source "${HERE}/venvs/polaris/2024-03-14/bin/activate" || exit +# echo "Using $(which python3)" +# --launcher_args='--pmi=pmix' + # deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ + # ${launch_cmd} \ + # --optimizer adam \ + # --use-flash-attn-v2 \ + # deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ +# source ezpz/src/ezpz/bin/getjobenv || exit +# if [[ -z "${DIST_LAUNCH}" ]]; then +# setupSrun || exit +# echo "Using SRUN_EXEC: ${SRUN_EXEC}" +# else +# SRUN_EXEC="${DIST_LAUNCH}" +# fi +# echo "Using SRUN_EXEC: ${SRUN_EXEC}" +# +export NHOSTS="${SLURM_NNODES:-1}" +export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" +export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" +export SRUN_EXEC="srun --gpus ${NGPUS} --gpus-per-node ${NGPU_PER_HOST} -N ${NHOSTS} -n ${NGPUS} -l -u --verbose" + + # srun --gpus ${NGPUS} \ + # --gpus-per-node ${NGPU_PER_HOST} \ + # -N ${NHOSTS} \ + # -n ${NGPUS} \ + # -l -u --verbose python3 ${EXEC} \ +run_cmd=" + ${SRUN_EXEC} python3 ${EXEC} \ + --$DTYPE \ + --optimizer ${OPT} \ + --num-workers 0 \ + --split 100,0,0 \ + --log-interval 1 \ + --no-bias-gelu-fusion \ + --lr-decay-style cosine \ + --no-bias-dropout-fusion \ + --no-masked-softmax-fusion \ + --tokenizer-type Llama2Tokenizer \ + --no-gradient-accumulation-fusion \ + --accumulate-allreduce-grads-in-fp32 \ + --use-checkpoint-opt_param-scheduler \ + --tensorboard-dir ${TBDIR} \ + --log-timers-to-tensorboard \ + --log-optimizer-states-to-tensorboard \ + --lr ${LR} \ + --save ${CKPT_DIR} \ + --load ${CKPT_DIR} \ + --seq-length ${SEQ} \ + --num-layers ${NLAYERS} \ + --hidden-size ${HIDDEN} \ + --train-iters ${TRAIN_ITER} \ + --eval-iters ${EVAL_ITERS} \ + --distributed-backend ${BE} \ + --num-attention-heads ${HEADS} \ + --save-interval ${SAVE_INTERVAL} \ + --eval-interval ${EVAL_INTERVAL} \ + --max-position-embeddings ${SEQ} \ + --micro-batch-size ${MICRO_BATCH} \ + --data-file-list ${DATA_FILE_LIST} \ + --tensor-model-parallel-size ${TP} \ + --global-batch-size ${GLOBAL_BATCH} \ + --pipeline-model-parallel-size ${PP} \ + --num-key-value-heads ${NUM_KV_HEAD} \ + --data-cache-path ${DATA_CACHE_PATH} \ + --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ + --tokenizer-model ${TOKENIZER_MODEL} \ + ${LLAMA_ARGS} \ + $ds_args \ + ${gpt_args[*]} \ + $custom_args \ + |& tee ${OUTPUT_LOG} + " + +run_cmd=$(echo "${run_cmd}" | sed -e 's/ */ /g') + +# echo "All DeepSpeed(s): $(which -a deepspeed)" +echo "! Using $(which deepspeed)" +ds_report + +echo "${run_cmd}" + +printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" +printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" +# echo "${OUTPUT_LOG}" +eval "${run_cmd}" +set +x From 8ac8bdc651f0fe31c5960294b9f1a21d57b006e8 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 10:01:38 -0500 Subject: [PATCH 164/268] Update `{train_llama_alcf.sh,ALCF/helpers.sh}` --- ALCF/helpers.sh | 3 +++ train_llama_alcf.sh | 10 +++++----- 2 files changed, 8 insertions(+), 5 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index c0976bd6de..ee97709ef4 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -102,6 +102,9 @@ setParams() { export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" + if [[ -z "${NO_FLASH_ATTN}" ]]; then + export LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" + fi # ---------------------------------------------------- } diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 0a2e7e5643..f0c939b9f7 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -50,11 +50,11 @@ mkdir -p "${TBDIR}" # source "${HERE}/venvs/polaris/2024-03-14/bin/activate" || exit # echo "Using $(which python3)" # --launcher_args='--pmi=pmix' - # deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ - # ${launch_cmd} \ - # --optimizer adam \ - # --use-flash-attn-v2 \ - # --num-workers 0 \ +# deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ +# ${launch_cmd} \ +# --use-flash-attn-v2 \ +# --num-workers 0 \ + run_cmd=" deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ --$DTYPE \ From 8c6c91f5ecc2eccf87a192cdfe4a86b620165013 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 10:02:01 -0500 Subject: [PATCH 165/268] Update `megatron/training.py` --- megatron/training.py | 23 ++++++++++++++--------- 1 file changed, 14 insertions(+), 9 deletions(-) diff --git a/megatron/training.py b/megatron/training.py index a0dd659b7c..9b701ea687 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -113,15 +113,17 @@ def _create_ds_config_dict(): return ds_config_dict -def pretrain(train_valid_test_dataset_provider, - model_provider, - model_type, - forward_step_func, - process_non_loss_data_func=None, - extra_args_provider=None, - args_defaults={}, - data_post_process=None, - external_args={}): +def pretrain( + train_valid_test_dataset_provider, + model_provider, + model_type, + forward_step_func, + process_non_loss_data_func=None, + extra_args_provider=None, + args_defaults={}, + data_post_process=None, + external_args={}, +) -> torch.nn.Module: """Main training program. This function will run the followings in the order provided: @@ -149,6 +151,9 @@ def pretrain(train_valid_test_dataset_provider, to it. It is used for programs to add their own arguments. args_defaults: a dictionary from argument-name to argument-value. It to set already parse arguments. + + Returns: + model (torch.nn.Module) """ # Initalize and get arguments, timers, and Tensorboard writer. From 7794fc07fe74fcdecc53fa1061e69d2eb8084e6b Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 10:02:20 -0500 Subject: [PATCH 166/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index a91217afa6..f5061bf5b2 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -571,18 +571,21 @@ def main(): model_provider, ModelType.encoder_or_decoder, forward_step, - args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + # args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, data_post_process=data_post_process ) - - prof.export_chrome_trace(f"{args.tensorboard_dir}/torch-trace-{RANK}-of-{WORLD_SIZE}.json") + args = get_args() + prof.export_chrome_trace( + f"{args.tensorboard_dir}" + "/torch-trace-{RANK}-of-{WORLD_SIZE}.json" + ) else: model = pretrain( train_valid_test_datasets_provider, model_provider, ModelType.encoder_or_decoder, forward_step, - args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, + # args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, data_post_process=data_post_process ) return model From 590630e79e2895452a908b73b3f37678484ef773 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 4 Apr 2024 11:13:02 -0500 Subject: [PATCH 167/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index ee97709ef4..bb612def4a 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -44,6 +44,7 @@ function setDSlauncher() { } setParams() { + LLAMA_ARGS="" # ---- [Parallelism Settings] -------------------------------------------- # -------- [Aurora] ---- || ----- [SunSpot] ------------ if [[ $(hostname) == x4* || $(hostname) == x1* ]]; then @@ -53,6 +54,9 @@ setParams() { export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 export WORKING_DIR="${PBS_O_WORKDIR}" + if [[ -z "${NO_FLASH_ATTN}" ]]; then + LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn" + fi # -------- [Polaris] ----------------------------------- elif [[ $(hostname) == x3* ]]; then TP=${TP:-2} # TP = 2 @@ -62,6 +66,9 @@ setParams() { export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 export WORKING_DIR="${PBS_O_WORKDIR}" + if [[ -z "${NO_FLASH_ATTN}" ]]; then + LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" + fi # -------- [Perlmutter] --------------------------------- elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then TP="${TP:-2}" @@ -70,6 +77,9 @@ setParams() { export DTYPE="${DTYPE:-bf16}" MICRO_BATCH="${MICRO_BATCH:-8}" export WORKING_DIR="${SLURM_SUBMIT_DIR}" + if [[ -z "${NO_FLASH_ATTN}" ]]; then + LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" + fi fi # ------------------------------------------------------------------------ export TP="${TP}" @@ -101,10 +111,7 @@ setParams() { tm="${WORKING_DIR}/ALCF/tokenizer.model" export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" - export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" - if [[ -z "${NO_FLASH_ATTN}" ]]; then - export LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" - fi + export LLAMA_ARGS="${LLAMA_ARGS} --no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" # ---------------------------------------------------- } From d03aac040e93045fe9b68c516e9528676a2c39e3 Mon Sep 17 00:00:00 2001 From: Varuni Sastry <88804132+vksastry@users.noreply.github.com> Date: Mon, 8 Apr 2024 11:19:47 -0500 Subject: [PATCH 168/268] Update README.md with data preprocessing info and links. --- ALCF/README.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/ALCF/README.md b/ALCF/README.md index 1a8612ed8a..d95c70125d 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -196,3 +196,14 @@ modules and launch # [...] ```
+ +### Data Preprocessing + +AuroraGPT is trained on the Dolma dataset (initially v0), now in the process of moving to v6. For more details on the dataset, refer to https://huggingface.co/datasets/allenai/dolma. The dolma dataset downloaded is already preprocessing to remove the duplicates (dedup) and filtering the data (mixing). For more details refer to https://github.com/allenai/dolma/tree/main/docs and https://github.com/vksastry/dolma_alcf/blob/main/ALCF/Readme.md. + +The data preprocessing of Dolma dataset before training consists of tokenization of the data using a specific tokenizer (LlamaTokenizer is what we are currently using), Use the below script to tokenize the entire dataset. Example shown for Polaris. + +``` bash +cd /eagle/datasets/dolma/utils +./tokenization.sh +``` From c72914f65ad8542eebc612da19a37dc2ad42651f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 16 Apr 2024 11:59:36 -0500 Subject: [PATCH 169/268] Update `megatron/core/tensor_parallel/cross_entropy.py` --- megatron/core/tensor_parallel/cross_entropy.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/megatron/core/tensor_parallel/cross_entropy.py b/megatron/core/tensor_parallel/cross_entropy.py index 9dcdc0459f..d0453d25ea 100644 --- a/megatron/core/tensor_parallel/cross_entropy.py +++ b/megatron/core/tensor_parallel/cross_entropy.py @@ -69,14 +69,14 @@ def forward(ctx, vocab_parallel_logits, target, label_smoothing=0.0): vocab_size = exp_logits.size(-1) if label_smoothing > 0: - """ + r""" We'd like to assign 1 / (K - 1) probability mass to every index that is not the ground truth. = (1 - alpha) * y_gt + alpha * mean(y_{i for i != gt}) = (1 - alpha) * y_gt + (alpha / (K - 1)) * \sum_{i != gt} y_i = ((K - 1) * (1 - alpha) / (K - 1)) * y_gt + (alpha / (K - 1)) * \sum_{i != gt} y_i = (K * (1 - alpha) - 1) / (K - 1)) * y_gt + (alpha / (K - 1)) * \sum_{i} y_i = (1 - (alpha * K) / (K - 1)) * y_gt + ( (alpha * K) / (K - 1) ) * \sum_{i} y_i / K - From: https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/common/losses/smoothed_cross_entropy.py + From: """ assert 1.0 > label_smoothing > 0.0 smoothing = label_smoothing * vocab_size / (vocab_size - 1) From 7848cd49c70592432c46910a0efb5d01ace2b430 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 16 Apr 2024 12:00:47 -0500 Subject: [PATCH 170/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 17 +++++++++++++++-- 1 file changed, 15 insertions(+), 2 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index f5061bf5b2..46036efbad 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -94,8 +94,8 @@ def model_provider(pre_process=True, post_process=True): # wandb.run.config.update({'args': vars(args)}) if RANK == 0: git_ds_info() - if hasattr(mpu, 'get_sequence_parallel_group'): - dpg = mpu.get_sequence_parallel_group() + if hasattr(mpu, 'get_sequence_data_parallel_group'): + dpg = mpu.get_sequence_data_parallel_group() elif hasattr(mpu, 'get_data_parallel_group'): dpg = mpu.get_data_parallel_group() else: @@ -154,6 +154,7 @@ def model_provider(pre_process=True, post_process=True): pre_process=pre_process, post_process=post_process ) + num_params = sum(p.numel() for p in model.parameters() if p.requires_grad) # print_rank_0('\n ------------------------ ') # print_rank_0(f'num of parameters {num_params}') @@ -588,6 +589,18 @@ def main(): # args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, data_post_process=data_post_process ) + try: + from megatron.text_generation import generate_and_post_process + import ezpz as ez + with torch.autocast(device_type=ez.get_torch_device(), dtype=torch.float16): + response, _, _, _ = generate_and_post_process(model, prompts=["Hello world", "Nature is", "Turing test comprises", "Explain solar eclipse"], tokens_to_generate=32) + if RANK == 0: + log.info(f'generation completed..\n response:{response}') + except ValueError as ve: + log.critical(f'ValueError: {ve}') + pass + # dist.barrier() + model.train() return model From f2b82b964beba5eac36be836a2a185a3515baf0a Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 16 Apr 2024 12:01:16 -0500 Subject: [PATCH 171/268] Removes old `train_sbatch_pp64.sh` --- train_sbatch_pp64.sh | 34 ---------------------------------- 1 file changed, 34 deletions(-) delete mode 100755 train_sbatch_pp64.sh diff --git a/train_sbatch_pp64.sh b/train_sbatch_pp64.sh deleted file mode 100755 index b7baf2539e..0000000000 --- a/train_sbatch_pp64.sh +++ /dev/null @@ -1,34 +0,0 @@ -#!/bin/bash --login -#SBATCH -A m3957_g -#SBATCH -C 'gpu&hbm80g' -#SBATCH -q regular -#SBATCH -t 00:30:00 -#SBATCH --nodes 128 -#SBATCH --gpus 512 - - -# TODO:: -# - Add logic for catching / killing hung process at end of run to ensure -# second run starts up (otherwise, it will wait for the hung process, which -# will run until the job is killed) -# - This wll let us try running multiple experiments in a single slurm job -# allocation. -# - Existing (similar implementation) from my `~/bin/kill-match`: -# ```bash -# #!/bin/bash --login -# TO_KILL=$1 -# kill $(ps aux | grep -E "$USER.+($TO_KILL)" | grep -v grep | awk '{print $2}') - - -PPSIZE=64 \ - MODEL_SIZE_KEY="GPT1T_$(( 2 * PPSIZE ))L" \ - SEQ_LEN=2048 \ - MICRO_BATCH=2 \ - GAS=$(( 8 * PPSIZE )) \ - SP_TYPE=megatron \ - ZERO_STAGE=1 \ - USE_SEQUENCE_PARALLEL=0 \ - MPSIZE=8 \ - SPSIZE=1 \ - USE_ACTIVATION_CHECKPOINTING=1 \ - ./ALCF/train-gpt3.sh From 5c3b5b7f98a2e09d75160d03a61a5e67ecba9ed1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 16 Apr 2024 15:36:24 -0500 Subject: [PATCH 172/268] Update `generate_config.sh` --- generate_config.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/generate_config.sh b/generate_config.sh index d5b1264219..b164b5e610 100644 --- a/generate_config.sh +++ b/generate_config.sh @@ -50,7 +50,7 @@ common="\ flops_profiler="\ \"flops_profiler\": { \"enabled\": true, - \"profile_step\": 45, + \"profile_step\": 4, \"module_depth\": -1, \"top_modules\": 1, \"detailed\": true, From 4e5c38321ca8d099b8bdad6fb0d47c54febd483e Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 16 Apr 2024 15:37:56 -0500 Subject: [PATCH 173/268] Add support for `schedulefree.{AdamWScheduleFree,SGDScheduleFree}` --- megatron/arguments.py | 10 +++- megatron/optimizer/__init__.py | 94 +++++++++++++++++++--------------- megatron/training.py | 43 +++++++++++----- 3 files changed, 94 insertions(+), 53 deletions(-) diff --git a/megatron/arguments.py b/megatron/arguments.py index 994a727ec3..5f9b6f4144 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -916,7 +916,15 @@ def _add_training_args(parser): help='Disable bias in the linear layers', dest='add_bias_linear') group.add_argument('--optimizer', type=str, default='adam', - choices=['adam', 'adamw', 'sgd', 'apex.adam', 'apex.sgd'], + choices=[ + 'adam', + 'adamw', + 'sgd', + 'apex.adam', + 'apex.sgd', + 'adamwschedulefree', + 'sgdschedulefree' + ], help='Optimizer function') group.add_argument('--dataloader-type', type=str, default=None, choices=['single', 'cyclic'], diff --git a/megatron/optimizer/__init__.py b/megatron/optimizer/__init__.py index cdcc344541..fdaa1f7dc7 100644 --- a/megatron/optimizer/__init__.py +++ b/megatron/optimizer/__init__.py @@ -87,8 +87,22 @@ def get_megatron_optimizer(model, weight_decay=args.weight_decay, betas=(args.adam_beta1, args.adam_beta2), eps=args.adam_eps) - else: - if str(args.optimizer).lower() == 'apex.adam': + elif str(args.optimizer).lower() == 'adamwschedulefree': + import schedulefree + optimizer = schedulefree.AdamWScheduleFree( + param_groups, + lr=args.lr, + warmup_steps=args.lr_warmup_iters, + ) + elif str(args.optimizer).lower() == 'sgdschedulefree': + import schedulefree + optimizer = schedulefree.SGDScheduleFree( + param_groups, + lr=args.lr, + warmup_steps=args.lr_warmup_iters, + ) + # else: + elif str(args.optimizer).lower() == 'apex.adam': assert get_accelerator().device_name() == 'cuda' from apex.optimizers import FusedAdam as Adam optimizer = Adam( @@ -98,45 +112,45 @@ def get_megatron_optimizer(model, betas=(args.adam_beta1, args.adam_beta2), eps=args.adam_eps ) - elif str(args.optimizer).lower() == 'apex.sgd': - from apex.optimizers import FusedSGD as SGD - optimizer = SGD( - param_groups, - lr=args.lr, - weight_decay=args.weight_decay, - momentum=args.sgd_momentum - ) - elif str(args.optimizer).lower() == 'adamw': - optimizer = torch.optim.AdamW( - param_groups, - lr=args.lr, - weight_decay=args.weight_decay, - betas=(args.adam_beta1, args.adam_beta2), - eps=args.adam_eps - ) - elif args.optimizer == 'adam': - if args.ds_fused_adam: - # global Adam - from deepspeed.ops.adam import FusedAdam - Adam = FusedAdam - else: - Adam = torch.optim.Adam - optimizer = Adam( - param_groups, - lr=args.lr, - weight_decay=args.weight_decay, - betas=(args.adam_beta1, args.adam_beta2), - eps=args.adam_eps - ) - elif args.optimizer == 'sgd': - optimizer = torch.optim.SGD( - param_groups, - lr=args.lr, - weight_decay=args.weight_decay, - momentum=args.sgd_momentum - ) + elif str(args.optimizer).lower() == 'apex.sgd': + from apex.optimizers import FusedSGD as SGD + optimizer = SGD( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + momentum=args.sgd_momentum + ) + elif str(args.optimizer).lower() == 'adamw': + optimizer = torch.optim.AdamW( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps + ) + elif args.optimizer == 'adam': + if args.ds_fused_adam: + # global Adam + from deepspeed.ops.adam import FusedAdam + Adam = FusedAdam else: - raise TypeError(f'{args.optimizer} optimizer is not supported.') + Adam = torch.optim.Adam + optimizer = Adam( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps + ) + elif args.optimizer == 'sgd': + optimizer = torch.optim.SGD( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + momentum=args.sgd_momentum + ) + else: + raise TypeError(f'{args.optimizer} optimizer is not supported.') if args.deepspeed: return optimizer diff --git a/megatron/training.py b/megatron/training.py index e4b2511767..634713eafb 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -1018,18 +1018,37 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, opt_stats_2 = [0.0] * 4 for _, group in enumerate(optimizer.param_groups): for _, param in enumerate(group['params']): - opt_stats[0] += (torch.norm(optimizer.state[param]['exp_avg_sq']).item())**2 - opt_stats[1] += (torch.norm(optimizer.state[param]['exp_avg_sq'].sqrt()).item())**2 - opt_stats[2] += (torch.norm(optimizer.state[param]['exp_avg']).item())**2 - opt_stats[3] += (torch.norm(param).item())**2 - opt_stats[4] += torch.norm(optimizer.state[param]['exp_avg_sq'],p=1).item() - opt_stats[5] += torch.norm(optimizer.state[param]['exp_avg_sq'].sqrt(),p=1).item() - opt_stats[6] += torch.norm(optimizer.state[param]['exp_avg'],p=1).item() - opt_stats[7] += torch.norm(param,p=1).item() - opt_stats_2[0] = max(opt_stats_2[0], abs(optimizer.state[param]['exp_avg_sq'].max().item()), abs(optimizer.state[param]['exp_avg_sq'].min().item())) - opt_stats_2[1] = max(opt_stats_2[1], optimizer.state[param]['exp_avg_sq'].sqrt().abs_().max().item()) - opt_stats_2[2] = max(opt_stats_2[2], abs(optimizer.state[param]['exp_avg'].max().item()), abs(optimizer.state[param]['exp_avg'].min().item())) - opt_stats_2[3] = max(opt_stats_2[3], abs(param.max().item()), abs(param.min().item())) + state_param = getattr(optimizer, 'state', None) + if state_param is not None: + exp_avg_sq = state_param.get('exp_avg_sq', torch.tensor(0.)) + exp_avg = state_param.get('exp_avg', torch.tensor(0.)) + opt_stats[0] += (torch.norm(exp_avg_sq).item()) ** 2 + opt_stats[1] += (torch.norm(exp_avg_sq.sqrt()).item()) ** 2 + opt_stats[2] += (torch.norm(exp_avg).item()) ** 2 + opt_stats[3] += (torch.norm(param).item()) ** 2 + opt_stats[4] += torch.norm(exp_avg_sq, p=1).item() + opt_stats[5] += torch.norm(exp_avg_sq.sqrt(), p=1).item() + opt_stats[6] += torch.norm(exp_avg, p=1).item() + opt_stats[7] += torch.norm(param, p=1).item() + opt_stats_2[0] = max( + opt_stats_2[0], + abs(exp_avg_sq.max().item()), + abs(exp_avg_sq.min().item()) + ) + opt_stats_2[1] = max( + opt_stats_2[1], + exp_avg_sq.sqrt().abs_().max().item() + ) + opt_stats_2[2] = max( + opt_stats_2[2], + abs(exp_avg.max().item()), + abs(exp_avg.min().item()) + ) + opt_stats_2[3] = max( + opt_stats_2[3], + abs(param.max().item()), + abs(param.min().item()) + ) # print('step {} rank {} before sync opt_stats {}, {}'.format(iteration, torch.distributed.get_rank(), opt_stats_2, opt_stats)) if args.zero_stage > 0: # ZeRO partiions optimizer states From a68ed8ebaeef43b2d5bcb63d8e8da905f40b7284 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 16 Apr 2024 15:38:25 -0500 Subject: [PATCH 174/268] update `train_llama_alcf.sh` --- train_llama_alcf.sh | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index f0c939b9f7..ce18842850 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -47,6 +47,15 @@ export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit TBDIR="${CKPT_DIR}/tensorboard" mkdir -p "${TBDIR}" +# TORCH_DEVICE=$(python3 -c 'import ezpz as ez; print(ez.get_torch_device())') +# printf %s "Using TORCH_DEVICE=${TORCH_DEVICE}" +# +# if [[ "${TORCH_DEVICE}" == "cuda" ]]; then +# printf %s "Setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True" +# PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True +# fi + + # source "${HERE}/venvs/polaris/2024-03-14/bin/activate" || exit # echo "Using $(which python3)" # --launcher_args='--pmi=pmix' @@ -55,6 +64,9 @@ mkdir -p "${TBDIR}" # --use-flash-attn-v2 \ # --num-workers 0 \ + # aprun -n "${NGPUS}" -N "${NGPU_PER_HOST}" --pmi=pmix ${PBS_O_WORKDIR}/local_rank.sh + # ${DIST_LAUNCH} $(which python3) ${EXEC} \ +# yeet="${DIST_LAUNCH} ./local_rank.sh" run_cmd=" deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ --$DTYPE \ From a70aa6e95b8c9e24a86c59f6f9401828f7c49aaf Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 16 Apr 2024 15:38:49 -0500 Subject: [PATCH 175/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 28 +++++++++++++--------------- 1 file changed, 13 insertions(+), 15 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 46036efbad..0139330277 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -36,34 +36,33 @@ import time from torch import nn import torch.nn.functional as F +import ezpz as ez -# from ezpz import get_logger -from ezpz.dist import get_world_size, setup_wandb, get_rank -# RANK = setup_torch( +# ---- SETUP DISTRIBUTED COMMS ---- +# RANK = ez.setup_torch( # backend='deepspeed', # port='5432', # ) +RANK = ez.get_rank() +WORLD_SIZE = ez.get_world_size() +DEVICE = ez.get_torch_device() + +# --- TURN OFF LOGGER ON ALL RANK != 0 ---- log = get_logger(__name__) -RANK = get_rank() -WORLD_SIZE = get_world_size() -LEVEL = "DEBUG" if RANK == 0 else "CRITICAL" +log.setLevel("INFO") if RANK == 0 else log.setLevel("CRITICAL") +# ---- SETUP WANDB FROM RANK 0 ---------------- WANDB_MODE = os.environ.get('WANDB_MODE', None) DISABLE_WANDB = ( WANDB_MODE is not None and str(WANDB_MODE).lower() == 'disabled' ) -if RANK == 0: - log.setLevel("INFO") -else: - log.setLevel("CRITICAL") - if RANK == 0 and not DISABLE_WANDB: project_name = ( os.environ.get( - 'WB_PROJECT', + 'WB_PROJECT', # look for WB_PROJECT in env os.environ.get( - 'WANDB_PROJECT', + 'WANDB_PROJECT', # look for WANDB_PROJECT in env 'AuroraGPT' ), ) @@ -71,7 +70,7 @@ print('--------------------------------------------------') print(f"Setting up W&B from: {RANK} with {project_name}") print('--------------------------------------------------') - setup_wandb(project_name=project_name) + ez.setup_wandb(project_name=project_name) def model_provider(pre_process=True, post_process=True): @@ -591,7 +590,6 @@ def main(): ) try: from megatron.text_generation import generate_and_post_process - import ezpz as ez with torch.autocast(device_type=ez.get_torch_device(), dtype=torch.float16): response, _, _, _ = generate_and_post_process(model, prompts=["Hello world", "Nature is", "Turing test comprises", "Explain solar eclipse"], tokens_to_generate=32) if RANK == 0: From 1de3c662eb2302dc99290cfd80cf80055469c811 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 17 Apr 2024 08:05:53 -0500 Subject: [PATCH 176/268] Fix checkpointing with `schedulefree.*` optimizers --- ALCF/helpers.sh | 5 ++- megatron/checkpointing.py | 88 +++++++++++++++++++++++++++++++++++++-- megatron/training.py | 64 ++++++++++++++++------------ 3 files changed, 126 insertions(+), 31 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index bb612def4a..cd04f890b9 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -178,7 +178,7 @@ saveDSenv() { setOutput() { # ---- Specify output location -------------------------------- - export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" + export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" export OUTPUT_DIR="${OUTPUT_DIR}" export OUTPUT_LOG="${OUTPUT_DIR}/output.log" @@ -235,6 +235,9 @@ setEnv() { echo "Running on Polaris !!" # ---- [load conda] --------------------- module load conda/2023-10-04; conda activate cu118-pt221 ; unset PYTHONUSERBASE + if [[ -d "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221" ]]; then + source "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221/bin/activate" + fi elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then echo "Running on Perlmutter !!" module load pytorch diff --git a/megatron/checkpointing.py b/megatron/checkpointing.py index 3e4d20035e..04201fcc06 100644 --- a/megatron/checkpointing.py +++ b/megatron/checkpointing.py @@ -8,6 +8,12 @@ import numpy as np from deepspeed.accelerator import get_accelerator import torch +import ezpz as ez +import logging +import torch.distributed as tdist + +import yaml +from pathlib import Path from megatron import update_num_microbatches, get_tokenizer from megatron.core import mpu, tensor_parallel @@ -24,6 +30,12 @@ UNIVERSAL_CHECKPOINT_VERSION_VALUE, ) +RANK = ez.get_rank() +WORLD_SIZE = ez.get_world_size() +DEVICE = ez.get_torch_device() +log = logging.getLogger(__name__) +log.setLevel("INFO") if RANK == 0 else log.setLevel("CRITICAL") + _CHECKPOINT_VERSION = None @@ -225,6 +237,10 @@ def get_rng_state(): def save_checkpoint(iteration, model, optimizer, opt_param_scheduler): """Save a model checkpoint.""" args = get_args() + assert args is not None + iteration = args.iteration + + save_lr_state_dict() # Only rank zero of the data parallel writes to the disk. if not args.deepspeed: @@ -529,15 +545,81 @@ def _set_arg(arg_name, old_arg_name=None, force=False): return args, checkpoint_args -def load_checkpoint(model, optimizer, opt_param_scheduler, load_arg='load', strict=True, load_only_weights=False): +def load_lr_state_dict(strict: bool = False) -> dict: + """Load {iteration, lr} from .yaml file when restoring from checkpoint.""" + args = get_args() + assert args is not None + lr_state_dict_fp = Path(args.load).joinpath( + f"lr_state_dict_{RANK}_of_{WORLD_SIZE}.yaml" + ) + lr_state_dict = {} + if lr_state_dict_fp.is_file(): + with lr_state_dict_fp.open('r') as f: + lr_state_dict = yaml.safe_load(f) + args.lr = lr_state_dict['lr'] + else: + if strict: + raise FileNotFoundError( + f"{lr_state_dict_fp=}.is_file() is False" + ) + log.info( + f"Unable to load lr_state_dict from {lr_state_dict_fp=}, " + f"but strict=False. Returning empty dictionary: {lr_state_dict=}" + ) + return lr_state_dict + + +def save_lr_state_dict() -> None: + """Save {iteration, lr} to .yaml file for safe-keeping. + + Make sure we're only saving from RANK == 0. + """ + if RANK != 0: + return None + args = get_args() + assert args is not None + outdir = getattr(args, 'save', None) + assert outdir is not None + lr_state_dict_fp = Path(args.save).joinpath( + "lr_state_dict.yaml" + ) + log.info(f"Saving lr_state_dict to {lr_state_dict_fp.as_posix()}") + with lr_state_dict_fp.open('w') as f: + yaml.dump( + {'iteration': args.iteration, 'lr': args.lr}, + f + ) + + +def load_checkpoint( + model, + optimizer, + opt_param_scheduler, + load_arg: str = 'load', + strict: bool = True, + load_only_weights: bool = False, + strict_lr_state_dict: bool = False +): """Load a model checkpoint and return the iteration. strict (bool): whether to strictly enforce that the keys in :attr:`state_dict` of the checkpoint match the names of parameters and buffers in model. """ args = get_args() + assert args is not None load_dir = getattr(args, load_arg) - + if RANK == 0: + lr_state_dict = load_lr_state_dict(strict=strict_lr_state_dict) + lr_tensor = torch.tensor( + lr_state_dict['lr'], + requires_grad=False, + device=DEVICE + ) + else: + lr_state_dict = {} + lr_tensor = torch.tensor(0., requires_grad=False, device=DEVICE) + tdist.broadcast(lr_tensor, 0) + args.lr = lr_tensor.item() if args.deepspeed: if args.finetune: loaded_dir, state_dict = model[0].load_checkpoint(load_dir, @@ -553,7 +635,7 @@ def load_checkpoint(model, optimizer, opt_param_scheduler, load_arg='load', stri print_rank_0(' will not load any checkpoints and will start from ' 'random') return 0 - release = False + release = False else: model = unwrap_model(model) diff --git a/megatron/training.py b/megatron/training.py index 634713eafb..c02ca8d0ef 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -10,6 +10,7 @@ # The earliest we can measure the start time. _TRAIN_START_TIME = time.time() import torch +import torch.distributed as tdist from collections import OrderedDict from torch.nn.parallel.distributed import DistributedDataParallel as torchDDP @@ -49,9 +50,16 @@ from deepspeed.compression.compress import init_compression, redundancy_clean from deepspeed.runtime.data_pipeline.data_routing.helper import convert_to_random_ltd from megatron.model.transformer import ParallelTransformerLayer +import ezpz as ez +import logging from deepspeed import comm as dist +RANK = ez.get_rank() +WORLD_SIZE = ez.get_world_size() +log = logging.getLogger(__name__) +log.setLevel("INFO") if RANK == 0 else log.setLevel("CRITICAL") + try: import wandb except (ImportError, ModuleNotFoundError): @@ -60,9 +68,9 @@ def print_datetime(string): """Note that this call will sync across all ranks.""" - torch.distributed.barrier() + tdist.barrier() time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') - print_rank_0('[' + string + '] datetime: {} '.format(time_str)) + log.info('[' + string + '] datetime: {} '.format(time_str)) def num_floating_point_operations(args, batch_size): @@ -169,10 +177,11 @@ def pretrain( # image ... launches. global _TRAIN_START_TIME start_time_tensor = get_accelerator().DoubleTensor([_TRAIN_START_TIME]) - torch.distributed.all_reduce(start_time_tensor, - op=torch.distributed.ReduceOp.MIN) + tdist.all_reduce(start_time_tensor, op=tdist.ReduceOp.MIN) + # torch.distributed.all_reduce(start_time_tensor, + # op=torch.distributed.ReduceOp.MIN) _TRAIN_START_TIME = start_time_tensor.item() - print_rank_0('time to initialize megatron (seconds): {:.3f}'.format( + log.info('time to initialize megatron (seconds): {:.3f}'.format( time.time() - _TRAIN_START_TIME)) print_datetime('after megatron is initialized') @@ -247,16 +256,16 @@ def pretrain( args.teacher_model = setup_teacher_model(args, model_provider) # Print setup timing. - print_rank_0('done with setup ...') + log.info('done with setup ...') timers.log(['model-and-optimizer-setup', 'train/valid/test-data-iterators-setup'], barrier=True) if not args.skip_train: - print_rank_0('training ...') + log.info('training ...') if args.dataloader_type == 'cyclic' and args.retro_add_retriever: args.train_iters = args.retro_cyclic_train_iters - print_rank_0("retro cyclic train iters : %d" % args.train_iters) + log.info("retro cyclic train iters : %d" % args.train_iters) iteration = 0 if args.do_train and args.train_iters > 0: @@ -273,7 +282,7 @@ def pretrain( if args.save and iteration != 0: save_checkpoint(iteration, model, optimizer, opt_param_scheduler) else: - print_rank_0('skipping training (--skip-train is on) ...') + log.info('skipping training (--skip-train is on) ...') iteration = args.iteration @@ -321,12 +330,12 @@ def update_train_iters(args): args.global_batch_size args.train_iters = iterations - print_rank_0('setting training iterations to {}'.format(args.train_iters)) + log.info('setting training iterations to {}'.format(args.train_iters)) def setup_teacher_model(args, model_provider): - print_rank_0('***>>>>> Student model checkpoint iteration:{}'.format(args.iteration)) + log.info('***>>>>> Student model checkpoint iteration:{}'.format(args.iteration)) iteration_stuent = args.iteration num_layers_student = args.num_layers num_experts_student = args.num_experts @@ -334,7 +343,7 @@ def setup_teacher_model(args, model_provider): num_attention_heads_student = args.num_attention_heads load_student = args.load - print_rank_0('***>>>>> Setting up the teacher model') + log.info('***>>>>> Setting up the teacher model') args.num_layers = args.num_layers_teacher args.num_experts = args.num_experts_teacher @@ -342,7 +351,7 @@ def setup_teacher_model(args, model_provider): args.num_attention_heads = args.num_attention_heads_teacher args.load = args.load_teacher teacher_model, _, _ = load_model_weights_only(model_provider) - print_rank_0('***>>>>> Teacher model:{}'.format(teacher_model)) + log.info('***>>>>> Teacher model:{}'.format(teacher_model)) args.num_layers = num_layers_student args.num_experts = num_experts_student @@ -518,7 +527,7 @@ def get_optimizer_param_scheduler(optimizer): def load_model_weights_only(model_provider_func): """Setup model and optimizer.""" args = get_args() - print_rank_0('***>>>>> Args:{}'.format(args)) + log.info('***>>>>> Args:{}'.format(args)) model = get_model(model_provider_func) @@ -577,7 +586,7 @@ def setup_model_and_optimizer(model_provider_func, else: args.iteration = 0 student_global_steps = model[0].global_steps - print_rank_0('***>>>>> Student model, global step:{}'.format(student_global_steps)) + log.info('***>>>>> Student model, global step:{}'.format(student_global_steps)) if args.compression_training: model, _, _, _ = deepspeed.initialize( @@ -605,7 +614,7 @@ def setup_model_and_optimizer(model_provider_func, opt_param_scheduler = get_optimizer_param_scheduler(optimizer) if args.deepspeed: - print_rank_0("DeepSpeed is enabled.") + log.info("DeepSpeed is enabled.") pp = mpu.get_pipeline_model_parallel_world_size() if args.data_efficiency_curriculum_learning and build_train_valid_test_datasets_provider is not None: train_ds = None @@ -681,7 +690,7 @@ def setup_model_and_optimizer(model_provider_func, # get model without FP16 and/or TorchDDP wrappers if args.iteration == 0 and len(unwrapped_model) == 1 \ and hasattr(unwrapped_model[0], 'init_state_dict_from_bert'): - print_rank_0("Initializing ICT from pretrained BERT model") + log.info("Initializing ICT from pretrained BERT model") unwrapped_model[0].init_state_dict_from_bert() if args.fp16: optimizer.reload_model_params() @@ -1238,7 +1247,8 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, total_loss_dict[advanced_iters_key] = 0 total_loss_dict[skipped_iters_key] = 0 total_loss_dict[nan_iters_key] = 0 - print_rank_last(log_string) + # print_rank_last(log_string) + log.info(log_string) if report_memory_flag and learning_rate > 0.: # Report memory after optimizer state has been initialized. report_memory('(after {} iterations)'.format(iteration)) @@ -1465,7 +1475,7 @@ def evaluate(forward_step_func, while iteration < args.eval_iters: iteration += 1 if verbose and iteration % args.log_interval == 0: - print_rank_0('Evaluating iter {}/{}'.format(iteration, + log.info('Evaluating iter {}/{}'.format(iteration, args.eval_iters)) forward_backward_func = get_forward_backward_func() @@ -1576,9 +1586,9 @@ def evaluate_and_print_results(prefix, forward_step_func, process_non_loss_data_func(collected_non_loss_data, iteration, writer) length = len(string) + 1 - print_rank_last('-' * length) - print_rank_last(string) - print_rank_last('-' * length) + log.info('-' * length) + log.info(string) + log.info('-' * length) def cyclic_iter(iter): @@ -1603,10 +1613,10 @@ def build_train_valid_test_datasets(build_train_valid_test_datasets_provider): train_val_test_num_samples = [train_samples, eval_iters * args.global_batch_size, test_iters * args.global_batch_size] - print_rank_0(' > datasets target sizes (minimum size):') - print_rank_0(' train: {}'.format(train_val_test_num_samples[0])) - print_rank_0(' validation: {}'.format(train_val_test_num_samples[1])) - print_rank_0(' test: {}'.format(train_val_test_num_samples[2])) + log.info(' > datasets target sizes (minimum size):') + log.info(' train: {}'.format(train_val_test_num_samples[0])) + log.info(' validation: {}'.format(train_val_test_num_samples[1])) + log.info(' test: {}'.format(train_val_test_num_samples[2])) # Build the datasets. return build_train_valid_test_datasets_provider(train_val_test_num_samples) @@ -1620,7 +1630,7 @@ def build_train_valid_test_data_loaders( (train_dataloader, valid_dataloader, test_dataloader) = (None, None, None) - print_rank_0('> building train, validation, and test datasets ...') + log.info('> building train, validation, and test datasets ...') # Backward compatibility, assume fixed batch size. if args.iteration > 0 and args.consumed_train_samples == 0: From aa2cd591cec5a355b59abd5ec248aed1f462f79f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 17 Apr 2024 08:24:58 -0500 Subject: [PATCH 177/268] Fix checkpointing with `schedulefree.*` optimizers --- megatron/checkpointing.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/megatron/checkpointing.py b/megatron/checkpointing.py index 04201fcc06..d585baf717 100644 --- a/megatron/checkpointing.py +++ b/megatron/checkpointing.py @@ -608,16 +608,16 @@ def load_checkpoint( args = get_args() assert args is not None load_dir = getattr(args, load_arg) + lr_state_dict = {} + lr_tensor = torch.tensor(args.lr, requires_grad=False, device=DEVICE) if RANK == 0: lr_state_dict = load_lr_state_dict(strict=strict_lr_state_dict) - lr_tensor = torch.tensor( - lr_state_dict['lr'], - requires_grad=False, - device=DEVICE - ) - else: - lr_state_dict = {} - lr_tensor = torch.tensor(0., requires_grad=False, device=DEVICE) + if len(lr_state_dict.keys()) > 0 and 'lr' in lr_state_dict: + lr_tensor = torch.tensor( + lr_state_dict['lr'], + requires_grad=False, + device=DEVICE, + ) tdist.broadcast(lr_tensor, 0) args.lr = lr_tensor.item() if args.deepspeed: From a365a182a3f17edf90d59021088ef28855ead611 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 17 Apr 2024 09:03:41 -0500 Subject: [PATCH 178/268] Add `--schedulefree-foreach` flag From https://github.com/facebookresearch/schedule_free/blob/6db4953ccde631baca5f5fd2d9e5cab21caf9ed4/schedulefree/adamw_schedulefree.py#L39 --- megatron/arguments.py | 35 +++++++++---- megatron/optimizer/__init__.py | 95 +++++++++++++++++++--------------- 2 files changed, 78 insertions(+), 52 deletions(-) diff --git a/megatron/arguments.py b/megatron/arguments.py index 5f9b6f4144..b982337f51 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -915,17 +915,30 @@ def _add_training_args(parser): group.add_argument('--disable-bias-linear', action='store_false', help='Disable bias in the linear layers', dest='add_bias_linear') - group.add_argument('--optimizer', type=str, default='adam', - choices=[ - 'adam', - 'adamw', - 'sgd', - 'apex.adam', - 'apex.sgd', - 'adamwschedulefree', - 'sgdschedulefree' - ], - help='Optimizer function') + group.add_argument( + '--optimizer', + type=str, + default='adam', + choices=[ + 'adam', + 'adamw', + 'sgd', + 'apex.adam', + 'apex.sgd', + 'adamwschedulefree', + 'sgdschedulefree' + ], + help='Optimizer function' + ) + group.add_argument( + "--schedulefree-for-each", + action="store_true", + help=""" + Use a foreach-backed implementation of the schedulefree optimizers. + Should be significantly faster, + but will have a higher peak memory usage. + """, + ) group.add_argument('--dataloader-type', type=str, default=None, choices=['single', 'cyclic'], help='Single pass vs multiple pass data loader') diff --git a/megatron/optimizer/__init__.py b/megatron/optimizer/__init__.py index fdaa1f7dc7..6dfd0ea40f 100644 --- a/megatron/optimizer/__init__.py +++ b/megatron/optimizer/__init__.py @@ -60,21 +60,29 @@ def get_param_groups(modules, return param_groups -def get_megatron_optimizer(model, - no_weight_decay_cond=None, - scale_lr_cond=None, - lr_mult=1.0): + +def get_megatron_optimizer( + model, + no_weight_decay_cond=None, + scale_lr_cond=None, + lr_mult=1.0 +): args = get_args() # Base optimizer. - param_groups = get_param_groups(model, - no_weight_decay_cond, - scale_lr_cond, - lr_mult) + param_groups = get_param_groups( + model, + no_weight_decay_cond, + scale_lr_cond, + lr_mult + ) if args.create_moe_param_group: - from deepspeed.moe.utils import split_params_into_different_moe_groups_for_optimizer - param_groups = split_params_into_different_moe_groups_for_optimizer(param_groups) - + from deepspeed.moe.utils import ( + split_params_into_different_moe_groups_for_optimizer + ) + param_groups = split_params_into_different_moe_groups_for_optimizer( + param_groups + ) if args.cpu_optimizer: assert args.optimizer == 'adam', 'CPU offloading is for Adam' if args.cpu_torch_adam: @@ -82,36 +90,44 @@ def get_megatron_optimizer(model, else: from deepspeed.ops.adam import DeepSpeedCPUAdam cpu_adam_optimizer = DeepSpeedCPUAdam - optimizer = cpu_adam_optimizer(param_groups, - lr=args.lr, - weight_decay=args.weight_decay, - betas=(args.adam_beta1, args.adam_beta2), - eps=args.adam_eps) + optimizer = cpu_adam_optimizer( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps, + ) elif str(args.optimizer).lower() == 'adamwschedulefree': import schedulefree optimizer = schedulefree.AdamWScheduleFree( param_groups, lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps, warmup_steps=args.lr_warmup_iters, + foreach=args.schedulefree_for_each, ) elif str(args.optimizer).lower() == 'sgdschedulefree': import schedulefree optimizer = schedulefree.SGDScheduleFree( param_groups, lr=args.lr, + momentum=args.sgd_momentum, + weight_decay=args.weight_decay, warmup_steps=args.lr_warmup_iters, + foreach=args.schedulefree_for_each, ) - # else: elif str(args.optimizer).lower() == 'apex.adam': - assert get_accelerator().device_name() == 'cuda' - from apex.optimizers import FusedAdam as Adam - optimizer = Adam( - param_groups, - lr=args.lr, - weight_decay=args.weight_decay, - betas=(args.adam_beta1, args.adam_beta2), - eps=args.adam_eps - ) + assert get_accelerator().device_name() == 'cuda' + from apex.optimizers import FusedAdam as Adam + optimizer = Adam( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps + ) elif str(args.optimizer).lower() == 'apex.sgd': from apex.optimizers import FusedSGD as SGD optimizer = SGD( @@ -153,18 +169,15 @@ def get_megatron_optimizer(model, raise TypeError(f'{args.optimizer} optimizer is not supported.') if args.deepspeed: return optimizer - # Determine whether the params have main-grad field. params_have_main_grad = False if args.use_contiguous_buffers_in_local_ddp: params_have_main_grad = True - # Mixed precision optimizer. # - Note: both the Float16Optimizer and the DistributedOptimizer inherit # from the MixedPrecisionOptimizer, which manages any optimizer where # the model params and main params are distinct. if args.fp16 or args.bf16 or args.use_distributed_optimizer: - # Grad scaler: # if loss-scale is provided, instantiate the constant scaler. # if we are using fp16 and loss-scale is not present, use a @@ -172,11 +185,9 @@ def get_megatron_optimizer(model, # otherwise we are running in bf16 with no loss-scale so # leave it as None. grad_scaler = None - # Constant loss scale. if args.loss_scale: grad_scaler = ConstantGradScaler(args.loss_scale) - # Dynamic loss scale. else: if args.fp16: @@ -187,11 +198,11 @@ def get_megatron_optimizer(model, backoff_factor=0.5, growth_interval=args.loss_scale_window, hysteresis=args.hysteresis) - # Megatron optimizer. - opt_ty = DistributedOptimizer \ - if args.use_distributed_optimizer else \ - Float16OptimizerWithFloat16Params + opt_ty = ( + DistributedOptimizer if args.use_distributed_optimizer + else Float16OptimizerWithFloat16Params + ) return opt_ty(optimizer, args.clip_grad, args.log_num_zeros_in_grad, @@ -202,10 +213,12 @@ def get_megatron_optimizer(model, args.params_dtype, grad_scaler, model) - # FP32. - return FP32Optimizer(optimizer, args.clip_grad, - args.log_num_zeros_in_grad, - params_have_main_grad, - args.use_contiguous_buffers_in_local_ddp, - model) + return FP32Optimizer( + optimizer, + args.clip_grad, + args.log_num_zeros_in_grad, + params_have_main_grad, + args.use_contiguous_buffers_in_local_ddp, + model + ) From eecf70d55ea4c8b46cb714bc127087aa645299aa Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 17 Apr 2024 09:05:16 -0500 Subject: [PATCH 179/268] Replace `{:.6E}` with `{:.6f}` in `log_string` formatting --- megatron/training.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/megatron/training.py b/megatron/training.py index c02ca8d0ef..43fd359ab0 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -1218,7 +1218,7 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, avg = total_loss_dict[key].item() / \ float(max(1, total_loss_dict[advanced_iters_key])) if avg > 0.0: - log_string += ' {}: {:.6E} |'.format(key, avg) + log_string += ' {}: {:.6f} |'.format(key, avg) total_loss_dict[key] = get_accelerator().FloatTensor([0.0]) if loss_scale is not None: log_string += ' loss scale: {:.1f} |'.format(loss_scale) From 6969dc2d09bc845e3982aa0fb416760830cca9c3 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 17 Apr 2024 11:06:11 -0500 Subject: [PATCH 180/268] Update `megatron/training.py` --- megatron/training.py | 45 ++++++++++++++++++++++---------------------- 1 file changed, 23 insertions(+), 22 deletions(-) diff --git a/megatron/training.py b/megatron/training.py index 43fd359ab0..67cd47bda1 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -70,7 +70,7 @@ def print_datetime(string): """Note that this call will sync across all ranks.""" tdist.barrier() time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') - log.info('[' + string + '] datetime: {} '.format(time_str)) + log.info('[' + string + '] datetime={} '.format(time_str)) def num_floating_point_operations(args, batch_size): @@ -181,7 +181,7 @@ def pretrain( # torch.distributed.all_reduce(start_time_tensor, # op=torch.distributed.ReduceOp.MIN) _TRAIN_START_TIME = start_time_tensor.item() - log.info('time to initialize megatron (seconds): {:.3f}'.format( + log.info('time to initialize megatron (seconds)={:.3f}'.format( time.time() - _TRAIN_START_TIME)) print_datetime('after megatron is initialized') @@ -435,7 +435,7 @@ def get_model(model_provider_func, model_type=ModelType.encoder_or_decoder, wrap # Print number of parameters. if mpu.get_data_parallel_rank() == 0: print(' > number of parameters on (tensor, pipeline) ' - 'model parallel rank ({}, {}): {}'.format( + 'model parallel rank ({}, {})={}'.format( mpu.get_tensor_model_parallel_rank(), mpu.get_pipeline_model_parallel_rank(), sum([sum([p.ds_numel if hasattr(p,'ds_id') else p.nelement() for p in model_module.parameters()]) @@ -1185,18 +1185,18 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, log_string = f' iteration {iteration:8d}/{args.train_iters:8d} |' # .format( iteration, args.train_iters) log_string += ( - f' consumed samples: {args.consumed_train_samples:12d} |' + f' consumed samples={args.consumed_train_samples:12d} |' # .format(args.consumed_train_samples) ) - log_string += f' consumed tokens: {args.consumed_train_tokens:12d} |' + log_string += f' consumed tokens={args.consumed_train_tokens:12d} |' # .format( args.consumed_train_tokens) log_string += ( ' elapsed time per iteration (ms): ' f'{elapsed_time_per_iteration * 1000.0:.1f} |' # .format( elapsed_time_per_iteration * 1000.0) ) - log_string += f' learning rate: {learning_rate:.3E} |' - log_string += f' global batch size: {batch_size:5d} |' + log_string += f' learning rate={learning_rate:.3f} |' + log_string += f' global batch size={batch_size:5d} |' # if wandb is not None and getattr(wandb, 'run', None) is not None: wandb_metrics |= { 'training/iteration': iteration, @@ -1218,32 +1218,32 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, avg = total_loss_dict[key].item() / \ float(max(1, total_loss_dict[advanced_iters_key])) if avg > 0.0: - log_string += ' {}: {:.6f} |'.format(key, avg) + log_string += ' {}={:.6f} |'.format(key, avg) total_loss_dict[key] = get_accelerator().FloatTensor([0.0]) if loss_scale is not None: - log_string += ' loss scale: {:.1f} |'.format(loss_scale) + log_string += ' loss scale={:.1f} |'.format(loss_scale) wandb_metrics |= {'loss/loss_scale': loss_scale} if grad_norm is not None: - log_string += ' grad norm: {:.3f} |'.format(grad_norm) + log_string += ' grad norm={:.3f} |'.format(grad_norm) wandb_metrics |= {'loss/grad_norm': grad_norm} if num_zeros_in_grad is not None: - log_string += ' num zeros: {:.1f} |'.format(num_zeros_in_grad) + log_string += ' num zeros={:.1f} |'.format(num_zeros_in_grad) wandb_metrics |= {'loss/num_zeros_in_grad': num_zeros_in_grad} if params_norm is not None: - log_string += ' params norm: {:.3f} |'.format(params_norm) + log_string += ' params norm={:.3f} |'.format(params_norm) wandb_metrics |= {'loss/params_norm': params_norm} if args.curriculum_learning_legacy or args.data_efficiency_curriculum_learning: - log_string += ' curriculum seqlen: {:5d} |'.format(args.curriculum_seqlen) + log_string += ' curriculum seqlen={:5d} |'.format(args.curriculum_seqlen) if args.random_ltd: - log_string += ' random ltd reserved length: {:5d} |'.format(args.random_ltd_reserved_length) - log_string += ' actual seqlen: {:5d} |'.format(seq_len) - log_string += ' number of skipped iterations: {:3d} |'.format( + log_string += ' random ltd reserved length={:5d} |'.format(args.random_ltd_reserved_length) + log_string += ' actual seqlen={:5d} |'.format(seq_len) + log_string += ' number of skipped iterations={:3d} |'.format( total_loss_dict[skipped_iters_key]) - log_string += ' number of nan iterations: {:3d} |'.format( + log_string += ' number of nan iterations={:3d} |'.format( total_loss_dict[nan_iters_key]) - log_string += ' samples per second: {:.3f} |'.format(samples_per_sec) - log_string += ' tokens per gpu per second (tgs): {:.3f} |'.format(tokens_per_gpu_per_second) - log_string += ' TFLOPs: {:.2f} |'.format(tflops) + log_string += ' samples per second={:.3f} |'.format(samples_per_sec) + log_string += ' tokens per gpu per second (tgs)={:.3f} |'.format(tokens_per_gpu_per_second) + log_string += ' TFLOPs={:.2f} |'.format(tflops) total_loss_dict[advanced_iters_key] = 0 total_loss_dict[skipped_iters_key] = 0 total_loss_dict[nan_iters_key] = 0 @@ -1560,9 +1560,10 @@ def evaluate_and_print_results(prefix, forward_step_func, process_non_loss_data_func, config, verbose) string = ' validation loss at {} | '.format(prefix) for key in total_loss_dict: - string += '{} value: {:.6E} | '.format(key, total_loss_dict[key].item()) + string += f"{key} value={total_loss_dict[key].item():.6f}" ppl = math.exp(min(20, total_loss_dict[key].item())) - string += '{} PPL: {:.6E} | '.format(key, ppl) + string += f"{key} PPL={ppl:.6f}" + # string += '{} PPL={:.6f} | '.format(key, ppl) if writer and is_last_rank(): data_type = 'test' if test else 'validation' writer.add_scalar(f'lm-loss-validation/{key} {data_type}', From 1d30d41dd33de0e26d9253e581120c10aa8c99c7 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 18 Apr 2024 08:39:03 -0500 Subject: [PATCH 181/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 63 ++++++++----------------------------------------- 1 file changed, 10 insertions(+), 53 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index cd04f890b9..151c3e857a 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -28,9 +28,6 @@ function setupSrun() { function setDSlauncher() { # launcher setting outdir=$1 - # hfds=$1 - # hfmpi=$2 - # here=$(python3 -c 'import os; print(os.getcwd())') export hfds="$outdir/hostfile_deepspeed" export hfmpi="$outdir/hostfile_mpich" [ -f "$hfds" ] || exit @@ -90,8 +87,8 @@ setParams() { export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} # ---- Llama2 7B Config ------------------------------ export MODEL_KEY="Llama-7B" - export HEADS=${HEADS:-32} - export NLAYERS=${NLAYERS:-32} + export HEADS=${HEADS:-${NHEADS:-32}} + export NLAYERS=${NLAYERS:-${NUM_LAYERS:-32}} export HIDDEN=${HIDDEN:-4096} export NUM_KV_HEAD=${NUM_KV_HEAD:-8} export FFN_HIDDEN_SIZE=${FFN_HIDDEN_SIZE:-11008} @@ -146,6 +143,10 @@ setArgs() { export gpt_args } +# +---------------------------------------+ +# | 1. Git clone `ezpz` (if not found) | +# | 2. Install `ezpz` (if not installed) | +# +---------------------------------------+ ezpz() { if [[ ! -d ezpz ]]; then git clone https://github.com/saforem2/ezpz @@ -164,6 +165,10 @@ ezpz() { # source ezpz/src/ezpz/bin/getjobenv || exit } +# +------------------------------------------------------------------------+ +# | Save important environment variables to .deepspeed_env, which will be | +# | forwarded to ALL ranks with DeepSpeed | +# +------------------------------------------------------------------------+ saveDSenv() { echo "Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env" { @@ -202,8 +207,6 @@ buildDSconfig() { sumWeights() { local file_list=$1 weights=$(cat "${file_list}" | awk '{print $1}' | tr '\n' '\ ,\ ' | sed 's/^/[/g' | sed 's/$/]/g' | tr '\ ' "\,\ ") - # weights=$(echo "$weights" | tr ",]" "]") - # echo "weights: $weights" python3 -c "import numpy as np; print(np.sum(${weights}))" } @@ -298,52 +301,6 @@ setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- echo "--------------------" } -# buildCLIargs() { # ---- [BROKEN] ------------------------------------------- -# custom_args=" $@" -# export CLI_ARGS=" -# --$DTYPE \ -# --num-workers 0 \ -# --split 100,0,0 \ -# --log-interval 1 \ -# --use-flash-attn-v2 \ -# --no-bias-gelu-fusion \ -# --lr-decay-style cosine \ -# --no-bias-dropout-fusion \ -# --no-masked-softmax-fusion \ -# --tokenizer-type Llama2Tokenizer \ -# --no-gradient-accumulation-fusion \ -# --accumulate-allreduce-grads-in-fp32 \ -# --use-checkpoint-opt_param-scheduler \ -# --lr ${LR} \ -# --save ${CKPT_DIR} \ -# --load ${CKPT_DIR} \ -# --seq-length ${SEQ} \ -# --num-layers ${NLAYERS} \ -# --hidden-size ${HIDDEN} \ -# --train-iters ${TRAIN_ITER} \ -# --eval-iters ${EVAL_ITERS} \ -# --distributed-backend ${BE} \ -# --num-attention-heads ${HEADS} \ -# --save-interval ${SAVE_INTERVAL} \ -# --eval-interval ${EVAL_INTERVAL} \ -# --max-position-embeddings ${SEQ} \ -# --micro-batch-size ${MICRO_BATCH} \ -# --data-file-list ${DATA_FILE_LIST} \ -# --tensor-model-parallel-size ${TP} \ -# --global-batch-size ${GLOBAL_BATCH} \ -# --pipeline-model-parallel-size ${PP} \ -# --num-key-value-heads ${NUM_KV_HEAD} \ -# --data-cache-path ${DATA_CACHE_PATH} \ -# --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ -# --tokenizer-model ${TOKENIZER_MODEL} \ -# $ds_args \ -# ${LLAMA_ARGS} \ -# ${gpt_args[*]} \ -# ${custom_args} \ -# " -# } - - printBlack() { printf "\e[1;30m%s\e[0m\n" "$@" } From 981b7d9896e4c416a842e3b3af09b3f36d46f889 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 18 Apr 2024 08:39:35 -0500 Subject: [PATCH 182/268] Update logging in `megatron/training.py` --- megatron/training.py | 34 +++++++++++++++++----------------- 1 file changed, 17 insertions(+), 17 deletions(-) diff --git a/megatron/training.py b/megatron/training.py index 67cd47bda1..2bdf61f908 100644 --- a/megatron/training.py +++ b/megatron/training.py @@ -1182,21 +1182,21 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, elapsed_time_per_iteration, args.consumed_train_samples) writer.add_scalar('iteration-time/iteration-time vs tokens', elapsed_time_per_iteration, args.consumed_train_tokens) - log_string = f' iteration {iteration:8d}/{args.train_iters:8d} |' + log_string = f' iteration={iteration:8d}/{args.train_iters:8d} |' # .format( iteration, args.train_iters) log_string += ( - f' consumed samples={args.consumed_train_samples:12d} |' + f' consumed_samples={args.consumed_train_samples:12d} |' # .format(args.consumed_train_samples) ) - log_string += f' consumed tokens={args.consumed_train_tokens:12d} |' + log_string += f' consumed_tokens={args.consumed_train_tokens:12d} |' # .format( args.consumed_train_tokens) log_string += ( - ' elapsed time per iteration (ms): ' + ' elapsed_time_per_iteration_ms=' f'{elapsed_time_per_iteration * 1000.0:.1f} |' # .format( elapsed_time_per_iteration * 1000.0) ) - log_string += f' learning rate={learning_rate:.3f} |' - log_string += f' global batch size={batch_size:5d} |' + log_string += f' learning_rate={learning_rate:.6f} |' + log_string += f' global_batch_size={batch_size:5d} |' # if wandb is not None and getattr(wandb, 'run', None) is not None: wandb_metrics |= { 'training/iteration': iteration, @@ -1221,28 +1221,28 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration, log_string += ' {}={:.6f} |'.format(key, avg) total_loss_dict[key] = get_accelerator().FloatTensor([0.0]) if loss_scale is not None: - log_string += ' loss scale={:.1f} |'.format(loss_scale) + log_string += ' loss_scale={:.1f} |'.format(loss_scale) wandb_metrics |= {'loss/loss_scale': loss_scale} if grad_norm is not None: - log_string += ' grad norm={:.3f} |'.format(grad_norm) + log_string += ' grad_norm={:.3f} |'.format(grad_norm) wandb_metrics |= {'loss/grad_norm': grad_norm} if num_zeros_in_grad is not None: - log_string += ' num zeros={:.1f} |'.format(num_zeros_in_grad) + log_string += ' num_zeros={:.1f} |'.format(num_zeros_in_grad) wandb_metrics |= {'loss/num_zeros_in_grad': num_zeros_in_grad} if params_norm is not None: - log_string += ' params norm={:.3f} |'.format(params_norm) + log_string += ' params_norm={:.3f} |'.format(params_norm) wandb_metrics |= {'loss/params_norm': params_norm} if args.curriculum_learning_legacy or args.data_efficiency_curriculum_learning: - log_string += ' curriculum seqlen={:5d} |'.format(args.curriculum_seqlen) + log_string += ' curriculum_seqlen={:5d} |'.format(args.curriculum_seqlen) if args.random_ltd: - log_string += ' random ltd reserved length={:5d} |'.format(args.random_ltd_reserved_length) - log_string += ' actual seqlen={:5d} |'.format(seq_len) - log_string += ' number of skipped iterations={:3d} |'.format( + log_string += ' random_ltd reserved_length={:5d} |'.format(args.random_ltd_reserved_length) + log_string += ' actual_seqlen={:5d} |'.format(seq_len) + log_string += ' number_of_skipped_iterations={:3d} |'.format( total_loss_dict[skipped_iters_key]) - log_string += ' number of nan iterations={:3d} |'.format( + log_string += ' number_of_nan_iterations={:3d} |'.format( total_loss_dict[nan_iters_key]) - log_string += ' samples per second={:.3f} |'.format(samples_per_sec) - log_string += ' tokens per gpu per second (tgs)={:.3f} |'.format(tokens_per_gpu_per_second) + log_string += ' samples_per_second={:.3f} |'.format(samples_per_sec) + log_string += ' tokens_per_gpu_per_second_tgs={:.3f} |'.format(tokens_per_gpu_per_second) log_string += ' TFLOPs={:.2f} |'.format(tflops) total_loss_dict[advanced_iters_key] = 0 total_loss_dict[skipped_iters_key] = 0 From 7e6a3a42a8a8707fee77c844ce83015c6ce9e4d5 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 18 Apr 2024 08:40:44 -0500 Subject: [PATCH 183/268] Remove redundant `train_llama_alcf_*.sh` --- train_llama_alcf_aurora.sh | 234 ------------------------------------ train_llama_alcf_polaris.sh | 116 ------------------ train_llama_alcf_sunspot.sh | 158 ------------------------ 3 files changed, 508 deletions(-) delete mode 100644 train_llama_alcf_aurora.sh delete mode 100644 train_llama_alcf_polaris.sh delete mode 100644 train_llama_alcf_sunspot.sh diff --git a/train_llama_alcf_aurora.sh b/train_llama_alcf_aurora.sh deleted file mode 100644 index 48651dbeb1..0000000000 --- a/train_llama_alcf_aurora.sh +++ /dev/null @@ -1,234 +0,0 @@ -#!/bin/bash --login -#PBS -l walltime=06:00:00 -#PBS -A argonne_tpc -#PBS -q prod -#PBS -l select=48 -#PBS -l filesystems=eagle:home -# - -function sourceFile() { - fp="$1" - if [[ -f "${fp}" ]]; then - echo "Found ${fp}, \`source\`-ing" - # shellcheck source="${fp}" - source "${fp}" - else - echo "ERROR: UNABLE TO SOURCE ${fp}" - fi -} - -# +++++++++++++++ SCRIPT START ++++++++++++++++++++++ -# ---- source ./helpers_alcf.sh --------------------- -cd "${PBS_O_WORKDIR}" || exit -HERE=$(python3 -c 'import os; print(os.getcwd())') -sourceFile "${HERE}/ALCF_utils/helpers_alcf.sh" || exit -# cd ~/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed || exit -# eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate anl_release_q4v2 -ezpz || exit -setEnv || exit -saveDSenv || exit -makeHostfiles || exit -setupData "${DATA_FILE_LIST:-${HERE}/data_file_list_reweighted.txt}" || exit -# dfl_fallback="${HERE}/data_file_list_shuf_debug.txt" - -# # ---- DATA SETUP ------------------------------------ -# dfl_debug="./data_file_list_shuf_debug.txt" -# DATA_FILE_LIST="${DATA_FILE_LIST:-${dfl_debug}}" && export DATA_FILE_LIST="${DATA_FILE_LIST}" -# NUM_DOCS=$(wc -l < "${DATA_FILE_LIST}") && export NUM_DOCS="${NUM_DOCS}" -# WEIGHT_SUM="$(sumWeights "${DATA_FILE_LIST}")" && export WEIGHT_SUM="${WEIGHT_SUM}" -# DFL_STEM=$(echo "$DATA_FILE_LIST" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") && export DFL_STEM="${DFL_STEM}" -# dcp="${HERE}/.cache/${DFL_STEM}-index-cache" -# DATA_CACHE_PATH="${DATA_CACHE_PATH:-${dcp}}" && export DATA_CACHE_PATH="${DATA_CACHE_PATH}" -# mkdir -p "${DATA_CACHE_PATH}" -# if [[ -n "${DOLMA_CHUNK_IDX}" ]]; then -# echo "Using DOLMA CHUNK ${DOLMA_CHUNK_IDX} from ${DATA_FILE_LIST} with ${NUM_DOCS} documents..." -# else -# echo "Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" -# fi - - -# ---- Parallelism Settings -------------------------- -PP=${PP:-1} -TP=${TP:-1} -export PP="${PP}" -export TP="${TP}" -export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" -export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} -# export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${PBS_NODEFILE}")} -# ---------------------------------------------------- - -# ---- Llama2 7B Config ----------------------- -export HEADS=${HEADS:-32} -export NLAYERS=${NLAYERS:-32} -export HIDDEN=${HIDDEN:-4096} -export NUM_KV_HEAD=${NUM_KV_HEAD:-8} -export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" -# --------------------------------------------- - -# ---- Run Settings --------------------------- -export LR=${LR:-0.0003} -export SEQ=${SEQ:-4096} -export DTYPE=${DTYPE:-bf16} -export ZERO_STAGE=${ZERO_STAGE:-2} -export MICRO_BATCH=${MICRO_BATCH:-4} -export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} -export TRAIN_ITER=${TRAIN_ITER:-317892} -export SAVE_INTERVAL=${SAVE_INTERVAL:-200} -export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} -export GLOBAL_BATCH=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) -export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-0} -export TOKENIZER_MODEL="/lus/gecko/projects/Aurora_deployment/AuroraGPT/datasets/dolma/utils/tokenizer.model" -# export EXTRA_ARGS="" -export LLAMA_ARGS="--no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" -# --------------------------------------------- - -# ---- Build DeepSpeed Config --------------------------------- -export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" -bash "${HERE}/generate_config.sh" "${DS_CONFIG}" || exit -# ------------------------------------------------------------- - - -# ---- Specify output location -------------------------------- -export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}" -# OUTPUT_DIR=logs/ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_`date +%m%d%H%M%S`_${HOSTNAME} -OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" -export OUTPUT_DIR="${OUTPUT_DIR}" -export OUTPUT_LOG="${OUTPUT_DIR}/output.log" -export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" -echo "${OUTPUT_LOG}" >> "logs/latest" -mkdir -p "${OUTPUT_DIR}" -echo "!!!Please see logs at ${OUTPUT_DIR}" - - -gpt_args=() -ds_args=" " -ds_args=" --deepspeed ${ds_args}" -if [ "$PP" == 1 ]; then - ds_args=" --no-pipeline-parallel ${ds_args}" -fi -ds_args=" --deepspeed_config=$DS_CONFIG ${ds_args}" -ds_args=" --zero-stage=$ZERO_STAGE ${ds_args}" - -# BUG: [???] ---------------------------------------------------------------- -# I dont know where this came from... -# > we are now using activation checkpoint provided by megatron, see below. -# --------------------------------------------------------------------------- -# -# NOTE: [???] --------------------------------------------------------------- -# In `train_llama_alcf_polaris.sh` we also pass -# `"--checkpoint-num-layers 1"` -# ---------------------------------------------------------------------------- -if [[ "$USE_ACTIVATION_CHECKPOINTING" == 1 ]]; then - echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" - ds_args=" --deepspeed-activation-checkpointing ${ds_args}" - gpt_args+=( - "--checkpoint-activations" - ) - # "--checkpoint-num-layers 1" - # --checkpoint-activations \ - # --deepspeed-activation-checkpointing -fi - -# take custom args -custom_args=" $@" - -# Ensure `./hostfile_deepspeed` and `./hostfile_mpich` exist in $(pwd) -hfds="${HERE}/hostfile_deepspeed" -hfmpi="${HERE}/hostfile_mpich" -[ -f "$hfds" ] || exit -[ -f "$hfmpi" ] || exit - -# launcher setting -LAUNCHER=${LAUNCHER:-MPICH} -if [[ $LAUNCHER == "deepspeed" ]]; then - launcher="" -else - launcher="--force_multi --hostfile ${hfds} --launcher=${LAUNCHER} --launcher_args='-hostfile ${hfmpi}'" -fi - - -if [[ $(hostname) == x4* ]]; then - CCL=${CCL:-ccl} - BE="${CCL}" -elif [[ $(hostname) == x3* ]]; then - NCCL=${NCCL:-nccl} - BE="${NCCL}" -fi -# NCCL=${NCCL:-nccl} -EXEC=pretrain_gpt_alcf.py - -# MODEL=LLAMA_7B -# OUTPUT_PREFIX=${MODEL}_z${ZERO_STAGE}_seqlen_tp${TP}_pp${PP}_sp${SP}_nl${NUM_LAYERS}_hs${HIDDEN_SIZE}_gb${BS}_mb${MBS} -echo "++++++++++++++++++++++++++++++++++++++++++++++++++" -echo "- WORLD_SIZE:${WORLD_SIZE}" -echo "- BACKEND: ${BE}" -echo "- MODEL_TYPE: ${MODEL_TYPE}" -echo "- DOCUMENT WEIGHT_SUM: ${WEIGHT_SUM}" -echo "- Using DATA_FILE_LIST: ${DATA_FILE_LIST}" -echo "- Using NUM_DOCS=${NUM_DOCS} documents from DATA_FILE_LIST=${DATA_FILE_LIST}" -echo "++++++++++++++++++++++++++++++++++++++++++++++++++" - -run_cmd=" - deepspeed $launcher ${EXEC} \ - --use-flash-attn \ - --num-key-value-heads ${NUM_KV_HEAD} \ - --tensor-model-parallel-size $TP \ - --pipeline-model-parallel-size $PP \ - --num-layers $NLAYERS \ - --hidden-size $HIDDEN \ - --num-attention-heads $HEADS \ - --seq-length $SEQ \ - --max-position-embeddings $SEQ \ - --micro-batch-size $MICRO_BATCH \ - --global-batch-size $GLOBAL_BATCH \ - --train-iters $TRAIN_ITER \ - --lr ${LR} \ - --lr-decay-style cosine \ - --log-interval 1 \ - --save-interval ${SAVE_INTERVAL} \ - --split 100,0,0 \ - --$DTYPE \ - --no-masked-softmax-fusion \ - --no-bias-gelu-fusion \ - --no-bias-dropout-fusion \ - --no-gradient-accumulation-fusion \ - --distributed-backend ${BE} \ - --tokenizer-type Llama2Tokenizer \ - --save checkpoints/${OUTPUT_PREFIX} \ - --load checkpoints/${OUTPUT_PREFIX} \ - --use-checkpoint-opt_param-scheduler \ - --tokenizer-model ${TOKENIZER_MODEL} \ - --data-file-list ${DATA_FILE_LIST} \ - --data-cache-path ${DATA_CACHE_PATH} \ - $ds_args \ - ${LLAMA_ARGS} \ - ${gpt_args[*]} \ - $custom_args \ - |& tee ${OUTPUT_LOG} - " - # >> ${OUTPUT_LOG} 2>&1 & - # |& tee $OUTPUT_DIR/output.log - -# --ffn-hidden-size 11008 \ -# --vocab-file $VOCAB_FILE \ -# --merge-file $MERGE_FILE \ -# --lr-decay-iters 320000 \ -# --num-workers 0 \ -# --eval-iters ${EVAL_ITERS} \ -# --eval-interval ${EVAL_INTERVAL} \ -# --lr-warmup-iters 5000 \ -# --lr-decay-iters 10000 \ -# --accumulate-allreduce-grads-in-fp32 \ -# --data-impl mmap \ - -echo "All DeepSpeed(s): $(which -a deepspeed)" -echo "Using $(which deepspeed)" -ds_report - -echo "${run_cmd}" - -printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" -printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" - -eval "${run_cmd}" -set +x diff --git a/train_llama_alcf_polaris.sh b/train_llama_alcf_polaris.sh deleted file mode 100644 index 06f268f10e..0000000000 --- a/train_llama_alcf_polaris.sh +++ /dev/null @@ -1,116 +0,0 @@ -#!/bin/bash --login -#PBS -l walltime=06:00:00 -#PBS -A argonne_tpc -#PBS -q prod -#PBS -l select=48 -#PBS -l filesystems=eagle:home - -function sourceFile() { - fp="$1" - echo "source-ing ${fp}" - if [[ -f "${fp}" ]]; then - # shellcheck source="${fp}" - source "${fp}" - else - echo "ERROR: UNABLE TO SOURCE ${fp}" - fi -} - -# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -# ---- 0. Navigate into `$PBS_O_WORKDIR` ------------------------------------- -cd "${PBS_O_WORKDIR}" || exit -HERE=$(python3 -c 'import os; print(os.getcwd())') -export HERE -# ---- 1. Assert `./pretrain_gpt_alcf.py` exists: ----------------------------- -export EXEC="${HERE}/pretrain_gpt_alcf.py" -[ -f "${EXEC}" ] || exit -# ---- 2. `source ./ALCF/helpers_alcf.sh`: ------------------------------------ -sourceFile "${HERE}/ALCF/helpers.sh" || exit -# ---- 3. Call fns from `./ALCF/helpers_alcf.sh` ------------------------------ -setEnv || exit # 1. load `conda` environment -saveDSenv || exit # 2. save env vars to `.deepspeed_env` -ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars -makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` -setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` -buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ -setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} -setArgs || exit # 8. specify additional `deepspeed` arguments -setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset -setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` -printJobInfo || exit # 11. print job info -# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ - -# Take custom args -custom_args=" $@" - -# Assert `./hostfile_deepspeed` exists -export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit -TBDIR="${CKPT_DIR}/tensorboard" -mkdir -p "${TBDIR}" - -# source "${HERE}/venvs/polaris/2024-03-14/bin/activate" || exit -# echo "Using $(which python3)" -# --launcher_args='--pmi=pmix' - # deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ - # ${launch_cmd} \ - # --optimizer adam \ - # --use-flash-attn-v2 \ - # --num-workers 0 \ -run_cmd=" - deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ - --$DTYPE \ - --optimizer ${OPT} \ - --split 100,0,0 \ - --log-interval 1 \ - --no-bias-gelu-fusion \ - --lr-decay-style cosine \ - --no-bias-dropout-fusion \ - --no-masked-softmax-fusion \ - --tokenizer-type Llama2Tokenizer \ - --no-gradient-accumulation-fusion \ - --accumulate-allreduce-grads-in-fp32 \ - --use-checkpoint-opt_param-scheduler \ - --tensorboard-dir ${TBDIR} \ - --log-timers-to-tensorboard \ - --log-optimizer-states-to-tensorboard \ - --lr ${LR} \ - --save ${CKPT_DIR} \ - --load ${CKPT_DIR} \ - --seq-length ${SEQ} \ - --num-layers ${NLAYERS} \ - --hidden-size ${HIDDEN} \ - --train-iters ${TRAIN_ITER} \ - --eval-iters ${EVAL_ITERS} \ - --distributed-backend ${BE} \ - --num-attention-heads ${HEADS} \ - --save-interval ${SAVE_INTERVAL} \ - --eval-interval ${EVAL_INTERVAL} \ - --max-position-embeddings ${SEQ} \ - --micro-batch-size ${MICRO_BATCH} \ - --data-file-list ${DATA_FILE_LIST} \ - --tensor-model-parallel-size ${TP} \ - --global-batch-size ${GLOBAL_BATCH} \ - --pipeline-model-parallel-size ${PP} \ - --num-key-value-heads ${NUM_KV_HEAD} \ - --data-cache-path ${DATA_CACHE_PATH} \ - --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ - --tokenizer-model ${TOKENIZER_MODEL} \ - ${LLAMA_ARGS} \ - $ds_args \ - ${gpt_args[*]} \ - $custom_args \ - |& tee ${OUTPUT_LOG} - " - - -# echo "All DeepSpeed(s): $(which -a deepspeed)" -echo "! Using $(which deepspeed)" -ds_report - -echo "${run_cmd}" - -printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" -printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" -# echo "${OUTPUT_LOG}" -eval "${run_cmd}" -set +x diff --git a/train_llama_alcf_sunspot.sh b/train_llama_alcf_sunspot.sh deleted file mode 100644 index 700f5dbfdb..0000000000 --- a/train_llama_alcf_sunspot.sh +++ /dev/null @@ -1,158 +0,0 @@ -#!/bin/bash --login -#PBS -l walltime=06:00:00 -#PBS -A argonne_tpc -#PBS -q prod -#PBS -l select=48 -#PBS -l filesystems=eagle:home - -function sourceFile() { - fp="$1" - echo "source-ing ${fp}" - if [[ -f "${fp}" ]]; then - # shellcheck source="${fp}" - source "${fp}" - else - echo "ERROR: UNABLE TO SOURCE ${fp}" - fi -} - -module () { - if [ -z "${LMOD_SH_DBG_ON+x}" ] - then - case "$-" in - (*v*x*) __lmod_sh_dbg='vx' ;; - (*v*) __lmod_sh_dbg='v' ;; - (*x*) __lmod_sh_dbg='x' ;; - esac - fi - if [ -n "${__lmod_sh_dbg:-}" ] - then - set +$__lmod_sh_dbg - echo "Shell debugging temporarily silenced: export LMOD_SH_DBG_ON=1 for Lmod's output" >&2 - fi - eval "$($LMOD_CMD $LMOD_SHELL_PRGM "$@")" && eval "$(${LMOD_SETTARG_CMD:-:} -s sh)" - __lmod_my_status=$? - if [ -n "${__lmod_sh_dbg:-}" ] - then - echo "Shell debugging restarted" >&2 - set -$__lmod_sh_dbg - fi - unset __lmod_sh_dbg - return $__lmod_my_status -} - - -# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -# ---- 0. Navigate into `$PBS_O_WORKDIR` ------------------------------------- -cd "${PBS_O_WORKDIR}" || exit -HERE=$(python3 -c 'import os; print(os.getcwd())') -export HERE -# ---- 1. Assert `./pretrain_gpt_alcf.py` exists: ----------------------------- -export EXEC="${HERE}/pretrain_gpt_alcf.py" -[ -f "${EXEC}" ] || exit -# ---- 2. `source ./ALCF/helpers_alcf.sh`: ------------------------------------ -sourceFile "${HERE}/ALCF/helpers.sh" || exit -# ---- 3. Call fns from `./ALCF/helpers_alcf.sh` ------------------------------------------------------------------ -setEnv || exit # 1. load `conda` environment -saveDSenv || exit # 2. save env vars to `.deepspeed_env` -ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars -makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` -setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` -buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ -setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} -setArgs || exit # 8. specify additional `deepspeed` arguments -setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset -setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` -printJobInfo || exit # 11. print job info -# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ - -# Take custom args -custom_args=" $@" - -# Assert `./hostfile_deepspeed` exists -export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit - -TBDIR="${CKPT_DIR}/tensorboard" -mkdir -p "${TBDIR}" - - # --use-flash-attn-v2 \ - # --use-flash-attn \ - # --$DTYPE \ - # --optimizer adamw \ - # --adam-beta1 0.9 \ - # --adam-beta2 0.95 \ -run_cmd=" - deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ - --${DTYPE} \ - --optimizer ${OPT} \ - --num-workers 0 \ - --split 100,0,0 \ - --log-interval 1 \ - --no-bias-gelu-fusion \ - --lr-decay-style cosine \ - --no-bias-dropout-fusion \ - --no-masked-softmax-fusion \ - --tokenizer-type Llama2Tokenizer \ - --no-gradient-accumulation-fusion \ - --accumulate-allreduce-grads-in-fp32 \ - --use-checkpoint-opt_param-scheduler \ - --tensorboard-dir ${TBDIR} \ - --log-timers-to-tensorboard \ - --log-optimizer-states-to-tensorboard \ - --lr ${LR} \ - --save ${CKPT_DIR} \ - --load ${CKPT_DIR} \ - --seq-length ${SEQ} \ - --num-layers ${NLAYERS} \ - --hidden-size ${HIDDEN} \ - --train-iters ${TRAIN_ITER} \ - --eval-iters ${EVAL_ITERS} \ - --distributed-backend ${BE} \ - --num-attention-heads ${HEADS} \ - --save-interval ${SAVE_INTERVAL} \ - --eval-interval ${EVAL_INTERVAL} \ - --max-position-embeddings ${SEQ} \ - --micro-batch-size ${MICRO_BATCH} \ - --data-file-list ${DATA_FILE_LIST} \ - --tensor-model-parallel-size ${TP} \ - --global-batch-size ${GLOBAL_BATCH} \ - --pipeline-model-parallel-size ${PP} \ - --num-key-value-heads ${NUM_KV_HEAD} \ - --data-cache-path ${DATA_CACHE_PATH} \ - --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ - --tokenizer-model ${TOKENIZER_MODEL} \ - ${LLAMA_ARGS} \ - $ds_args \ - ${gpt_args[*]} \ - $custom_args \ - |& tee ${OUTPUT_LOG} - " - - # --------------------------------------------------- - # --vocab-file $VOCAB_FILE \ - # --merge-file $MERGE_FILE \ - # --lr-decay-iters 320000 \ - # --lr-warmup-iters 5000 \ - # --lr-decay-iters 10000 \ - # --num-workers 4 \ - # launch python3 ${EXEC} \ - # --data-impl mmap \ - # source ./ezpz/src/ezpz/bin/getjobenv || exit - # --------------------------------------------------- - # ${DIST_LAUNCH} ./local_rank.sh python3 ${EXEC} \ - # ${DIST_LAUNCH} python3 ${EXEC} \ - # deepspeed $launcher ${EXEC} \ - # >> ${OUTPUT_LOG} 2>&1 & - # >> ${OUTPUT_LOG} 2>&1 & - # |& tee $OUTPUT_DIR/output.log - # ${EXTRA_ARGS} \ - -echo "! Using $(which deepspeed)" -ds_report - -echo "${run_cmd}" -printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" -printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" -# echo "${OUTPUT_LOG}" -eval "${run_cmd}" -set +x From d243489c1c6b0e41e39e3e81d78b42a04538a849 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 18 Apr 2024 11:27:20 -0500 Subject: [PATCH 184/268] Update README.md --- ALCF/README.md | 463 ++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 461 insertions(+), 2 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index d95c70125d..5f0fd1b6bd 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -1,6 +1,9 @@ # Megatron-DeepSpeed @ ALCF -## Polaris +## ✅ TODOs + +
+TODOs: - [ ] Ensure / double check that optimizer settings from `ds_config.json` aren't being overwritten by some defaults in `megatron/arguments.py` - [ ] specifically, `momentum, beta{1, 2}, etc` @@ -69,6 +72,456 @@
+
+ +## 🏃‍♂️ Running + +> [!NOTE] +> [`train_llama_alcf.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/train_llama_alcf.sh) is the main entry point for launching +> distributed training on {Polaris, Aurora, Sunspot} @ ALCF. + +To launch: + +```bash +$ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I +$ cd /path/to/Megatron-DeepSpeed/ +# load your favorite {conda, venv} environment, requires: {pytorch, deepspeed} +# e.g. on Polaris: +$ module load conda/2023-10-04 # ; conda activate cu118-pt221 ; unset PYTHONUSERBASE +$ export PBS_O_WORKDIR="$(pwd)" && DATA_FILE_LIST=./convergence_debug_small.txt DTYPE=bf16 OPT=adamw bash train_llama_alcf.sh +``` + +
[output]: + +
+ +
[Sunspot]: + +```bash +# [09:07:32 AM] [foremans@x1921c0s0b0n0] ~/q/llm.devkit/Megatron-DeepSpeed  main !1 ?27 q4-drop 26s ✘ INT +$ PBS_O_WORKDIR=$(pwd) DATA_FILE_LIST=./convergence_debug_small.txt bash train_llama_alcf.sh +source-ing /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/ALCF/helpers.sh +Sourcing /home/foremans/q4-drop_sunspot/llm.devkit/setenv.sh... + UMD: agama-ci-devel-736.9 successfully loaded: + UMD: graphics-compute-runtime/agama-ci-devel-736.9 +Lmod has detected the following error: The following module(s) are unknown: "gcc/12.1.0" + +Please check the spelling or version number. Also try "module spider ..." +It is also possible your cache file is out-of-date; it may help to try: + $ module --ignore_cache load "gcc/12.1.0" + +Also make sure that all modulefiles written in TCL start with the string #%Module + +Note: the module "intel_compute_runtime/release/agama-devel-647" cannot be unloaded because it was not loaded. + +Running on SunSpot !! +[python] Using: /home/foremans/miniconda3/envs/q4-drop/bin/python3 +Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env +Found ezpz! +/lus/gila/projects/Aurora_deployment/foremans/locations/sunspot/projects/saforem2/ezpz/src/ezpz/__init__.py +Has ezpz installed. Nothing to do. +Done with ezpz. +┌─────────────────────────────────────────────────────────────────── +│ Writing PBS vars to /home/foremans/.pbsenv +│ HOSTFILE: /var/spool/pbs/aux/8988430.amn-0001 +│ NHOSTS: 2 +│ NGPU_PER_HOST: 12 GPUs per host +│ NGPUS: 24 GPUs total +└─────────────────────────────────────────────────────────────────── +┌────────────────────────────────────────────────────────────────── +│ [Hosts]: +│ • [host:0] - x1921c0s0b0n0.hostmgmt2000.cm.americas.sgi.com +│ • [host:1] - x1921c0s1b0n0.hostmgmt2000.cm.americas.sgi.com +└────────────────────────────────────────────────────────────────── +┌────────────────────────────────────────────────────────────────── +│ [DIST INFO]: +│ • Loading job env from: /home/foremans/.pbsenv +│ • HOSTFILE: /var/spool/pbs/aux/8988430.amn-0001 +│ • NHOSTS: 2 +│ • NGPU_PER_HOST: 12 +│ • NGPUS (NHOSTS x NGPU_PER_HOST): 24 +│ • WORLD_SIZE: 24 +│ • DIST_LAUNCH: mpiexec --verbose --envall -n 24 -ppn 12 --hostfile /var/spool/pbs/aux/8988430.amn-0001 +└────────────────────────────────────────────────────────────────── +┌────────────────────────────────────────────────────────────────── +│ [Launch]: +│ • Use: 'launch' (=mpiexec --verbose --envall -n 24 -ppn 12 --hostfile /var/spool/pbs/aux/8988430.amn-0001) +│ to launch job +└────────────────────────────────────────────────────────────────── +DS_CONFIG: ds_stage2_mb4_gb96_pp1_bf16.json +ZS: 2, CPU_OPTIMIZER: , MB: 4, GB: 96, PP: 1, DTYPE: bf16!!!Please see logs at logs/ds_stage2_nl32_hs4096_mb4_seq4096_gb96_pp1_tp1_bf16/0404090742_x1921c0s0b0n0 +!! Caught USE_ACTIVATION_CHECKPOINTING=1 !! +!! Caught USE_ACTIVATION_CHECKPOINTING=1 !! +Calling: `setData()` with ./convergence_debug_small.txt +-------------------- +Updated environment: +DATA_FILE_LIST: ./convergence_debug_small.txt +NUM_DOCS: 15 + WEIGHT_SUM: 15.0 +DFL_STEM: convergence_debug_small +DATA_CACHE_PATH: /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache +-------------------- +++++++++++++++++++++++++++++++++++++++++++++++++++ +- MPICH_DIR= +- Using /home/foremans/miniconda3/envs/q4-drop/bin/python3 +- WORLD_SIZE:24 +- NCCL: nccl +- MODEL_TYPE: llama-seq4096-pp1-tp1-32layers-32heads-4096hidden +- Using DATA_FILE_LIST: ./convergence_debug_small.txt +++++++++++++++++++++++++++++++++++++++++++++++++++ +! Using /home/foremans/miniconda3/envs/q4-drop/bin/deepspeed +/home/foremans/miniconda3/envs/q4-drop/bin/ds_report:4: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html + __import__('pkg_resources').require('deepspeed==0.12.3+6ea44d02') +/home/foremans/miniconda3/envs/q4-drop/lib/python3.9/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: ''If you don't plan on using image function +ality from `torchvision.io`, you can ignore this warning. Otherwise, there might be something wrong with your environment. Did you have `libjpeg` or `libpng` installed before building `torch +vision` from source? + warn( +[2024-04-04 09:07:45,585] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to xpu (auto detect) +[2024-04-04 09:07:45,818] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to xpu (auto detect) +-------------------------------------------------- +DeepSpeed C++/CUDA extension op report +-------------------------------------------------- +NOTE: Ops not installed will be just-in-time (JIT) compiled at + runtime if needed. Op compatibility means that your system + meet the required dependencies to JIT install the op. +-------------------------------------------------- +JIT compiled ops requires ninja +ninja .................. [OKAY] +-------------------------------------------------- +op name ................ installed .. compatible +-------------------------------------------------- +async_io ............... [NO] ....... [OKAY] +cpu_adagrad ............ [NO] ....... [OKAY] +cpu_adam ............... [NO] ....... [OKAY] +flash_attn ............. [NO] ....... [OKAY] +fused_adam ............. [NO] ....... [OKAY] +quantizer .............. [NO] ....... [OKAY] +transformer ............ [NO] ....... [OKAY] +transformer_inference .. [NO] ....... [OKAY] +utils .................. [NO] ....... [OKAY] +-------------------------------------------------- +DeepSpeed general environment info: +torch install path ............... ['/home/foremans/miniconda3/envs/q4-drop/lib/python3.9/site-packages/torch'] +torch version .................... 2.1.0a0+cxx11.abi +deepspeed install path ........... ['/lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/DeepSpeed/deepspeed'] +deepspeed info ................... 0.12.3+6ea44d02, 6ea44d02, HEAD +deepspeed wheel compiled w. ...... torch 2.1 +shared memory (/dev/shm) size .... 503.18 GB + + deepspeed --hostfile /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/hostfile_deepspeed --launcher MPICH /lus/gila/projects/Aurora_deployment/ +foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/pretrain_gpt_alcf.py --bf16 --optimizer adamw --split 100,0,0 --log-interval 1 --no-bias-gelu-fusion --lr-decay +-style cosine --no-bias-dropout-fusion --no-masked-softmax-fusion --tokenizer-type Llama2Tokenizer --no-gradient-accumulation-fusion --accumulate-allreduce-grads-in-fp32 + --use-checkpoint-opt_param-scheduler --tensorboard-dir checkpoints/ds_stage2_nl32_hs4096_mb4_seq4096_gb96_pp1_tp1_bf16/tensorboard --log-timers-to-tensorboard --log-optimizer +-states-to-tensorboard --lr 0.0003 --save checkpoints/ds_stage2_nl32_hs4096_mb4_seq4096_gb96_pp1_tp1_bf16 --load checkpoints/ds_stage2_nl32_hs4096_mb4_seq4096_gb96_pp1_tp1_bf16 + --seq-length 4096 --num-layers 32 --hidden-size 4096 --train-iters 317892 --eval-iters 10 --distributed-backend ccl --num-attention-heads 32 --save-interval 20 +0 --eval-interval 50000 --max-position-embeddings 4096 --micro-batch-size 4 --data-file-list ./convergence_debug_small.txt --tensor-model-parallel-size 1 --global-bat +ch-size 96 --pipeline-model-parallel-size 1 --num-key-value-heads 8 --data-cache-path /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/ +.cache/convergence_debug_small/index-cache --ffn-hidden-size 11008 --tokenizer-model /home/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/ALCF/tokenizer.model --no-query- +key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear --deepspeed-activation-checkpointing --z +ero-stage=2 --deepspeed_config=ds_stage2_mb4_gb96_pp1_bf16.json --no-pipeline-parallel --deepspeed --checkpoint-activations --checkpoint-num-layers 1 |& tee logs/ds_stage2 +_nl32_hs4096_mb4_seq4096_gb96_pp1_tp1_bf16/0404090742_x1921c0s0b0n0/output.log + +[!! NOTE] View output at: +logs/ds_stage2_nl32_hs4096_mb4_seq4096_gb96_pp1_tp1_bf16/0404090742_x1921c0s0b0n0/output.log + +# ... + +/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/cc_en_middle-0051_text_document.bin + creating memory view of numpy buffer... + > finished creating indexed dataset in 0.010017 seconds + number of documents: 1498927 + > dataset split: + train: + document indices in [0, 1498927) total of 1498927 documents + validation: + document indices in [1498927, 1498927) total of 0 documents + test: + document indices in [1498927, 1498927) total of 0 documents + > loading doc-idx mapping from /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/bf90c74a625ac2ee4de6e1d6f7f84fbb_doc_idx.npy + > loading sample-idx mapping from /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/bf90c74a625ac2ee4de6e1d6f7f84fbb_sample_idx.npy + > loading shuffle-idx mapping from /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/bf90c74a625ac2ee4de6e1d6f7f84fbb_shuffle_idx.npy + loaded indexed file in 0.056 seconds + total number of samples: 2318461 + total number of epochs: 8 +> loading blendable dataset index: /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/3a426af74008c22f9db24db811aad6b7_index.npy +> loading blendable dataset sample index: /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/llm.devkit/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/3a426af74008c22f9db24db811aad6b7_sample_index.npy +/home/foremans/miniconda3/envs/q4-drop/lib/python3.9/site-packages/torch/utils/data/dataloader.py:557: UserWarning: This DataLoader will create 2 worker processes in total. Our suggested max number of worker in current system is 1, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary. + +[after dataloaders are built] datetime: 2024-04-04 09:09:27 +done with setup ... +(min, max) time across ranks (ms): + model-and-optimizer-setup ......................: (64818.18, 64858.22) + train/valid/test-data-iterators-setup ..........: (1968.10, 2288.56) +training ... +[before the start of training step] datetime: 2024-04-04 09:09:27 +[2024-04-04 09:09:27,718] [INFO] [checkpointing.py:540:forward] Activation Checkpointing Information +[2024-04-04 09:09:27,719] [INFO] [checkpointing.py:541:forward] ----Partition Activations False, CPU CHECKPOINTING False +[2024-04-04 09:09:27,719] [INFO] [checkpointing.py:542:forward] ----contiguous Memory Checkpointing False with 32 total layers +[2024-04-04 09:09:27,719] [INFO] [checkpointing.py:544:forward] ----Synchronization False +[2024-04-04 09:09:27,719] [INFO] [checkpointing.py:545:forward] ----Profiling time in checkpointing False +[2024-04-04 09:09:33][INFO][utils:145] - Note: detected 208 virtual cores but NumExpr set to maximum of 64, check "NUMEXPR_MAX_THREADS" environment variable. +[2024-04-04 09:09:33][INFO][utils:148] - Note: NumExpr detected 208 cores but "NUMEXPR_MAX_THREADS" not set, so enforcing safe limit of 8. +[2024-04-04 09:09:33][INFO][utils:160] - NumExpr defaulting to 8 threads. +^[c[2024-04-04 09:09:53,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 884.11 | optimizer_gradients: 6.43 | optimizer_step: 23.44 +[2024-04-04 09:09:53,312] [INFO] [logging.py:96:log_dist] [Rank 0] step=1, skipped=0, lr=[0.00029999999999267505, 0.00029999999999267505], mom=[(0.9, 0.999), (0.9, 0.999)] +[2024-04-04 09:09:53,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 6567.68 | bwd_microstep: 17950.36 | bwd_inner_microstep: 17711.20 | bwd_allreduce_microstep: 239.11 | step_microstep: 1139.27 +[2024-04-04 09:09:53,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 6567.66 | bwd: 17950.35 | bwd_inner: 17711.19 | bwd_allreduce: 239.11 | step: 1139.29 +[Rank 0] (after 1 iterations) memory (MB) | allocated: 18244.640625 | max allocated: 41299.50146484375 | reserved: 46764.0 | max reserved: 46764.0 + iteration 1/ 317892 | consumed samples: 96 | consumed tokens: 393216 | elapsed time per iteration (ms): 25849.1 | learning rate: 3.000E-04 | global batch size: 96 | lm loss: 1.117136E+01 | loss scale: 1.0 | actual seqlen: 4096 | number of skipped iterations: 0 | number of nan iterations: 0 | samples per second: 3.714 | tokens per gpu per second(tgs): 633.832 | TFLOPs: 38.61 | +[2024-04-04 09:10:13,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 327.85 | optimizer_gradients: 6.26 | optimizer_step: 23.60 +[2024-04-04 09:10:13,619] [INFO] [logging.py:96:log_dist] [Rank 0] step=2, skipped=0, lr=[0.00029999999997070033, 0.00029999999997070033], mom=[(0.9, 0.999), (0.9, 0.999)] +[2024-04-04 09:10:13,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 4022.74 | bwd_microstep: 15738.67 | bwd_inner_microstep: 15556.80 | bwd_allreduce_microstep: 181.82 | step_microstep: 371.01 +[2024-04-04 09:10:13,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4022.73 | bwd: 15738.66 | bwd_inner: 15556.62 | bwd_allreduce: 181.81 | step: 371.02 + iteration 2/ 317892 | consumed samples: 192 | consumed tokens: 786432 | elapsed time per iteration (ms): 20298.3 | learning rate: 3.000E-04 | global batch size: 96 | lm loss: 2.537718E+01 | loss scale: 1.0 | actual seqlen: 4096 | number of skipped iterations: 0 | number of nan iterations: 0 | samples per second: 4.729 | tokens per gpu per second(tgs): 807.159 | TFLOPs: 49.17 | +``` + +
+ +
[Polaris]: + +```bash +[09:31:35 AM] [foremans@x3112c0s13b0n0] ~/pol/p/a/Megatron-DeepSpeed  main !4 ?24 cu118-pt221 ✘ INT +$ export PBS_O_WORKDIR="$(pwd)" && DATA_FILE_LIST=./convergence_debug_small.txt DTYPE=bf16 OPT=adamw bash train_llama_alcf.sh +source-ing /lus/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/ALCF/helpers.sh +Running on Polaris !! + +[python] Using: /eagle/datascience/foremans/miniconda3/envs/cu118-pt221/bin/python3 +Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env +Found ezpz! +/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/ezpz/src/ezpz/__init__.py +Has ezpz installed. Nothing to do. +Done with ezpz. +┌─────────────────────────────────────────────────────────────────── +│ Writing PBS vars to /home/foremans/.pbsenv +│ HOSTFILE: /var/spool/pbs/aux/1822297.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov +│ NHOSTS: 2 +│ NGPU_PER_HOST: 4 GPUs per host +│ NGPUS: 8 GPUs total +└─────────────────────────────────────────────────────────────────── +┌────────────────────────────────────────────────────────────────── +│ [Hosts]: +│ • [host:0] - x3112c0s13b0n0.hsn.cm.polaris.alcf.anl.gov +│ • [host:1] - x3112c0s13b1n0.hsn.cm.polaris.alcf.anl.gov +└────────────────────────────────────────────────────────────────── +┌────────────────────────────────────────────────────────────────── +│ [DIST INFO]: +│ • Loading job env from: /home/foremans/.pbsenv +│ • HOSTFILE: /var/spool/pbs/aux/1822297.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov +│ • NHOSTS: 2 +│ • NGPU_PER_HOST: 4 +│ • NGPUS (NHOSTS x NGPU_PER_HOST): 8 +│ • WORLD_SIZE: 8 +│ • DIST_LAUNCH: mpiexec --verbose --envall -n 8 -ppn 4 --hostfile /var/spool/pbs/aux/1822297.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov +└────────────────────────────────────────────────────────────────── +┌────────────────────────────────────────────────────────────────── +│ [Launch]: +│ • Use: 'launch' (=mpiexec --verbose --envall -n 8 -ppn 4 --hostfile /var/spool/pbs/aux/1822297.polaris-pbs-01.hsn.cm.polaris.alcf.anl.gov) +│ to launch job +└────────────────────────────────────────────────────────────────── +DS_CONFIG: ds_stage2_mb8_gb32_pp1_bf16.json +ZS: 2, CPU_OPTIMIZER: , MB: 8, GB: 32, PP: 1, DTYPE: bf16!!!Please see logs at logs/ds_stage2_nl32_hs4096_mb8_seq4096_gb32_pp1_tp2_bf16/0404093534_x3112c0s13b0n0 +!! Caught USE_ACTIVATION_CHECKPOINTING=1 !! +!! Caught USE_ACTIVATION_CHECKPOINTING=1 !! +Calling: setData() with ./convergence_debug_small.txt +-------------------- +Updated environment: +DATA_FILE_LIST: ./convergence_debug_small.txt +NUM_DOCS: 15 + WEIGHT_SUM: 15.0 +DFL_STEM: convergence_debug_small +DATA_CACHE_PATH: /lus/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache +-------------------- +++++++++++++++++++++++++++++++++++++++++++++++++++ +- MPICH_DIR=/opt/cray/pe/mpich/8.1.25/ofi/gnu/9.1 +- Using /eagle/datascience/foremans/miniconda3/envs/cu118-pt221/bin/python3 +- WORLD_SIZE:8 +- NCCL: nccl +- MODEL_TYPE: llama-seq4096-pp1-tp2-32layers-32heads-4096hidden +- Using DATA_FILE_LIST: ./convergence_debug_small.txt +++++++++++++++++++++++++++++++++++++++++++++++++++ +! Using /eagle/datascience/foremans/miniconda3/envs/cu118-pt221/bin/deepspeed +[2024-04-04 09:35:35,959] [INFO] [real_accelerator.py:191:get_accelerator] Setting ds_accelerator to cuda (auto detect) +-------------------------------------------------- +DeepSpeed C++/CUDA extension op report +-------------------------------------------------- +NOTE: Ops not installed will be just-in-time (JIT) compiled at + runtime if needed. Op compatibility means that your system + meet the required dependencies to JIT install the op. +-------------------------------------------------- +JIT compiled ops requires ninja +ninja .................. [OKAY] +-------------------------------------------------- +op name ................ installed .. compatible +-------------------------------------------------- +async_io ............... [NO] ....... [OKAY] +fused_adam ............. [NO] ....... [OKAY] +cpu_adam ............... [NO] ....... [OKAY] +cpu_adagrad ............ [NO] ....... [OKAY] +cpu_lion ............... [NO] ....... [OKAY] + [WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH +evoformer_attn ......... [NO] ....... [NO] +fused_lamb ............. [NO] ....... [OKAY] +fused_lion ............. [NO] ....... [OKAY] +inference_core_ops ..... [NO] ....... [OKAY] +cutlass_ops ............ [NO] ....... [OKAY] +transformer_inference .. [NO] ....... [OKAY] +quantizer .............. [NO] ....... [OKAY] +ragged_device_ops ...... [NO] ....... [OKAY] +ragged_ops ............. [NO] ....... [OKAY] +random_ltd ............. [NO] ....... [OKAY] + [WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.2 + [WARNING] using untested triton version (2.2.0), only 1.0.0 is known to be compatible +sparse_attn ............ [NO] ....... [NO] +spatial_inference ...... [NO] ....... [OKAY] +transformer ............ [NO] ....... [OKAY] +stochastic_transformer . [NO] ....... [OKAY] +-------------------------------------------------- +DeepSpeed general environment info: +torch install path ............... ['/eagle/datascience/foremans/miniconda3/envs/cu118-pt221/lib/python3.12/site-packages/torch'] +torch version .................... 2.2.1 +deepspeed install path ........... ['/eagle/datascience/foremans/miniconda3/envs/cu118-pt221/lib/python3.12/site-packages/deepspeed'] +deepspeed info ................... 0.14.0, unknown, unknown +torch cuda version ............... 11.8 +torch hip version ................ None +nvcc version ..................... 11.8 +deepspeed wheel compiled w. ...... torch 2.2, cuda 11.8 +shared memory (/dev/shm) size .... 251.61 GB + + deepspeed --hostfile /lus/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/hostfile_deepspeed --launcher MPICH /lus/eagle/projects/datascienc +e/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/pretrain_gpt_alcf.py --bf16 --optimizer adamw --split 100,0,0 --log-interval 1 --no-bias-gelu-fusion + --lr-decay-style cosine --no-bias-dropout-fusion --no-masked-softmax-fusion --tokenizer-type Llama2Tokenizer --no-gradient-accumulation-fusion --accumulate-allreduce- +grads-in-fp32 --use-checkpoint-opt_param-scheduler --tensorboard-dir checkpoints/ds_stage2_nl32_hs4096_mb8_seq4096_gb32_pp1_tp2_bf16/tensorboard --log-timers-to-tensorboard - +-log-optimizer-states-to-tensorboard --lr 0.0003 --save checkpoints/ds_stage2_nl32_hs4096_mb8_seq4096_gb32_pp1_tp2_bf16 --load checkpoints/ds_stage2_nl32_hs4096_mb8_seq4096_gb32_ +pp1_tp2_bf16 --seq-length 4096 --num-layers 32 --hidden-size 4096 --train-iters 317892 --eval-iters 10 --distributed-backend nccl --num-attention-heads 32 --s +ave-interval 200 --eval-interval 50000 --max-position-embeddings 4096 --micro-batch-size 8 --data-file-list ./convergence_debug_small.txt --tensor-model-parallel-size 2 + --global-batch-size 32 --pipeline-model-parallel-size 1 --num-key-value-heads 8 --data-cache-path /lus/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-l +cf/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache --ffn-hidden-size 11008 --tokenizer-model /home/foremans/polaris/projects/argonne-lcf/Megatron-DeepSpeed/ALCF/tokeniz +er.model --no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear --use-flash-attn-v2 + --deepspeed-activation-checkpointing --zero-stage=2 --deepspeed_config=ds_stage2_mb8_gb32_pp1_bf16.json --no-pipeline-parallel --deepspeed --checkpoint-activations --checkpoint- +num-layers 1 |& tee logs/ds_stage2_nl32_hs4096_mb8_seq4096_gb32_pp1_tp2_bf16/0404093534_x3112c0s13b0n0/output.log + +[!! NOTE] View output at: +logs/ds_stage2_nl32_hs4096_mb8_seq4096_gb32_pp1_tp2_bf16/0404093534_x3112c0s13b0n0/output.log + +# ... + +/eagle/datasets/dolma/data_Llama2Tokenizer/common-crawl/cc_en_middle/cc_en_middle-0051_text_document.bin + creating memory view of numpy buffer... + > finished creating indexed dataset in 0.001280 seconds + number of documents: 1498927 + > dataset split: + train: + document indices in [0, 1498927) total of 1498927 documents + validation: + document indices in [1498927, 1498927) total of 0 documents + test: + document indices in [1498927, 1498927) total of 0 documents + > loading doc-idx mapping from /lus/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/9217d94f3290abc2fddf9e87bff236d6_doc_idx.npy + > loading sample-idx mapping from /lus/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/9217d94f3290abc2fddf9e87bff236d6_sample_idx.npy + > loading shuffle-idx mapping from /lus/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/9217d94f3290abc2fddf9e87bff236d6_shuffle_idx.npy + loaded indexed file in 0.004 seconds + total number of samples: 869423 + total number of epochs: 3 +> loading blendable dataset index: /lus/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/a815d51f6752c6f486d94194ce95fb87_index.npy +> loading blendable dataset sample index: /lus/eagle/projects/datascience/foremans/locations/polaris/projects/argonne-lcf/Megatron-DeepSpeed/.cache/convergence_debug_small/index-cache/a815d51f6752c6f486d94194ce95fb87_sample_index.npy +> size of blendable dataset: 10223415 samples +> finished creating GPT datasets ... +[after dataloaders are built] datetime: 2024-04-04 09:36:07 +done with setup ... +(min, max) time across ranks (ms): + model-and-optimizer-setup ......................: (4794.78, 4795.23) + train/valid/test-data-iterators-setup ..........: (589.69, 721.20) +training ... +[before the start of training step] datetime: 2024-04-04 09:36:07 +[2024-04-04 09:36:07,407] [INFO] [checkpointing.py:539:forward] Activation Checkpointing Information +[2024-04-04 09:36:07,407] [INFO] [checkpointing.py:540:forward] ----Partition Activations False, CPU CHECKPOINTING False +[2024-04-04 09:36:07,407] [INFO] [checkpointing.py:541:forward] ----contiguous Memory Checkpointing False with 32 total layers +[2024-04-04 09:36:07,407] [INFO] [checkpointing.py:543:forward] ----Synchronization False +[2024-04-04 09:36:07,407] [INFO] [checkpointing.py:544:forward] ----Profiling time in checkpointing False +[2024-04-04 09:36:28,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 1626.54 | optimizer_gradients: 19.29 | optimizer_step: 419.48 +[2024-04-04 09:36:28,430] [INFO] [logging.py:96:log_dist] [Rank 0] step=1, skipped=0, lr=[0.00029999999999267505, 0.00029999999999267505], mom=[(0.9, 0.999), (0.9, 0.999)] +[2024-04-04 09:36:28,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 11336.34 | bwd_microstep: 7134.73 | bwd_inner_microstep: 7090.02 | bwd_allreduce_microstep: 44.65 | step_microstep: 2564.02 +[2024-04-04 09:36:28,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 11336.33 | bwd: 7134.75 | bwd_inner: 7090.01 | bwd_allreduce: 44.66 | step: 2564.02 + iteration 1/ 317892 | consumed samples: 32 | consumed tokens: 131072 | elapsed time per iteration (ms): 21133.8 | learning rate: 3.000E-04 | global batch size: 32 | lm loss: 1.119983E+01 | loss scale: 1.0 | actual seqlen: 4096 | number of skipped iterations: 0 | number of nan iterations: 0 | samples per second: 1.514 | tokens per gpu per second(tgs): 775.250 | TFLOPs: 47.23 | +[Rank 1] (after 1 iterations) memory (MB) | allocated: 14165.525390625 | max allocated: 22332.37255859375 | reserved: 24642.0 | max reserved: 35824.0 +[Rank 0] (after 1 iterations) memory (MB) | allocated: 14165.525390625 | max allocated: 22332.37255859375 | reserved: 24642.0 | max reserved: 32994.0 +[2024-04-04 09:36:38,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 1605.55 | optimizer_gradients: 11.56 | optimizer_step: 50.92 +[2024-04-04 09:36:38,623] [INFO] [logging.py:96:log_dist] [Rank 0] step=2, skipped=0, lr=[0.00029999999997070033, 0.00029999999997070033], mom=[(0.9, 0.999), (0.9, 0.999)] +[2024-04-04 09:36:38,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1395.17 | bwd_microstep: 6832.48 | bwd_inner_microstep: 6789.73 | bwd_allreduce_microstep: 42.70 | step_microstep: 1867.64 +[2024-04-04 09:36:38,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1395.15 | bwd: 6832.49 | bwd_inner: 6789.73 | bwd_allreduce: 42.71 | step: 1867.65 + iteration 2/ 317892 | consumed samples: 64 | consumed tokens: 262144 | elapsed time per iteration (ms): 10154.3 | learning rate: 3.000E-04 | global batch size: 32 | lm loss: 1.766422E+01 | loss scale: 1.0 | actual seqlen: 4096 | number of skipped iterations: 0 | number of nan iterations: 0 | samples per second: 3.151 | tokens per gpu per second(tgs): 1613.503 | TFLOPs: 98.29 | + +# ... +``` + +
+ +
+ +## 📦 Install + +
Install Instructions + +1. Clone [`argonne-lcf/Megatron-DeepSpeed`](https://github.com/argonne-lcf/Megatron-DeepSpeed) + + ```bash + $ git clone https://github.com/argonne-lcf/Megatron-DeepSpeed + $ cd Megatron-DeepSpeed + ``` + + > [!NOTE] + > In the `conda create` command below, + > you can replace `--name "${DAY}"` with + > `--prefix /path/to/your/conda/envs`, if you prefer: + +2. Create `conda` env: + + ```bash + $ module load conda/2023-10-04 + $ export MPICC="cc -shared -taret-accel=nvidia80" + $ export DAY=$(date "+%Y-%m-%d") + $ export PYTHONUSERBASE="${HOME}/.local/polaris/conda/${DAY}" + $ conda create --solver libmamba -c pytorch -c nvidia --name "${DAY}" "python==3.12" + ``` + +3. Install dependencies: + + ```bash + $ conda activate "${DAY}" # e.g. 2024-03-07 + $ conda install -c pytorch -c nvidia --solver libmamba mpi4py ninja transformers xformers triton pytorch torchvision torchaudio pytorch-cuda=11.8 + $ conda install --solver libmamba mpi4py -c conda-forge -c pytorch -c nvidia + $ python3 -m pip install --upgrade pip pybind11 toolong appdirs wandb sentencepiece ipython setuptools wheel ninja + $ python3 -m pip install --upgrade deepspeed wandb + ``` + + - [`ezpz`](https://github.com/saforem2/ezpz): + +
install: + + ```bash + $ git clone https://github.com/saforem2/ezpz + $ python3 -m pip install -e "ezpz[dev]" + ``` + +
+ + - [**OPTIONAL**] [`NVIDIA/apex`](https://github.com/NVIDIA/apex): + +
install: + + ```bash + $ git clone https://github.com/NVIDIA/apex + $ cd apex + # NOTE: need GCC < 11 for APEX ¯\_(ツ)_/¯ ?? + $ module swap gcc gcc/10.3.0 + $ python3 -m pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./ + ``` + +
+ +
+ + +## 📝 Data Preprocessing + +
Data Pre-Processing: + AuroraGPT is trained on the Dolma dataset (initially v0), now in the process of moving to v6. For more details on the dataset, refer to https://huggingface.co/datasets/allenai/dolma. The dolma dataset downloaded is already preprocessing to remove the duplicates (dedup) and filtering the data (mixing). For more details refer to https://github.com/allenai/dolma/tree/main/docs and https://github.com/vksastry/dolma_alcf/blob/main/ALCF/Readme.md. The data preprocessing of Dolma dataset before training consists of tokenization of the data using a specific tokenizer (LlamaTokenizer is what we are currently using), Use the below script to tokenize the entire dataset. Example shown for Polaris. @@ -207,3 +664,5 @@ The data preprocessing of Dolma dataset before training consists of tokenization cd /eagle/datasets/dolma/utils ./tokenization.sh ``` + +
From 78f378539eb4932a82dced1cfb8262ee608eca28 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 18 Apr 2024 11:45:49 -0500 Subject: [PATCH 185/268] Update README.md --- ALCF/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 5f0fd1b6bd..d405986fdf 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -152,7 +152,7 @@ DS_CONFIG: ds_stage2_mb4_gb96_pp1_bf16.json ZS: 2, CPU_OPTIMIZER: , MB: 4, GB: 96, PP: 1, DTYPE: bf16!!!Please see logs at logs/ds_stage2_nl32_hs4096_mb4_seq4096_gb96_pp1_tp1_bf16/0404090742_x1921c0s0b0n0 !! Caught USE_ACTIVATION_CHECKPOINTING=1 !! !! Caught USE_ACTIVATION_CHECKPOINTING=1 !! -Calling: `setData()` with ./convergence_debug_small.txt +Calling: setData() with ./convergence_debug_small.txt -------------------- Updated environment: DATA_FILE_LIST: ./convergence_debug_small.txt @@ -172,7 +172,7 @@ DATA_CACHE_PATH: /lus/gila/projects/Aurora_deployment/foremans/q4-drop_sunspot/l ! Using /home/foremans/miniconda3/envs/q4-drop/bin/deepspeed /home/foremans/miniconda3/envs/q4-drop/bin/ds_report:4: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html __import__('pkg_resources').require('deepspeed==0.12.3+6ea44d02') -/home/foremans/miniconda3/envs/q4-drop/lib/python3.9/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: ''If you don't plan on using image function +/home/foremans/miniconda3/envs/q4-drop/lib/python3.9/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: ''If you dont plan on using image function ality from `torchvision.io`, you can ignore this warning. Otherwise, there might be something wrong with your environment. Did you have `libjpeg` or `libpng` installed before building `torch vision` from source? warn( From 2dc5aebb1eb4345c1eab32d8247a813c7c6bba98 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 18 Apr 2024 12:05:35 -0500 Subject: [PATCH 186/268] Add `ALCF/data-lists/polaris/*.txt` --- ALCF/data-lists/polaris/data_file_list_c4.txt | 86 + ALCF/data-lists/polaris/data_file_list_cc.txt | 2878 +++++++++++ .../data_file_list_gutenberg-books.txt | 3 + .../polaris/data_file_list_peS2o.txt | 42 + .../polaris/data_file_list_stack-code.txt | 4435 +++++++++++++++++ .../polaris/data_file_list_wiki-en-simple.txt | 2 + 6 files changed, 7446 insertions(+) create mode 100644 ALCF/data-lists/polaris/data_file_list_c4.txt create mode 100644 ALCF/data-lists/polaris/data_file_list_cc.txt create mode 100644 ALCF/data-lists/polaris/data_file_list_gutenberg-books.txt create mode 100644 ALCF/data-lists/polaris/data_file_list_peS2o.txt create mode 100644 ALCF/data-lists/polaris/data_file_list_stack-code.txt 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/eagle/datasets//dolma/data_Llama2Tokenizer/stack-code/vue/v3-0036_text_document +0.172 /eagle/datasets//dolma/data_Llama2Tokenizer/stack-code/vue/v3-0030_text_document +0.172 /eagle/datasets//dolma/data_Llama2Tokenizer/stack-code/vue/v3-0001_text_document +0.172 /eagle/datasets//dolma/data_Llama2Tokenizer/stack-code/vue/v3-0053_text_document +0.172 /eagle/datasets//dolma/data_Llama2Tokenizer/stack-code/vue/v3-0031_text_document +0.172 /eagle/datasets//dolma/data_Llama2Tokenizer/stack-code/xproc/v3-0000_text_document +0.172 /eagle/datasets//dolma/data_Llama2Tokenizer/stack-code/racket/v3-0000_text_document diff --git a/ALCF/data-lists/polaris/data_file_list_wiki-en-simple.txt b/ALCF/data-lists/polaris/data_file_list_wiki-en-simple.txt new file mode 100644 index 0000000000..134c1473b1 --- /dev/null +++ b/ALCF/data-lists/polaris/data_file_list_wiki-en-simple.txt @@ -0,0 +1,2 @@ +0.0045 /eagle/datasets//dolma/data_Llama2Tokenizer/wiki-en-simple//en_simple_wiki-0000_text_document +0.0045 /eagle/datasets//dolma/data_Llama2Tokenizer/wiki-en-simple//en_simple_wiki-0001_text_document From 27f66fd87053c0f3764e4dedc9afe8f3fd65c963 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 19 Apr 2024 11:35:52 -0500 Subject: [PATCH 187/268] Add support for DeepSpeed `FusedLamb` optimizer --- megatron/arguments.py | 7 +- megatron/optimizer/__init__.py | 146 +++++++++++++++++++++++++++++++-- 2 files changed, 144 insertions(+), 9 deletions(-) diff --git a/megatron/arguments.py b/megatron/arguments.py index b982337f51..70dfa88ef6 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -923,10 +923,15 @@ def _add_training_args(parser): 'adam', 'adamw', 'sgd', + 'ds.fusedlamb', 'apex.adam', 'apex.sgd', 'adamwschedulefree', - 'sgdschedulefree' + 'sgdschedulefree', + 'galoreadamw', + 'adam8bit', + 'galoreadamw8bit', + 'galoreadamw8bitperlayer' ], help='Optimizer function' ) diff --git a/megatron/optimizer/__init__.py b/megatron/optimizer/__init__.py index 6dfd0ea40f..80adeb8521 100644 --- a/megatron/optimizer/__init__.py +++ b/megatron/optimizer/__init__.py @@ -3,6 +3,7 @@ from deepspeed.accelerator import get_accelerator import torch +from typing import Callable, Any from megatron import get_args from .distrib_optimizer import DistributedOptimizer @@ -10,19 +11,60 @@ from .optimizer import Float16OptimizerWithFloat16Params, FP32Optimizer -def get_param_groups(modules, - no_weight_decay_cond, - scale_lr_cond, - lr_mult): - """creates param groups based on weight decay condition (regularized vs non regularized) - and learning rate scale condition (args.lr vs lr_mult * args.lr) - scale_lr_cond is used during finetuning where head of the network requires a scaled - version of the base learning rate. +import ezpz as ez +RANK = ez.get_rank() + + +def get_param_groups( + modules: torch.nn.Module | iter[torch.nn.Module], + no_weight_decay_cond: Callable[[str, torch.Tensor], bool], + scale_lr_cond: Callable[[str, torch.Tensor], bool], + lr_mult: Any, + use_galore: bool = False, +): + """ + Creates param groups (regularized vs non) based on: + + - weight decay condition. + - learning rate scale condition (args.lr vs lr_mult * args.lr) + - scale_lr_cond is used during finetuning, where head of the network + requires a scaled version of the base learning rate. + # if 'galore' in args.optimizer.lower(): + # # make parameters with "rank" to a single group, if param_name has "mlp" or "attn" + # galore_params = [] + # target_modules_list = ["attn", "mlp"] + # # for module_name, module in param_groups: + # for group_id, group in enumerate(param_groups): + # for param, p in enumerate(group['params']): + # if not isinstance(module, torch.nn.Linear): + # continue + # if not any(target_key in module_name for target_key in target_modules_list): + # continue + # print('enable GaLore for weights in module: ', module_name) + # galore_params.append(module.weight) + # id_galore_params = [id(p) for p in galore_params] + # # make parameters without "rank" to another group + # regular_params = [p for p in param_groups if id(p) not in id_galore_params] + # # then call galore_adamw + # param_groups = [ + # { + # 'params': regular_params + # }, + # { + # 'params': galore_params, + # 'rank': RANK, + # 'update_proj_gap': args.update_proj_gap, + # 'scale': args.galore_scale, + # 'proj_type': args.proj_type + # } + # ] """ wd_no_scale_lr = [] wd_scale_lr = [] no_wd_no_scale_lr = [] no_wd_scale_lr = [] + galore_params = [] + target_modules_list = ["attn", "mlp"] for module in modules: for name, param in module.named_parameters(): if not param.requires_grad: @@ -83,6 +125,7 @@ def get_megatron_optimizer( param_groups = split_params_into_different_moe_groups_for_optimizer( param_groups ) + if args.cpu_optimizer: assert args.optimizer == 'adam', 'CPU offloading is for Adam' if args.cpu_torch_adam: @@ -97,6 +140,93 @@ def get_megatron_optimizer( betas=(args.adam_beta1, args.adam_beta2), eps=args.adam_eps, ) + + elif args.optimizer.lower() == "galore_adamw": + from galore_torch import GaLoreAdamW, GaLoreAdamW8bit + # redefine way to call galore_adamw + optimizer = GaLoreAdamW(param_groups, lr=args.lr, weight_decay=args.weight_decay) + elif args.optimizer.lower() == "galore_adamw": + # redefine way to call galore_adamw + optimizer = GaLoreAdamW(param_groups, lr=args.lr, weight_decay=args.weight_decay) + # implement adafactor + elif args.optimizer.lower() == "adafactor": + import transformers + args.beta1 = None if args.beta1 == 0.0 else args.beta1 + optimizer = transformers.optimization.Adafactor( + param_groups, + lr=args.lr, + eps=(1e-30, 1e-3), + clip_threshold=1.0, + decay_rate=-0.8, + beta1=args.beta1, + weight_decay=args.weight_decay, + relative_step=False, + scale_parameter=False, + warmup_init=False, + ) + # low-rank adafactor + elif args.optimizer.lower() == "galore_adafactor": + args.beta1 = None if args.beta1 == 0.0 else args.beta1 + optimizer = GaLoreAdafactor( + param_groups, + lr=args.lr, + eps=(1e-30, 1e-3), + clip_threshold=1.0, + decay_rate=-0.8, + beta1=args.beta1, + weight_decay=args.weight_decay, + relative_step=False, + scale_parameter=False, + warmup_init=False, + ) + # 8-bit Adam + elif args.optimizer.lower() == "adam8bit": + import bitsandbytes as bnb + optimizer = bnb.optim.Adam8bit(param_groups, lr=args.lr, weight_decay=args.weight_decay) + elif args.optimizer.lower() == "galore_adamw8bit": + optimizer = GaLoreAdamW8bit(param_groups, lr=args.lr, weight_decay=args.weight_decay) + elif args.optimizer.lower() == 'galore_adamw8bit_per_layer': + # TODO: seems scheduler call twice in one update step, need to check, for now double the num_training_steps, warmup_steps and update_proj_gap + optimizer_dict = {} + for p in model.parameters(): + if p.requires_grad: + if id(p) in id_galore_params: + optimizer_dict[p] = GaLoreAdamW8bit([{'params': [p], 'rank': args.rank, 'update_proj_gap': args.update_proj_gap * 2, 'scale': args.galore_scale, 'proj_type': args.proj_type}], lr=args.lr, weight_decay=args.weight_decay) + else: + optimizer_dict[p] = bnb.optim.Adam8bit([p], lr=args.lr, weight_decay=args.weight_decay) + # get scheduler dict + scheduler_dict = {} + from galore_torch.peft_pretraining import training_utils + for p in model.parameters(): + if p.requires_grad: + scheduler_dict[p] = training_utils.get_scheculer( + optimizer=optimizer_dict[p], + scheduler_type=args.scheduler, + num_training_steps=args.num_training_steps * 2, + warmup_steps=args.warmup_steps * 2, + min_lr_ratio=args.min_lr_ratio, + ) + + def optimizer_hook(p): + if p.grad is None: + return + optimizer_dict[p].step() + optimizer_dict[p].zero_grad() + scheduler_dict[p].step() + # Register the hook onto every parameter + for p in model.parameters(): + if p.requires_grad: + p.register_post_accumulate_grad_hook(optimizer_hook) + layer_wise_flag = True + elif str(args.optimizer).lower() == 'ds.fusedlamb': + from deepspeed.ops.lamb import FusedLamb + optimizer = FusedLamb( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps, + ) elif str(args.optimizer).lower() == 'adamwschedulefree': import schedulefree optimizer = schedulefree.AdamWScheduleFree( From fc1b347ca8e6c246309e43fa1a8600ee81b4de68 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 19 Apr 2024 12:20:58 -0500 Subject: [PATCH 188/268] Add `ALCF/data-lists/sunspot/*.txt` --- ...erg-books.txt => data_file_list_books.txt} | 0 ...tack-code.txt => data_file_list_stack.txt} | 0 ...-en-simple.txt => data_file_list_wiki.txt} | 0 .../sunspot/data_file_list_books.txt | 3 + ALCF/data-lists/sunspot/data_file_list_c4.txt | 86 + ALCF/data-lists/sunspot/data_file_list_cc.txt | 2880 +++++++++++++++++ .../sunspot/data_file_list_peS2o.txt | 26 + .../sunspot/data_file_list_reddit.txt | 78 + .../sunspot/data_file_list_stack.txt | 149 + .../sunspot/data_file_list_wiki.txt | 2 + 10 files changed, 3224 insertions(+) rename ALCF/data-lists/polaris/{data_file_list_gutenberg-books.txt => data_file_list_books.txt} (100%) rename ALCF/data-lists/polaris/{data_file_list_stack-code.txt => data_file_list_stack.txt} (100%) rename ALCF/data-lists/polaris/{data_file_list_wiki-en-simple.txt => data_file_list_wiki.txt} (100%) create mode 100644 ALCF/data-lists/sunspot/data_file_list_books.txt create mode 100644 ALCF/data-lists/sunspot/data_file_list_c4.txt create mode 100644 ALCF/data-lists/sunspot/data_file_list_cc.txt create mode 100644 ALCF/data-lists/sunspot/data_file_list_peS2o.txt create mode 100644 ALCF/data-lists/sunspot/data_file_list_reddit.txt create mode 100644 ALCF/data-lists/sunspot/data_file_list_stack.txt create mode 100644 ALCF/data-lists/sunspot/data_file_list_wiki.txt diff --git a/ALCF/data-lists/polaris/data_file_list_gutenberg-books.txt b/ALCF/data-lists/polaris/data_file_list_books.txt similarity index 100% rename from ALCF/data-lists/polaris/data_file_list_gutenberg-books.txt rename to ALCF/data-lists/polaris/data_file_list_books.txt diff --git a/ALCF/data-lists/polaris/data_file_list_stack-code.txt b/ALCF/data-lists/polaris/data_file_list_stack.txt similarity index 100% rename from ALCF/data-lists/polaris/data_file_list_stack-code.txt rename to ALCF/data-lists/polaris/data_file_list_stack.txt diff --git a/ALCF/data-lists/polaris/data_file_list_wiki-en-simple.txt b/ALCF/data-lists/polaris/data_file_list_wiki.txt similarity index 100% rename from ALCF/data-lists/polaris/data_file_list_wiki-en-simple.txt rename to ALCF/data-lists/polaris/data_file_list_wiki.txt diff --git a/ALCF/data-lists/sunspot/data_file_list_books.txt b/ALCF/data-lists/sunspot/data_file_list_books.txt new file mode 100644 index 0000000000..9187565a5e --- /dev/null +++ b/ALCF/data-lists/sunspot/data_file_list_books.txt @@ -0,0 +1,3 @@ +0.0031007020167215667 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_Llama2Tokenizer/books-0000_text_document +0.003100207465277759 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/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_Llama2Tokenizer/en_simple_wiki_v0-0000_text_document +0.0018422361471876658 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_Llama2Tokenizer/en_simple_wiki_v0-0001_text_document From 80dc91c416e08cd72ec3db74b49976e2767adead Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 19 Apr 2024 13:17:25 -0500 Subject: [PATCH 189/268] Add support for `--optimizer ipex.{fused}lamb` --- megatron/optimizer/__init__.py | 24 ++++++++++++++++++++++-- 1 file changed, 22 insertions(+), 2 deletions(-) diff --git a/megatron/optimizer/__init__.py b/megatron/optimizer/__init__.py index 80adeb8521..48f2737a06 100644 --- a/megatron/optimizer/__init__.py +++ b/megatron/optimizer/__init__.py @@ -3,7 +3,7 @@ from deepspeed.accelerator import get_accelerator import torch -from typing import Callable, Any +from typing import Callable, Any, Iterable, Union from megatron import get_args from .distrib_optimizer import DistributedOptimizer @@ -16,7 +16,7 @@ def get_param_groups( - modules: torch.nn.Module | iter[torch.nn.Module], + modules: Union[torch.nn.Module, Iterable[torch.nn.Module]], no_weight_decay_cond: Callable[[str, torch.Tensor], bool], scale_lr_cond: Callable[[str, torch.Tensor], bool], lr_mult: Any, @@ -110,6 +110,7 @@ def get_megatron_optimizer( lr_mult=1.0 ): args = get_args() + assert args is not None # Base optimizer. param_groups = get_param_groups( @@ -218,6 +219,25 @@ def optimizer_hook(p): if p.requires_grad: p.register_post_accumulate_grad_hook(optimizer_hook) layer_wise_flag = True + elif str(args.optimizer) == 'ipex.lamb': + from intel_extension_for_pytorch.optim._lamb import Lamb + optimizer = Lamb( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps, + ) + elif str(args.optimizer) == 'ipex.fusedlamb': + from intel_extension_for_pytorch.optim._lamb import Lamb + optimizer = Lamb( + param_groups, + lr=args.lr, + weight_decay=args.weight_decay, + betas=(args.adam_beta1, args.adam_beta2), + eps=args.adam_eps, + fused=True, + ) elif str(args.optimizer).lower() == 'ds.fusedlamb': from deepspeed.ops.lamb import FusedLamb optimizer = FusedLamb( From 36af9fc9cf90c0f41cbb60d920302f10ca9f525e Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 19 Apr 2024 13:17:36 -0500 Subject: [PATCH 190/268] Add support for `--optimizer ipex.{fused}lamb` --- megatron/arguments.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/megatron/arguments.py b/megatron/arguments.py index 70dfa88ef6..702a4bad09 100644 --- a/megatron/arguments.py +++ b/megatron/arguments.py @@ -924,6 +924,8 @@ def _add_training_args(parser): 'adamw', 'sgd', 'ds.fusedlamb', + 'ipex.lamb', + 'ipex.fusedlamb', 'apex.adam', 'apex.sgd', 'adamwschedulefree', From 997c39fb3a80fe684e878fbdd40ab1429f324886 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 19 Apr 2024 16:49:13 -0500 Subject: [PATCH 191/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 25 ++++++++++++++----------- 1 file changed, 14 insertions(+), 11 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 151c3e857a..d124ecb242 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -144,12 +144,13 @@ setArgs() { } # +---------------------------------------+ -# | 1. Git clone `ezpz` (if not found) | -# | 2. Install `ezpz` (if not installed) | +# | 1. Git clone ezpz (if not found) | +# | 2. Install ezpz (if not installed) | # +---------------------------------------+ ezpz() { - if [[ ! -d ezpz ]]; then - git clone https://github.com/saforem2/ezpz + if [[ ! -d "${PBS_O_WORKDIR}/deps/ezpz" ]]; then + mkdir -p "${PBS_O_WORKDIR}/deps" + git clone https://github.com/saforem2/ezpz "${PBS_O_WORKDIR}/deps" else echo "Found ezpz!" fi @@ -157,12 +158,12 @@ ezpz() { echo "Has ezpz installed. Nothing to do." else echo "Does not have ezpz installed. Installing..." - echo "Using $(which python3) to install \`ezpz\`:" - python3 -m pip install -e ezpz > ezpz-install.log 2>&1 + echo "Using $(which python3) to install ezpz:" + python3 -m pip install -e "${PBS_O_WORKDIR}/edps/ezpz" # > ezpz-install.log 2>&1 fi echo "Done with ezpz." - # source ezpz/src/ezpz/bin/savejobenv || exit # > /tmp/savejobenv.log 2>&1 || exit - # source ezpz/src/ezpz/bin/getjobenv || exit + source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit + source ezpz/src/ezpz/bin/getjobenv || exit } # +------------------------------------------------------------------------+ @@ -270,9 +271,11 @@ setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- if [[ $(hostname) == x4* ]]; then # ---- [AURORA] ---- dfl_fallback="/home/foremans/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed/data_file_list_reweighted.txt" elif [[ $(hostname) == x1* ]]; then - dfl_fallback="/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_file_list_reweighted.txt" + dfl_fallback="../ALCF/data-lists/sunspot/data_file_list_books.txt" + # dfl_fallback="/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_file_list_reweighted.txt" elif [[ $(hostname) == x3* ]]; then - dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" + # dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" + dfl_fallback="../ALCF/data-lists/polaris/data_file_list_books.txt" elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then dfl_fallback="${SLURM_SUBMIT_DIR}/genslm-subsample.txt" else @@ -280,7 +283,7 @@ setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- fi dfl="${1:-${dfl_fallback}}" # dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" - printf "Calling: \`setData()\` with %s\n" "${dfl}" + printf "Calling: setData() with %s\n" "${dfl}" ndocs=$(wc -l < "${dfl}") ws=$(sumWeights "${dfl}") dfl_stem=$(echo "${dfl}" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") From e179fe05af7c19e5a9b590be57b0ffad8da38723 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 22 Apr 2024 21:56:57 -0500 Subject: [PATCH 192/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 43 +++++++++++++++++++++++++++++-------------- 1 file changed, 29 insertions(+), 14 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index d124ecb242..216798876b 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -1,5 +1,16 @@ #!/bin/bash --login +if [[ -n "${PBS_O_WORKDIR}" ]]; then + WORKING_DIR="${PBS_O_WORKDIR}" +elif [[ -n "${SLURM_SUBMIT_DIR}" ]]; then + WORKING_DIR="${SLURM_SUBMIT_DIR}" +else + WORKING_DIR="$(realpath $(pwd))" +fi + +export WORKING_DIR="${WORKING_DIR}" +printf "Using WORKING_DIR: %s" ${WORKING_DIR} + printJobInfo() { echo "++++++++++++++++++++++++++++++++++++++++++++++++++" @@ -50,7 +61,7 @@ setParams() { export BE="${CCL}" # BE = CCL export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 - export WORKING_DIR="${PBS_O_WORKDIR}" + # export WORKING_DIR="${PBS_O_WORKDIR}" if [[ -z "${NO_FLASH_ATTN}" ]]; then LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn" fi @@ -62,7 +73,7 @@ setParams() { # export DTYPE=${DTYPE:-bf16} # DTYPE: BF16 ?? export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 - export WORKING_DIR="${PBS_O_WORKDIR}" + # export WORKING_DIR="${PBS_O_WORKDIR}" if [[ -z "${NO_FLASH_ATTN}" ]]; then LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" fi @@ -73,7 +84,7 @@ setParams() { export BE="${NCCL}" export DTYPE="${DTYPE:-bf16}" MICRO_BATCH="${MICRO_BATCH:-8}" - export WORKING_DIR="${SLURM_SUBMIT_DIR}" + # export WORKING_DIR="${SLURM_SUBMIT_DIR}" if [[ -z "${NO_FLASH_ATTN}" ]]; then LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" fi @@ -162,8 +173,8 @@ ezpz() { python3 -m pip install -e "${PBS_O_WORKDIR}/edps/ezpz" # > ezpz-install.log 2>&1 fi echo "Done with ezpz." - source ezpz/src/ezpz/bin/savejobenv > /tmp/savejobenv.log 2>&1 || exit - source ezpz/src/ezpz/bin/getjobenv || exit + source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv" > /tmp/savejobenv.log 2>&1 || exit + source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv" || exit } # +------------------------------------------------------------------------+ @@ -236,11 +247,15 @@ setEnv() { fi # ----- [Polaris] --------------------------------------- elif [[ $(hostname) == x3* ]]; then - echo "Running on Polaris !!" - # ---- [load conda] --------------------- - module load conda/2023-10-04; conda activate cu118-pt221 ; unset PYTHONUSERBASE - if [[ -d "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221" ]]; then - source "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221/bin/activate" + if [[ "${PBS_O_HOST}" == sirius* ]]; then + export MACHINE="Running on Sirius !!" + else + echo "Running on Polaris !!" + # ---- [load conda] --------------------- + # module load conda/2023-10-04; conda activate cu118-pt221 ; unset PYTHONUSERBASE + if [[ -d "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221" ]]; then + source "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221/bin/activate" + fi fi elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then echo "Running on Perlmutter !!" @@ -254,8 +269,8 @@ setEnv() { } makeHostfiles() { - source ezpz/src/ezpz/bin/savejobenv || exit #> /tmp/savejobenv.log 2>&1 & - source ezpz/src/ezpz/bin/getjobenv || exit + # source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv" || exit #> /tmp/savejobenv.log 2>&1 & + # source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv" || exit export GPUS_PER_NODE="${GPUS_PER_NODE:-${NGPU_PER_HOST:-${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}}}" # ---- Make MPICH hostfile ---------------- hf="${HOSTFILE:-${PBS_NODEFILE}}" @@ -271,11 +286,11 @@ setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- if [[ $(hostname) == x4* ]]; then # ---- [AURORA] ---- dfl_fallback="/home/foremans/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed/data_file_list_reweighted.txt" elif [[ $(hostname) == x1* ]]; then - dfl_fallback="../ALCF/data-lists/sunspot/data_file_list_books.txt" + dfl_fallback="${WORKING_DIR}/ALCF/data-lists/sunspot/data_file_list_books.txt" # dfl_fallback="/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_file_list_reweighted.txt" elif [[ $(hostname) == x3* ]]; then # dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" - dfl_fallback="../ALCF/data-lists/polaris/data_file_list_books.txt" + dfl_fallback="${WORKING_DIR}/ALCF/data-lists/polaris/data_file_list_books.txt" elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then dfl_fallback="${SLURM_SUBMIT_DIR}/genslm-subsample.txt" else From 133f24484f302bb8fc439b6bba772eb0dec9653a Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 23 Apr 2024 16:07:10 -0500 Subject: [PATCH 193/268] Remove `apex` deps from `megatron/*` --- megatron/model/__init__.py | 12 +++++++++--- megatron/optimizer/clip_grads.py | 10 +++++++--- megatron/optimizer/distrib_optimizer.py | 7 ++++--- megatron/utils.py | 13 ++++++++----- 4 files changed, 28 insertions(+), 14 deletions(-) diff --git a/megatron/model/__init__.py b/megatron/model/__init__.py index 2306749fcb..141c901ffa 100644 --- a/megatron/model/__init__.py +++ b/megatron/model/__init__.py @@ -1,12 +1,18 @@ # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. -from deepspeed.accelerator.real_accelerator import get_accelerator -if get_accelerator().device_name() == 'cuda': +# from deepspeed.accelerator.real_accelerator import get_accelerator +# if get_accelerator().device_name() == 'cuda': +try: from .fused_layer_norm import MixedFusedLayerNorm as LayerNorm from apex.normalization import MixedFusedRMSNorm as RMSNorm -else: + HAS_APEX = True +except Exception: + HAS_APEX = False from .rmsnorm import RMSNorm from torch.nn import LayerNorm +# else: +# from .rmsnorm import RMSNorm +# from torch.nn import LayerNorm from .distributed import DistributedDataParallel from .bert_model import BertModel diff --git a/megatron/optimizer/clip_grads.py b/megatron/optimizer/clip_grads.py index afec8f220c..b5141d0059 100644 --- a/megatron/optimizer/clip_grads.py +++ b/megatron/optimizer/clip_grads.py @@ -8,10 +8,14 @@ except ModuleNotFoundError: from torch import inf as inf -from deepspeed.accelerator import get_accelerator -if get_accelerator().device_name() == 'cuda': +# from deepspeed.accelerator import get_accelerator +# if get_accelerator().device_name() == 'cuda': +try: from apex.multi_tensor_apply import multi_tensor_applier import amp_C + HAS_APEX = True +except Exception: + HAS_APEX = False from megatron.model.module import param_is_not_shared from megatron.core.tensor_parallel import param_is_not_tensor_parallel_duplicate @@ -71,7 +75,7 @@ def clip_grad_norm_fp32(parameters, grads_for_norm, else: if norm_type == 2.0: - if get_accelerator().device_name() == 'cuda': + if get_accelerator().device_name() == 'cuda' and HAS_APEX: dummy_overflow_buf = torch.cuda.IntTensor([0]) # Use apex's multi-tensor applier for efficiency reasons. # Multi-tensor applier takes a function and a list of list diff --git a/megatron/optimizer/distrib_optimizer.py b/megatron/optimizer/distrib_optimizer.py index 1aeeac3444..10331607d9 100644 --- a/megatron/optimizer/distrib_optimizer.py +++ b/megatron/optimizer/distrib_optimizer.py @@ -2,10 +2,11 @@ """Megatron distributed optimizer.""" -from deepspeed.accelerator import get_accelerator -if get_accelerator().device_name() == 'cuda': +# from deepspeed.accelerator import get_accelerator +# if get_accelerator().device_name() == 'cuda': +try: from apex.optimizers import FusedAdam as Adam -else: +except Exception: from torch.optim import Adam import math diff --git a/megatron/utils.py b/megatron/utils.py index 97294070af..f6a293281a 100644 --- a/megatron/utils.py +++ b/megatron/utils.py @@ -10,8 +10,12 @@ from deepspeed.accelerator import get_accelerator if get_accelerator().device_name() == 'cuda': - from apex.multi_tensor_apply import multi_tensor_applier - import amp_C + try: + from apex.multi_tensor_apply import multi_tensor_applier + import amp_C + HAS_APEX = True + except Exception: + HAS_APEX = False from megatron import ( get_args, @@ -74,15 +78,14 @@ def calc_params_l2_norm(model): # Calculate norm dummy_overflow_buf = get_accelerator().IntTensor([0]) - if get_accelerator().device_name() == 'cuda': - + if get_accelerator().device_name() == 'cuda' and HAS_APEX: norm, _ = multi_tensor_applier( amp_C.multi_tensor_l2norm, dummy_overflow_buf, [params_data], False # no per-parameter norm ) - else : + else: norm = torch.norm(params_data,p=2.0) norm_2 = norm * norm # Sum across all model-parallel GPUs. From 42a27fb40cd5758b3aa8e03bcf94d0e896e45fce Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 23 Apr 2024 16:09:54 -0500 Subject: [PATCH 194/268] Move `generate_config.sh` logic into `ALCF/helpers.sh` --- ALCF/helpers.sh | 179 +++++++++++++++++++++++++++++++++++++++++++-- generate_config.sh | 172 ------------------------------------------- 2 files changed, 173 insertions(+), 178 deletions(-) delete mode 100644 generate_config.sh diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 216798876b..18fe965f82 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -95,7 +95,11 @@ setParams() { export DTYPE="${DTYPE:-bf16}" export OPT="${OPT:-adamw}" export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" - export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} + NHOSTS=$(wc -l < "${HOSTFILE}") + NGPU_PER_HOST=$(python3 -c 'import ezpz as ez; print(ez.get_gpus_per_node())') + export WORLD_SIZE="${WORLD_SIZE:-$(( NHOSTS * NGPU_PER_HOST ))}" + # export WORLD_SIZE="${WORLD_SIZE:-${NGPUS:-$(( ))}}" + # export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} # ---- Llama2 7B Config ------------------------------ export MODEL_KEY="Llama-7B" export HEADS=${HEADS:-${NHEADS:-32}} @@ -207,11 +211,13 @@ setOutput() { buildDSconfig() { # ---- Build DeepSpeed Config --------------------------------- - export DS_CONFIG="ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" + export DS_CONFIG="${WORKING_DIR}/ds-configs/ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" + mkdir -p $(dirname "${DS_CONFIG}") echo "DS_CONFIG: ${DS_CONFIG}" printf "ZS: %s, CPU_OPTIMIZER: %s, MB: %s, GB: %s, PP: %s, DTYPE: %s" "${ZERO_STAGE}" "${CPU_OPTIMIZER}" "${MICRO_BATCH}" "${GLOBAL_BATCH}" "${PP}" "${DTYPE}" - working_dir="${PBS_O_WORKDIR:-${SLURM_SUBMIT_DIR:-$(pwd)}}" - bash "${working_dir}/generate_config.sh" "${DS_CONFIG}" + # working_dir="${PBS_O_WORKDIR:-${SLURM_SUBMIT_DIR:-$(pwd)}}" + generateDSconfig "${DS_CONFIG}" + # bash "${WORKING_DIR}/ALCF/generate_ds_config.sh" "${DS_CONFIG}" # ------------------------------------------------------------- } @@ -302,8 +308,8 @@ setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- ndocs=$(wc -l < "${dfl}") ws=$(sumWeights "${dfl}") dfl_stem=$(echo "${dfl}" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") - dcp="${HERE}/.cache/${dfl_stem}/index-cache" - mkdir -p dcp + dcp=".cache/${dfl_stem}/index-cache" + # mkdir -p dcp export DATA_FILE_LIST="${dfl}" export NUM_DOCS="${ndocs}" export WEIGHT_SUM="${ws}" @@ -319,6 +325,167 @@ setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- echo "--------------------" } +generateDSconfig() { + for v in "$GLOBAL_BATCH" "$MICRO_BATCH" "$GRAD_ACC_STEPS" "$ZERO_STAGE" \ + "$PP" "$DTYPE" + do + if [ -z $v ]; then + echo "Please export required envs before execute $0" + exit 1 + fi + done + if [ $# -ne 1 ]; then + echo "Usage: $0 config_file" + exit 1 + fi + # \"optimizer\": { + # \"type\": \"AdamW\", + # \"params\": { + # \"lr\": ${LR}, + # \"beta1\": 0.9, + # \"beta2\": 0.95, + # \"eps\": 1e-5, + # \"weight_decay\": 1e-1 + # } + # }, + # \"scheduler\": { + # \"type\": \"WarmupLR\", + # \"params\": { + # \"warmup_min_lr\": 0.00003, + # \"warmup_max_lr\": 0.0003, + # \"warmup_num_steps\": 5000 + # } + # }, + extra="" + common="\ + \"train_batch_size\": $GLOBAL_BATCH, + \"train_micro_batch_size_per_gpu\": $MICRO_BATCH, + \"steps_per_print\": 1, + \"gradient_accumulation_steps\": $GRAD_ACC_STEPS, + \"zero_allow_untested_optimizer\": true, + \"gradient_clipping\": 1.0, + \"activation_checkpointing\": { + \"partition_activations\": true, + \"contiguous_memory_optimization\": false + }, + \"wall_clock_breakdown\": false," + flops_profiler="\ + \"flops_profiler\": { + \"enabled\": true, + \"profile_step\": 4, + \"module_depth\": -1, + \"top_modules\": 1, + \"detailed\": true, + \"output_file\": null + }" + if [[ $DTYPE == "bf16" ]]; then + dtype="\ + \"communication_data_type\": \"bf16\", + \"fp16\": { + \"enabled\": false, + \"loss_scale\": 0, + \"loss_scale_window\": 1000, + \"hysteresis\": 2, + \"min_loss_scale\": 1 + }, + \"bfloat16\": { + \"enabled\": true, + \"loss_scale\": 1.0 + }," + elif [[ $DTYPE == "fp16" ]]; then + dtype="\ + \"communication_data_type\": \"fp16\", + \"fp16\": { + \"enabled\": true, + \"loss_scale\": 0, + \"loss_scale_window\": 1000, + \"hysteresis\": 2, + \"min_loss_scale\": 1 + }, + \"bfloat16\": { + \"enabled\": false, + \"loss_scale\": 1.0 + }," + else + dtype="\"communication_data_type\": \"fp32\"," + fi + if [ $ZERO_STAGE == 3 ]; then + zero="\ + \"zero_optimization\": { + \"stage\": 3, + \"reduce_scatter\": false, + \"mics_shard_size\": 4, + \"mics_hierarchical_params_gather\": true, + \"stage3_max_live_parameters\": 3e9, + \"stage3_max_reuse_distance\": 3e9, + \"stage3_param_persistence_threshold\": 1e5, + \"stage3_prefetch_bucket_size\": 5e7, + \"contiguous_gradients\": true, + \"overlap_comm\": true, + \"reduce_bucket_size\": 90000000, + \"sub_group_size\": 1e9, + \"offload_optimizer\": { + \"device\": \"none\", + \"buffer_count\": 4, + \"pipeline_read\": false, + \"pipeline_write\": false, + \"pin_memory\": true + } + }," + # elif [[ $ZERO_STAGE == 2 ]]; then + elif [ "${ZERO_STAGE}" == 2 ] || [ "${ZERO_STAGE}" == 1 ]; then + if [[ -n "${CPU_OPTIMIZER}" ]]; then + echo "!!!! CAUGHT CPU_OPTIMIZER !!!!" + zero="\ + \"zero_optimization\": { + \"stage\": $ZERO_STAGE, + \"offload_optimizer\": { + \"device\": \"cpu\" + } + }," + else + zero="\ + \"zero_optimization\": { + \"stage\": $ZERO_STAGE + }," + fi + # elif [[ $ZERO_STAGE == 1 ]]; then + if [[ $PP > 1 ]]; then + extra="\ + \"data_types\": { + \"grad_accum_dtype\": \"fp32\" + }, + \"comms_logger\": { + \"enabled\": true, + \"verbose\": false, + \"prof_all\": true, + \"debug\": false + }," + else + # echo 'please add the config for zero_stage 1 without pipeline-parallelism' + extra="\ + \"comms_logger\": { + \"enabled\": true, + \"verbose\": false, + \"prof_all\": true, + \"debug\": false + }," + fi + else + echo 'Please add the correct config set!!!' + fi +# flops_profiler must at the end because no ',' is allowed at the end +cat < $1 +{ +$common +$zero +$dtype +$extra +$flops_profiler +} +EOT +} + printBlack() { printf "\e[1;30m%s\e[0m\n" "$@" } diff --git a/generate_config.sh b/generate_config.sh deleted file mode 100644 index b164b5e610..0000000000 --- a/generate_config.sh +++ /dev/null @@ -1,172 +0,0 @@ -#!/bin/bash --login - -for v in "$GLOBAL_BATCH" "$MICRO_BATCH" "$GRAD_ACC_STEPS" "$ZERO_STAGE" \ - "$PP" "$DTYPE" -do - if [ -z $v ]; then - echo "Please export required envs before execute $0" - exit 1 - fi -done - -if [ $# -ne 1 ]; then - echo "Usage: $0 config_file" - exit 1 -fi - -# \"optimizer\": { -# \"type\": \"AdamW\", -# \"params\": { -# \"lr\": ${LR}, -# \"beta1\": 0.9, -# \"beta2\": 0.95, -# \"eps\": 1e-5, -# \"weight_decay\": 1e-1 -# } -# }, -# \"scheduler\": { -# \"type\": \"WarmupLR\", -# \"params\": { -# \"warmup_min_lr\": 0.00003, -# \"warmup_max_lr\": 0.0003, -# \"warmup_num_steps\": 5000 -# } -# }, - -extra="" -common="\ - \"train_batch_size\": $GLOBAL_BATCH, - \"train_micro_batch_size_per_gpu\": $MICRO_BATCH, - \"steps_per_print\": 1, - \"gradient_accumulation_steps\": $GRAD_ACC_STEPS, - \"zero_allow_untested_optimizer\": true, - \"gradient_clipping\": 1.0, - \"activation_checkpointing\": { - \"partition_activations\": true, - \"contiguous_memory_optimization\": false - }, - \"wall_clock_breakdown\": false," - -flops_profiler="\ - \"flops_profiler\": { - \"enabled\": true, - \"profile_step\": 4, - \"module_depth\": -1, - \"top_modules\": 1, - \"detailed\": true, - \"output_file\": null - }" - -if [[ $DTYPE == "bf16" ]]; then -dtype="\ - \"communication_data_type\": \"bfp16\", - \"fp16\": { - \"enabled\": false, - \"loss_scale\": 0, - \"loss_scale_window\": 1000, - \"hysteresis\": 2, - \"min_loss_scale\": 1 - }, - \"bfloat16\": { - \"enabled\": true, - \"loss_scale\": 1.0 - }," -elif [[ $DTYPE == "fp16" ]]; then -dtype="\ - \"communication_data_type\": \"fp16\", - \"fp16\": { - \"enabled\": true, - \"loss_scale\": 0, - \"loss_scale_window\": 1000, - \"hysteresis\": 2, - \"min_loss_scale\": 1 - }, - \"bfloat16\": { - \"enabled\": false, - \"loss_scale\": 1.0 - }," -else - dtype="\"communication_data_type\": \"fp32\"," -fi - -if [ $ZERO_STAGE == 3 ]; then -zero="\ - \"zero_optimization\": { - \"stage\": 3, - \"reduce_scatter\": false, - \"mics_shard_size\": 4, - \"mics_hierarchical_params_gather\": true, - \"stage3_max_live_parameters\": 3e9, - \"stage3_max_reuse_distance\": 3e9, - \"stage3_param_persistence_threshold\": 1e5, - \"stage3_prefetch_bucket_size\": 5e7, - \"contiguous_gradients\": true, - \"overlap_comm\": true, - \"reduce_bucket_size\": 90000000, - \"sub_group_size\": 1e9, - \"offload_optimizer\": { - \"device\": \"none\", - \"buffer_count\": 4, - \"pipeline_read\": false, - \"pipeline_write\": false, - \"pin_memory\": true - } - }," - -# elif [[ $ZERO_STAGE == 2 ]]; then -elif [ "${ZERO_STAGE}" == 2 ] || [ "${ZERO_STAGE}" == 1 ]; then - -if [[ -n "${CPU_OPTIMIZER}" ]]; then -echo "!!!! CAUGHT CPU_OPTIMIZER !!!!" - -zero="\ - \"zero_optimization\": { - \"stage\": $ZERO_STAGE, - \"offload_optimizer\": { - \"device\": \"cpu\" - } - }," - -else -zero="\ - \"zero_optimization\": { - \"stage\": $ZERO_STAGE - }," -fi - -# elif [[ $ZERO_STAGE == 1 ]]; then -if [[ $PP > 1 ]]; then - extra="\ - \"data_types\": { - \"grad_accum_dtype\": \"fp32\" - }, - \"comms_logger\": { - \"enabled\": true, - \"verbose\": false, - \"prof_all\": true, - \"debug\": false - }," -else - # echo 'please add the config for zero_stage 1 without pipeline-parallelism' - extra="\ - \"comms_logger\": { - \"enabled\": true, - \"verbose\": false, - \"prof_all\": true, - \"debug\": false - }," -fi -else - echo 'Please add the correct config set!!!' -fi - -# flops_profiler must at the end because no ',' is allowed at the end -cat < $1 -{ -$common -$zero -$dtype -$extra -$flops_profiler -} -EOT From 3be7efc120849627404da4607f20103089532064 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 23 Apr 2024 16:25:46 -0500 Subject: [PATCH 195/268] Add option to launch with `mpiexec` --- ALCF/helpers.sh | 2 +- pretrain_gpt_alcf.py | 27 ++++++++++++++++----------- train_llama_alcf.sh | 32 ++++++++++++++++++++++++++++---- 3 files changed, 45 insertions(+), 16 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 18fe965f82..be04c08201 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -9,7 +9,7 @@ else fi export WORKING_DIR="${WORKING_DIR}" -printf "Using WORKING_DIR: %s" ${WORKING_DIR} +printf "Using WORKING_DIR: %s\n" ${WORKING_DIR} printJobInfo() { diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 0139330277..6530340c19 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -39,20 +39,19 @@ import ezpz as ez -# ---- SETUP DISTRIBUTED COMMS ---- -# RANK = ez.setup_torch( -# backend='deepspeed', -# port='5432', -# ) -RANK = ez.get_rank() +# ---- [SETUP COMMS] ------------------------ +RANK = ez.setup_torch(backend="deepspeed") +# RANK = ez.get_rank() WORLD_SIZE = ez.get_world_size() +LOCAL_RANK = ez.get_local_rank() DEVICE = ez.get_torch_device() - -# --- TURN OFF LOGGER ON ALL RANK != 0 ---- +if torch.cuda.is_available(): + torch.cuda.set_device(LOCAL_RANK) +# ------------------------------------------- +# --- [TURN OFF LOGGER ON ALL RANK != 0] ---- log = get_logger(__name__) log.setLevel("INFO") if RANK == 0 else log.setLevel("CRITICAL") - -# ---- SETUP WANDB FROM RANK 0 ---------------- +# ---- [SETUP WANDB FROM RANK 0] -------------- WANDB_MODE = os.environ.get('WANDB_MODE', None) DISABLE_WANDB = ( WANDB_MODE is not None and str(WANDB_MODE).lower() == 'disabled' @@ -70,7 +69,7 @@ print('--------------------------------------------------') print(f"Setting up W&B from: {RANK} with {project_name}") print('--------------------------------------------------') - ez.setup_wandb(project_name=project_name) + _ = ez.setup_wandb(project_name=project_name) def model_provider(pre_process=True, post_process=True): @@ -163,6 +162,12 @@ def model_provider(pre_process=True, post_process=True): print_rank_0(80 * '-') see_memory_usage("After Building Model", force=True) if wandb.run is not None: + tbdir = args.tensorboard_dir + # tbdir = args.getattr('tensorboard_dir', None) + if tbdir is not None: + log.info(f'Patching tensorboard from {tbdir}') + wandb.tensorboard.patch(root_logdir=tbdir) + wandb.run.config.update({'num_params': num_params}) if "args" not in wandb.run.config: log.info( diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index ce18842850..09b175b1cd 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -29,7 +29,11 @@ sourceFile "${HERE}/ALCF/helpers.sh" || exit setEnv || exit # 1. load `conda` environment saveDSenv || exit # 2. save env vars to `.deepspeed_env` ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars -makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +if [[ -z "${HOSTFILE}" ]]; then + makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +else + echo "!! USING CUSTOM HOSTFILE FROM: ${HOSTFILE}" +fi setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} @@ -65,10 +69,30 @@ mkdir -p "${TBDIR}" # --num-workers 0 \ # aprun -n "${NGPUS}" -N "${NGPU_PER_HOST}" --pmi=pmix ${PBS_O_WORKDIR}/local_rank.sh - # ${DIST_LAUNCH} $(which python3) ${EXEC} \ # yeet="${DIST_LAUNCH} ./local_rank.sh" + # deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ + # +# export MPICH_GPU_SUPPORT_ENABLED=1 +# export CUDA_DEVICE_MAX_CONNECTIONS=1 +# export NCCL_DEBUG=INFO + # deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ + # +data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" +mkdir -p "${data_cache_path}" + +if [[ -n "${DIST_LAUNCH}" ]]; then + LAUNCHER="${DIST_LAUNCH} python3 ${EXEC}" +else + LAUNCHER="deepspeed --hostfile $hfds --launcher MPICH ${EXEC}" +fi + +rstr=$(printRed "Launching with:") +gstr=$(printGreen " ${LAUNCHER}") +printf "%s %s\n" "${rstr}" "${gstr}" + + # ${DIST_LAUNCH} python3 ${EXEC} \ run_cmd=" - deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ + ${LAUNCHER} \ --$DTYPE \ --optimizer ${OPT} \ --split 100,0,0 \ @@ -103,7 +127,7 @@ run_cmd=" --global-batch-size ${GLOBAL_BATCH} \ --pipeline-model-parallel-size ${PP} \ --num-key-value-heads ${NUM_KV_HEAD} \ - --data-cache-path ${DATA_CACHE_PATH} \ + --data-cache-path ${data_cache_path} \ --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ --tokenizer-model ${TOKENIZER_MODEL} \ ${LLAMA_ARGS} \ From a8a9a591d72f1177a78ca3639c1eebca9515eff8 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 23 Apr 2024 23:01:56 -0500 Subject: [PATCH 196/268] Update `train_llama_alcf.sh` --- train_llama_alcf.sh | 18 ++++++++++++++---- 1 file changed, 14 insertions(+), 4 deletions(-) diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 09b175b1cd..2c5eff2410 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -20,11 +20,14 @@ function sourceFile() { cd "${PBS_O_WORKDIR}" || exit HERE=$(python3 -c 'import os; print(os.getcwd())') export HERE + # ----[1. Assert `./pretrain_gpt_alcf.py` exists:]----------------------------- export EXEC="${HERE}/pretrain_gpt_alcf.py" [ -f "${EXEC}" ] || exit + # ----[2. `source ./ALCF/helpers_alcf.sh`:]------------------------------------ sourceFile "${HERE}/ALCF/helpers.sh" || exit + # ----[3. Call fns from `./ALCF/helpers_alcf.sh`]------------------------------ setEnv || exit # 1. load `conda` environment saveDSenv || exit # 2. save env vars to `.deepspeed_env` @@ -81,16 +84,20 @@ data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" mkdir -p "${data_cache_path}" if [[ -n "${DIST_LAUNCH}" ]]; then - LAUNCHER="${DIST_LAUNCH} python3 ${EXEC}" + LAUNCHER="${DIST_LAUNCH} python3 -Wignore ${EXEC}" else LAUNCHER="deepspeed --hostfile $hfds --launcher MPICH ${EXEC}" fi -rstr=$(printRed "Launching with:") -gstr=$(printGreen " ${LAUNCHER}") -printf "%s %s\n" "${rstr}" "${gstr}" +rstr=$(printRed "Launching with:\n") +mstr=$(printBlue " ${LAUNCHER}") +printf "%s" "${rstr}'" +printf " %s" "${mstr}" +# printf "%s %s\n" "${rstr}" "${mstr}" # ${DIST_LAUNCH} python3 ${EXEC} \ + # --log-num-zeros-in-grad \ + # --log-memory-to-tensorboard \ run_cmd=" ${LAUNCHER} \ --$DTYPE \ @@ -130,6 +137,9 @@ run_cmd=" --data-cache-path ${data_cache_path} \ --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ --tokenizer-model ${TOKENIZER_MODEL} \ + --timing-log-level ${TIMING_LOG_LEVEL} \ + --log-timers-to-tensorboard \ + --log-optimizer-states-to-tensorboard \ ${LLAMA_ARGS} \ $ds_args \ ${gpt_args[*]} \ From 42140d7bd0af08ff718db69c10b34c8af8ba039c Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 23 Apr 2024 23:02:24 -0500 Subject: [PATCH 197/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 1 + 1 file changed, 1 insertion(+) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index be04c08201..06fadf74f3 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -117,6 +117,7 @@ setParams() { export TRAIN_ITER=${TRAIN_ITER:-317892} export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" export SAVE_INTERVAL=${SAVE_INTERVAL:-200} + export TIMING_LOG_LEVEL="${TIMING_LOG_LEVEL:-1}" export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" From fa0c5a66272a2dbb3295a0540c7c544e9e334640 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 13:06:48 -0500 Subject: [PATCH 198/268] Update `ALCF/helpers.sh`, `train_llama_alcf.sh` --- ALCF/helpers.sh | 57 +++++++++++++++++++++++++++++------------ train_llama_alcf.sh | 62 +++++++++++++++------------------------------ 2 files changed, 61 insertions(+), 58 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 06fadf74f3..8e9e508087 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -36,6 +36,19 @@ function setupSrun() { } +function setupLauncher() { + # outdir=$1 + if [[ -n "${DIST_LAUNCH}" && ${LAUNCH_CMD:-"MPICH"} != "deepspeed" ]]; then + export LAUNCH_CMD="${DIST_LAUNCH} python3 -Wignore ${EXEC}" + else + # Assert `./hostfile_deepspeed` exists + export hfds="${WORKING_DIR}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit + export LAUNCH_CMD="deepspeed --hostfile $hfds --launcher MPICH ${EXEC}" + fi + printf "%s" "$(printRed 'Launching with:')" + printf " %s" "$(printMagenta ${LAUNCH_CMD})" +} + function setDSlauncher() { # launcher setting outdir=$1 @@ -159,14 +172,27 @@ setArgs() { export gpt_args } + +function make_ds_hostfile() { + export GPUS_PER_NODE="${GPUS_PER_NODE:-${NGPU_PER_HOST:-${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}}}" + # ---- Make MPICH hostfile ---------------- + hf="${HOSTFILE:-${PBS_NODEFILE}}" + export hostfile_mpich=hostfile_mpich + cat "${hf}" > "${hostfile_mpich}" + # ---- Make DeepSpeed hostfile ------------------- + export hostfile_deepspeed=hostfile_deepspeed + cat "${hf}" > "${hostfile_deepspeed}" + sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" +} + # +---------------------------------------+ # | 1. Git clone ezpz (if not found) | # | 2. Install ezpz (if not installed) | # +---------------------------------------+ ezpz() { - if [[ ! -d "${PBS_O_WORKDIR}/deps/ezpz" ]]; then - mkdir -p "${PBS_O_WORKDIR}/deps" - git clone https://github.com/saforem2/ezpz "${PBS_O_WORKDIR}/deps" + if [[ ! -d "${WORKING_DIR}/deps/ezpz" ]]; then + mkdir -p "${WORKING_DIR}/deps" + git clone https://github.com/saforem2/ezpz "${WORKING_DIR}/deps" else echo "Found ezpz!" fi @@ -175,11 +201,12 @@ ezpz() { else echo "Does not have ezpz installed. Installing..." echo "Using $(which python3) to install ezpz:" - python3 -m pip install -e "${PBS_O_WORKDIR}/edps/ezpz" # > ezpz-install.log 2>&1 + python3 -m pip install -e "${WORKING_DIR}/edps/ezpz" # > ezpz-install.log 2>&1 fi echo "Done with ezpz." source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv" > /tmp/savejobenv.log 2>&1 || exit source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv" || exit + make_ds_hostfile || exit } # +------------------------------------------------------------------------+ @@ -201,7 +228,8 @@ saveDSenv() { setOutput() { # ---- Specify output location -------------------------------- export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" - OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" + # OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" + OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%Y%m%d-%H%M%S)_${WORLD_SIZE}_${HOSTNAME}" export OUTPUT_DIR="${OUTPUT_DIR}" export OUTPUT_LOG="${OUTPUT_DIR}/output.log" export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" @@ -275,18 +303,15 @@ setEnv() { echo "[python] Using: $(which python3)" } + makeHostfiles() { - # source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv" || exit #> /tmp/savejobenv.log 2>&1 & - # source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv" || exit - export GPUS_PER_NODE="${GPUS_PER_NODE:-${NGPU_PER_HOST:-${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}}}" - # ---- Make MPICH hostfile ---------------- - hf="${HOSTFILE:-${PBS_NODEFILE}}" - export hostfile_mpich=hostfile_mpich - cat "${hf}" > "${hostfile_mpich}" - # ---- Make DeepSpeed hostfile ------------------- - export hostfile_deepspeed=hostfile_deepspeed - cat "${hf}" > "${hostfile_deepspeed}" - sed -e "s/$/ slots=${GPUS_PER_NODE}/" -i "${hostfile_deepspeed}" + if [[ -n "${HOSTFILE}" ]]; then + printf "!! USING CUSTOM HOSTFILE FROM: %s" "${HOSTFILE}" + else + make_ds_hostfile + # source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv" || exit #> /tmp/savejobenv.log 2>&1 & + # source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv" || exit + fi } setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 2c5eff2410..af689ab235 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -30,29 +30,24 @@ sourceFile "${HERE}/ALCF/helpers.sh" || exit # ----[3. Call fns from `./ALCF/helpers_alcf.sh`]------------------------------ setEnv || exit # 1. load `conda` environment -saveDSenv || exit # 2. save env vars to `.deepspeed_env` +# saveDSenv || exit # 2. save env vars to `.deepspeed_env` ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars -if [[ -z "${HOSTFILE}" ]]; then - makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` -else - echo "!! USING CUSTOM HOSTFILE FROM: ${HOSTFILE}" -fi + +# if [[ -z "${HOSTFILE}" ]]; then +# makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +# else +# echo "!! USING CUSTOM HOSTFILE FROM: ${HOSTFILE}" +# fi setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} setArgs || exit # 8. specify additional `deepspeed` arguments setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset -setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` +# setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` printJobInfo || exit # 11. print job info +setupLauncher || exit # ----------------------------------------------------------------------------- -# Take custom args -custom_args=" $@" - -# Assert `./hostfile_deepspeed` exists -export hfds="${HERE}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit -TBDIR="${CKPT_DIR}/tensorboard" -mkdir -p "${TBDIR}" # TORCH_DEVICE=$(python3 -c 'import ezpz as ez; print(ez.get_torch_device())') # printf %s "Using TORCH_DEVICE=${TORCH_DEVICE}" @@ -63,44 +58,27 @@ mkdir -p "${TBDIR}" # fi -# source "${HERE}/venvs/polaris/2024-03-14/bin/activate" || exit -# echo "Using $(which python3)" -# --launcher_args='--pmi=pmix' -# deepspeed --hostfile $hfds --launcher ${LAUNCHER} ${EXEC} \ -# ${launch_cmd} \ -# --use-flash-attn-v2 \ -# --num-workers 0 \ - - # aprun -n "${NGPUS}" -N "${NGPU_PER_HOST}" --pmi=pmix ${PBS_O_WORKDIR}/local_rank.sh -# yeet="${DIST_LAUNCH} ./local_rank.sh" - # deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ - # # export MPICH_GPU_SUPPORT_ENABLED=1 # export CUDA_DEVICE_MAX_CONNECTIONS=1 # export NCCL_DEBUG=INFO - # deepspeed --hostfile $hfds --launcher MPICH ${EXEC} \ - # +# +# +# Assert TBDIR exists inside our $CKPT_DIR +TBDIR="${CKPT_DIR}/tensorboard" +mkdir -p "${TBDIR}" + data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" mkdir -p "${data_cache_path}" +module list -if [[ -n "${DIST_LAUNCH}" ]]; then - LAUNCHER="${DIST_LAUNCH} python3 -Wignore ${EXEC}" -else - LAUNCHER="deepspeed --hostfile $hfds --launcher MPICH ${EXEC}" -fi - -rstr=$(printRed "Launching with:\n") -mstr=$(printBlue " ${LAUNCHER}") -printf "%s" "${rstr}'" -printf " %s" "${mstr}" -# printf "%s %s\n" "${rstr}" "${mstr}" +# Take custom args +custom_args=" $@" - # ${DIST_LAUNCH} python3 ${EXEC} \ # --log-num-zeros-in-grad \ # --log-memory-to-tensorboard \ run_cmd=" - ${LAUNCHER} \ - --$DTYPE \ + ${LAUNCH_CMD} \ + --${DTYPE} \ --optimizer ${OPT} \ --split 100,0,0 \ --log-interval 1 \ From 4b9c2f2c966664e0f67a4840b3d88ab6691c76d1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 13:11:22 -0500 Subject: [PATCH 199/268] Add `ALCF/sunspot-env.sh` --- ALCF/sunspot-env.sh | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) create mode 100644 ALCF/sunspot-env.sh diff --git a/ALCF/sunspot-env.sh b/ALCF/sunspot-env.sh new file mode 100644 index 0000000000..e97545aafe --- /dev/null +++ b/ALCF/sunspot-env.sh @@ -0,0 +1,27 @@ +#!/bin/bash --login + +export CCL_OP_SYNC=1 # Required by current oneCCL (HPCS-8067) +export CCL_PROCESS_LAUNCHER=pmix # Required by Aurora mpich +export FI_PROVIDER=cxi # Required by Aurora mpich +export PALS_PMI=pmix # Required by Aurora mpich +export CCL_ATL_TRANSPORT=mpi # Required by Aurora mpich +export FI_MR_CACHE_MONITOR=disabled # Required by Aurora mpich (HPCS-6501) +export CCL_SKIP_SCHEDULER=1 # Required by current oneCCL, will remove when set by default +export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1 +export CCL_TOPO_COLOR="card:{0,1},{2,3},{4,5},{6,7},{8,9},{10,11};plane:{0,3,4,6,8,11},{1,2,5,7,9,10}" +export UR_L0_IN_ORDER_BARRIER_BY_SIGNAL=0 # Required by current oneCCL + + +export LLM_DK_DIR=/home/$(whoami)/q4-drop_sunspot/llm.devkit + +module load oneapi/release/2023.12.15.001 +unset MPIR_CVAR_CH4_COLL_SELECTION_TUNING_JSON_FILE +unset MPIR_CVAR_COLL_SELECTION_TUNING_JSON_FILE +unset MPIR_CVAR_CH4_POSIX_COLL_SELECTION_TUNING_JSON_FILE + + +module use /home/ftartagl/graphics-compute-runtime/modulefiles +module load graphics-compute-runtime/agama-ci-devel-736.9 +source /home/$(whoami)/q4-drop_sunspot/llm.devkit/torch-ccl/third_party/oneCCL/build/_install/env/vars.sh +module load gcc/12.1.0 +module unload intel_compute_runtime/release/agama-devel-647 From c2e9147546e03cfdb0afe85e6ed8317eecd7ea66 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 13:34:10 -0500 Subject: [PATCH 200/268] Update `train_llama_alcf.sh`, `ALCF/helpers.sh` --- ALCF/helpers.sh | 53 ++++++++++++++++++++++++++++----------------- train_llama_alcf.sh | 5 ++++- 2 files changed, 37 insertions(+), 21 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 8e9e508087..2e34e6c425 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -1,11 +1,15 @@ #!/bin/bash --login +# +# set -euxo pipefail if [[ -n "${PBS_O_WORKDIR}" ]]; then WORKING_DIR="${PBS_O_WORKDIR}" elif [[ -n "${SLURM_SUBMIT_DIR}" ]]; then WORKING_DIR="${SLURM_SUBMIT_DIR}" else - WORKING_DIR="$(realpath $(pwd))" + echo "Unable to detect PBS or SLURM working directory info..." + WORKING_DIR=$(python3 -c 'import os; print(os.getcwd())') + echo "Using ${WORKING_DIR} as working directory..." fi export WORKING_DIR="${WORKING_DIR}" @@ -14,7 +18,7 @@ printf "Using WORKING_DIR: %s\n" ${WORKING_DIR} printJobInfo() { echo "++++++++++++++++++++++++++++++++++++++++++++++++++" - echo "- MPICH_DIR=$MPICH_DIR" + echo "- MPICH_DIR=${MPICH_DIR:-${MPI_ROOT}}" echo "- Using $(which python3)" echo "- WORLD_SIZE:${WORLD_SIZE}" echo "- NCCL: ${NCCL:-nccl}" @@ -68,6 +72,7 @@ setParams() { LLAMA_ARGS="" # ---- [Parallelism Settings] -------------------------------------------- # -------- [Aurora] ---- || ----- [SunSpot] ------------ + NO_FLASH_ATTN="${NO_FLASH_ATTN:-0}" if [[ $(hostname) == x4* || $(hostname) == x1* ]]; then TP=${TP:-1} # TP = 1 export CCL=${CCL:-ccl} # CCL @@ -75,7 +80,7 @@ setParams() { export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 # export WORKING_DIR="${PBS_O_WORKDIR}" - if [[ -z "${NO_FLASH_ATTN}" ]]; then + if [[ "${NO_FLASH_ATTN}" != 0 ]]; then LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn" fi # -------- [Polaris] ----------------------------------- @@ -87,7 +92,8 @@ setParams() { export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 # export WORKING_DIR="${PBS_O_WORKDIR}" - if [[ -z "${NO_FLASH_ATTN}" ]]; then + # if [[ -z "${NO_FLASH_ATTN}" ]]; then + if [[ "${NO_FLASH_ATTN}" != 0 ]]; then LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" fi # -------- [Perlmutter] --------------------------------- @@ -98,7 +104,8 @@ setParams() { export DTYPE="${DTYPE:-bf16}" MICRO_BATCH="${MICRO_BATCH:-8}" # export WORKING_DIR="${SLURM_SUBMIT_DIR}" - if [[ -z "${NO_FLASH_ATTN}" ]]; then + # if [[ -z "${NO_FLASH_ATTN}" ]]; then + if [[ "${NO_FLASH_ATTN}" != 0 ]]; then LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" fi fi @@ -192,20 +199,21 @@ function make_ds_hostfile() { ezpz() { if [[ ! -d "${WORKING_DIR}/deps/ezpz" ]]; then mkdir -p "${WORKING_DIR}/deps" - git clone https://github.com/saforem2/ezpz "${WORKING_DIR}/deps" + git clone https://github.com/saforem2/ezpz "${WORKING_DIR}/deps/ezpz" else echo "Found ezpz!" fi + echo "Done with clone. Now, checking if ezpz is installed..." if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then echo "Has ezpz installed. Nothing to do." else echo "Does not have ezpz installed. Installing..." echo "Using $(which python3) to install ezpz:" - python3 -m pip install -e "${WORKING_DIR}/edps/ezpz" # > ezpz-install.log 2>&1 + python3 -m pip install -e "${WORKING_DIR}/deps/ezpz" # > ezpz-install.log 2>&1 fi echo "Done with ezpz." - source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv" > /tmp/savejobenv.log 2>&1 || exit - source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv" || exit + source ${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv # > /dev/null 2>&1 #> /tmp/savejobenv.log 2>&1 || exit + source ${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv || exit make_ds_hostfile || exit } @@ -240,10 +248,11 @@ setOutput() { buildDSconfig() { # ---- Build DeepSpeed Config --------------------------------- + export CPU_OPTIMIZER="${CPU_OPTIMIZER:-0}" export DS_CONFIG="${WORKING_DIR}/ds-configs/ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" mkdir -p $(dirname "${DS_CONFIG}") echo "DS_CONFIG: ${DS_CONFIG}" - printf "ZS: %s, CPU_OPTIMIZER: %s, MB: %s, GB: %s, PP: %s, DTYPE: %s" "${ZERO_STAGE}" "${CPU_OPTIMIZER}" "${MICRO_BATCH}" "${GLOBAL_BATCH}" "${PP}" "${DTYPE}" + printf "ZS: %s, , MB: %s, GB: %s, PP: %s, DTYPE: %s" "${ZERO_STAGE}" "${CPU_OPTIMIZER}" "${MICRO_BATCH}" "${GLOBAL_BATCH}" "${PP}" "${DTYPE}" # working_dir="${PBS_O_WORKDIR:-${SLURM_SUBMIT_DIR:-$(pwd)}}" generateDSconfig "${DS_CONFIG}" # bash "${WORKING_DIR}/ALCF/generate_ds_config.sh" "${DS_CONFIG}" @@ -269,16 +278,19 @@ sumFiles() { setEnv() { # ---- [SunSpot] ------- || ---- [Aurora] -------------- if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then - PBS_PARENT=$(dirname ${PBS_O_WORKDIR}) - echo "Sourcing ${PBS_PARENT}/setenv.sh..." - source "${PBS_PARENT}/setenv.sh" || exit + # PBS_PARENT=$(dirname ${PBS_O_WORKDIR}) + # echo "Sourcing ${PBS_PARENT}/setenv.sh..." + # source "${PBS_PARENT}/setenv.sh" || exit + source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit # ----- [Aurora] ----------------------------------- - if [[ $(hostname) == x4* ]]; then - eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate anl_release_q4v2 - # ----- [SunSpot] ---------------------------------- - elif [[ $(hostname) == x1* ]]; then - echo "Running on SunSpot !!" - eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate q4-drop + if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + if [[ $(hostname) == x4* ]]; then + eval "$(conda shell.zsh hook)" && conda activate anl_release_q4v2 + # ----- [SunSpot] ---------------------------------- + elif [[ $(hostname) == x1* ]]; then + echo "Running on SunSpot !!" + eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate q4-drop + fi fi # ----- [Polaris] --------------------------------------- elif [[ $(hostname) == x3* ]]; then @@ -460,7 +472,8 @@ generateDSconfig() { }," # elif [[ $ZERO_STAGE == 2 ]]; then elif [ "${ZERO_STAGE}" == 2 ] || [ "${ZERO_STAGE}" == 1 ]; then - if [[ -n "${CPU_OPTIMIZER}" ]]; then + # if [[ -n "${CPU_OPTIMIZER}" ]]; then + if [[ "${CPU_OPTIMIZER}" != 0 ]]; then echo "!!!! CAUGHT CPU_OPTIMIZER !!!!" zero="\ \"zero_optimization\": { diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index af689ab235..7731df52dd 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -5,6 +5,8 @@ #PBS -l select=48 #PBS -l filesystems=eagle:home +set -euxo pipefail + function sourceFile() { fp="$1" echo "source-ing ${fp}" @@ -125,7 +127,8 @@ run_cmd=" |& tee ${OUTPUT_LOG} " -echo "! Using $(which deepspeed)" +# ds_exec +# echo "! Using $(which deepspeed)" ds_report echo "${run_cmd}" From 41a3f3523a29a18462d926bbec5cd86c278bfedf Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 14:10:04 -0500 Subject: [PATCH 201/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 2e34e6c425..d0716739af 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -43,7 +43,7 @@ function setupSrun() { function setupLauncher() { # outdir=$1 if [[ -n "${DIST_LAUNCH}" && ${LAUNCH_CMD:-"MPICH"} != "deepspeed" ]]; then - export LAUNCH_CMD="${DIST_LAUNCH} python3 -Wignore ${EXEC}" + export LAUNCH_CMD="${DIST_LAUNCH} --cpu-bind depth -d 16 python3 -Wignore ${EXEC}" else # Assert `./hostfile_deepspeed` exists export hfds="${WORKING_DIR}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit From 71c725ec9aab266d25963fa0d8a37d15c582d7f2 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 14:17:00 -0500 Subject: [PATCH 202/268] Much faster check if `ezpz` installed Replace: ```bash if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then ``` with ```bash if python3 -c "import sys; any(['ezpz' in s for s in sys.path])" 2> '/dev/null'; then ``` in `ezpz()` from `ALCF/helpers.sh` --- ALCF/helpers.sh | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index d0716739af..a097d72efc 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -204,7 +204,8 @@ ezpz() { echo "Found ezpz!" fi echo "Done with clone. Now, checking if ezpz is installed..." - if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then + # if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then + if python3 -c "import sys; any(['ezpz' in s for s in sys.path])" 2> '/dev/null'; then echo "Has ezpz installed. Nothing to do." else echo "Does not have ezpz installed. Installing..." From ae0b4d8b40aec3d43c1842442166829463563d15 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 15:30:50 -0500 Subject: [PATCH 203/268] Add option to run in `DEBUG` mode (i.e. `set -euxo pipefail`) --- ALCF/helpers.sh | 84 ++++++++++++++++++++++++--------------------- train_llama_alcf.sh | 5 ++- 2 files changed, 49 insertions(+), 40 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index a097d72efc..fdd42b56b8 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -28,7 +28,7 @@ printJobInfo() { } -function setupSrun() { +setupSrun() { if [[ $(hostname) == login* || $(hostname) == nid* ]]; then export NHOSTS="${SLURM_NNODES:-1}" export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" @@ -40,7 +40,7 @@ function setupSrun() { } -function setupLauncher() { +setupLauncher() { # outdir=$1 if [[ -n "${DIST_LAUNCH}" && ${LAUNCH_CMD:-"MPICH"} != "deepspeed" ]]; then export LAUNCH_CMD="${DIST_LAUNCH} --cpu-bind depth -d 16 python3 -Wignore ${EXEC}" @@ -53,7 +53,7 @@ function setupLauncher() { printf " %s" "$(printMagenta ${LAUNCH_CMD})" } -function setDSlauncher() { +setDSlauncher() { # launcher setting outdir=$1 export hfds="$outdir/hostfile_deepspeed" @@ -70,20 +70,23 @@ function setDSlauncher() { setParams() { LLAMA_ARGS="" - # ---- [Parallelism Settings] -------------------------------------------- - # -------- [Aurora] ---- || ----- [SunSpot] ------------ - NO_FLASH_ATTN="${NO_FLASH_ATTN:-0}" + # +----[Parallelism Settings] -------------------------------------------+ + # +------[Aurora]--------||-------[SunSpot]-------------+ if [[ $(hostname) == x4* || $(hostname) == x1* ]]; then TP=${TP:-1} # TP = 1 export CCL=${CCL:-ccl} # CCL export BE="${CCL}" # BE = CCL export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 - # export WORKING_DIR="${PBS_O_WORKDIR}" - if [[ "${NO_FLASH_ATTN}" != 0 ]]; then - LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn" + ####################################################### + # if NO_FLASH_ATTN is NON-empty; then NO FLASH ATTN !! + if [[ -n "${NO_FLASH_ATTN-}" ]]; then + echo "Not using flash-attn!!" + else + LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-builder" fi - # -------- [Polaris] ----------------------------------- + ####################################################### + # +--------[Polaris]-----------------------------------+ elif [[ $(hostname) == x3* ]]; then TP=${TP:-2} # TP = 2 export NCCL=${NCCL:-nccl} # NCCL @@ -91,61 +94,64 @@ setParams() { # export DTYPE=${DTYPE:-bf16} # DTYPE: BF16 ?? export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 - # export WORKING_DIR="${PBS_O_WORKDIR}" - # if [[ -z "${NO_FLASH_ATTN}" ]]; then - if [[ "${NO_FLASH_ATTN}" != 0 ]]; then + if [[ -n "${NO_FLASH_ATTN-}" ]]; then + echo "Not using flash-attn!!" + else LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" fi - # -------- [Perlmutter] --------------------------------- + # +--------[Perlmutter]---------------------------------+ elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then TP="${TP:-2}" export NCCL="${NCCL:-nccl}" export BE="${NCCL}" export DTYPE="${DTYPE:-bf16}" MICRO_BATCH="${MICRO_BATCH:-8}" - # export WORKING_DIR="${SLURM_SUBMIT_DIR}" - # if [[ -z "${NO_FLASH_ATTN}" ]]; then - if [[ "${NO_FLASH_ATTN}" != 0 ]]; then + if [[ -n "${NO_FLASH_ATTN-}" ]]; then + echo "Not using flash-attn!!" + else LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" fi fi - # ------------------------------------------------------------------------ + # +----------------------------------------------------------------------+ export TP="${TP}" export PP="${PP:-1}" export DTYPE="${DTYPE:-bf16}" export OPT="${OPT:-adamw}" export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" NHOSTS=$(wc -l < "${HOSTFILE}") - NGPU_PER_HOST=$(python3 -c 'import ezpz as ez; print(ez.get_gpus_per_node())') + if [[ -z "${NGPU_PER_HOST-}" ]]; then + NGPU_PER_HOST=$(python3 -c 'import ezpz as ez; print(ez.get_gpus_per_node())') + fi export WORLD_SIZE="${WORLD_SIZE:-$(( NHOSTS * NGPU_PER_HOST ))}" # export WORLD_SIZE="${WORLD_SIZE:-${NGPUS:-$(( ))}}" # export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} - # ---- Llama2 7B Config ------------------------------ + # +---[Llama2 7B Config]-----------------------------+ export MODEL_KEY="Llama-7B" export HEADS=${HEADS:-${NHEADS:-32}} export NLAYERS=${NLAYERS:-${NUM_LAYERS:-32}} export HIDDEN=${HIDDEN:-4096} export NUM_KV_HEAD=${NUM_KV_HEAD:-8} export FFN_HIDDEN_SIZE=${FFN_HIDDEN_SIZE:-11008} - # ---- Run Settings ---------------------------------- - export LR=${LR:-0.0003} + # +---[Run Settings]------------------------------------------------------+ + export LR=${LR:-0.0003} # LEARNING_RATE export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 - export ZERO_STAGE=${ZERO_STAGE:-2} - export MICRO_BATCH=${MICRO_BATCH:-8} - export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} - export EVAL_ITERS="${EVAL_ITERS:-10}" - export TRAIN_ITER=${TRAIN_ITER:-317892} - export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" - export SAVE_INTERVAL=${SAVE_INTERVAL:-200} - export TIMING_LOG_LEVEL="${TIMING_LOG_LEVEL:-1}" - export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} - export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) - export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" - tm="${WORKING_DIR}/ALCF/tokenizer.model" - export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" - export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" + export ZERO_STAGE=${ZERO_STAGE:-2} # ZERO OFFLOADING STAGE + export MICRO_BATCH=${MICRO_BATCH:-8} # MICRO BATCH SIZE + export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} # GRADIENT ACCUMULATION STEPS + export EVAL_ITERS="${EVAL_ITERS:-10}" # NUMBER OF EVAL ITERS TO RUN + export TRAIN_ITER=${TRAIN_ITER:-317892} # NUMBER OF TRAIN ITERS + export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" # HOW FREQUENTLY TO RUN EVAL + export SAVE_INTERVAL=${SAVE_INTERVAL:-200} # HOW FREQUENTLY TO SAVE CKPTS + export TIMING_LOG_LEVEL="${TIMING_LOG_LEVEL:-1}" # TIMING VERBOSITY IN LOGS + export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # USE ACTIVATION CHECKPOINTING ? + export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) # MAX GLOBAL BATCH SIZE + export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" # WILL USE MAX IF NOT SET IN ENVIRONMENT + tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model + export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" # USE TOKENIZER_MODEL from env, else fallback from ^ + export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" # STRING FOR IDENTIFYING MODEL + # +----[ADDITIONAL LLAMA SPECIFIC ARGUMENTS]------------------------------ export LLAMA_ARGS="${LLAMA_ARGS} --no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" - # ---------------------------------------------------- + # +----------------------------------------------------------------------+ } @@ -180,7 +186,7 @@ setArgs() { } -function make_ds_hostfile() { +make_ds_hostfile() { export GPUS_PER_NODE="${GPUS_PER_NODE:-${NGPU_PER_HOST:-${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}}}" # ---- Make MPICH hostfile ---------------- hf="${HOSTFILE:-${PBS_NODEFILE}}" @@ -213,7 +219,7 @@ ezpz() { python3 -m pip install -e "${WORKING_DIR}/deps/ezpz" # > ezpz-install.log 2>&1 fi echo "Done with ezpz." - source ${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv # > /dev/null 2>&1 #> /tmp/savejobenv.log 2>&1 || exit + source ${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv > /dev/null 2>&1 #> /tmp/savejobenv.log 2>&1 || exit source ${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv || exit make_ds_hostfile || exit } diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 7731df52dd..4aac1153c7 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -5,7 +5,10 @@ #PBS -l select=48 #PBS -l filesystems=eagle:home -set -euxo pipefail +if [[ -n "${DEBUG-}" ]]; then + printf "\e[1;31m%s\e[0m\n" "!! RUNNING IN DEBUG MODE !!" + set -euxo pipefail +fi function sourceFile() { fp="$1" From 2d6608a9260cf36ac844d87efd7a4e73b08398de Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 17:00:23 -0500 Subject: [PATCH 204/268] Update `ALCF/data-lists/sunspot/*.txt` --- ALCF/data-lists/sunspot/algebraic.txt | 16 + ALCF/data-lists/sunspot/arxiv.txt | 100 + ALCF/data-lists/sunspot/books.txt | 3 + ALCF/data-lists/sunspot/c4.txt | 171 + ALCF/data-lists/sunspot/cc.txt | 1108 +++++++ .../sunspot/data_file_list_books.txt | 3 - ALCF/data-lists/sunspot/data_file_list_c4.txt | 86 - ALCF/data-lists/sunspot/data_file_list_cc.txt | 2880 ----------------- .../sunspot/data_file_list_peS2o.txt | 26 - .../sunspot/data_file_list_reddit.txt | 78 - .../sunspot/data_file_list_stack.txt | 149 - .../sunspot/data_file_list_wiki.txt | 2 - ALCF/data-lists/sunspot/falcon.txt | 501 +++ ALCF/data-lists/sunspot/megawiki.txt | 262 ++ .../sunspot/open-web-math-train.txt | 13 + ALCF/data-lists/sunspot/pes2o.txt | 26 + ALCF/data-lists/sunspot/reddit.txt | 78 + ALCF/data-lists/sunspot/stack.txt | 26 + ALCF/data-lists/sunspot/starcoder.txt | 50 + ALCF/data-lists/sunspot/tulu.txt | 66 + ALCF/data-lists/sunspot/wiki.txt | 2 + 21 files changed, 2422 insertions(+), 3224 deletions(-) create mode 100644 ALCF/data-lists/sunspot/algebraic.txt create mode 100644 ALCF/data-lists/sunspot/arxiv.txt create mode 100644 ALCF/data-lists/sunspot/books.txt create mode 100644 ALCF/data-lists/sunspot/c4.txt create mode 100644 ALCF/data-lists/sunspot/cc.txt delete mode 100644 ALCF/data-lists/sunspot/data_file_list_books.txt delete mode 100644 ALCF/data-lists/sunspot/data_file_list_c4.txt delete mode 100644 ALCF/data-lists/sunspot/data_file_list_cc.txt delete mode 100644 ALCF/data-lists/sunspot/data_file_list_peS2o.txt delete mode 100644 ALCF/data-lists/sunspot/data_file_list_reddit.txt delete mode 100644 ALCF/data-lists/sunspot/data_file_list_stack.txt delete mode 100644 ALCF/data-lists/sunspot/data_file_list_wiki.txt create mode 100644 ALCF/data-lists/sunspot/falcon.txt create mode 100644 ALCF/data-lists/sunspot/megawiki.txt create mode 100644 ALCF/data-lists/sunspot/open-web-math-train.txt create mode 100644 ALCF/data-lists/sunspot/pes2o.txt create mode 100644 ALCF/data-lists/sunspot/reddit.txt create mode 100644 ALCF/data-lists/sunspot/stack.txt create mode 100644 ALCF/data-lists/sunspot/starcoder.txt create mode 100644 ALCF/data-lists/sunspot/tulu.txt create mode 100644 ALCF/data-lists/sunspot/wiki.txt diff --git a/ALCF/data-lists/sunspot/algebraic.txt b/ALCF/data-lists/sunspot/algebraic.txt new file mode 100644 index 0000000000..0f25e30498 --- /dev/null +++ b/ALCF/data-lists/sunspot/algebraic.txt @@ -0,0 +1,16 @@ +0.0018520780893211373 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/algebraic-stack-train-0000_text_document +0.0017591050606817512 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/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0063_text_document +0.0002852973415334161 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0064_text_document +3.7555372465932136e-05 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0065_text_document diff --git a/ALCF/data-lists/sunspot/wiki.txt b/ALCF/data-lists/sunspot/wiki.txt new file mode 100644 index 0000000000..52af00d57b --- /dev/null +++ b/ALCF/data-lists/sunspot/wiki.txt @@ -0,0 +1,2 @@ +0.003548077173506675 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/wiki-0000_text_document +0.0018372203137874265 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/wiki-0001_text_document From 3648af572d926278429f35045abfd72eb1d76a76 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 17:51:23 -0500 Subject: [PATCH 205/268] Add `ALCF/test_sunspot.sh` --- ALCF/test_sunspot.sh | 48 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 48 insertions(+) create mode 100755 ALCF/test_sunspot.sh diff --git a/ALCF/test_sunspot.sh b/ALCF/test_sunspot.sh new file mode 100755 index 0000000000..a8a4a21f32 --- /dev/null +++ b/ALCF/test_sunspot.sh @@ -0,0 +1,48 @@ +#!/bin/bash --login +# +# Run complete test of +# https://github.com/argonne-lcf/Megatron-DeepSpeed +# on Sunspot @ ALCF + +# EXIT ON ERROR(s) +set -euxo pipefail + +######################################################## +# Setup / activate conda environment, +# mine is called q4-drop +######################################################## +setup_conda() { + if [[ "${SHELL}" = "/bin/zsh" ]]; then + eval "$(~/miniconda3/bin/conda shell.zsh hook)" + else + eval "$(~/miniconda3/bin/conda shell.bash hook)" + fi + conda activate q4-drop +} + + +######################################## +# Make sure ./tmp/Megatron-DeepSpeed +# does not already exist +######################################## +setup_megatron_deepspeed() { + mkdir tmp && cd tmp + if [[ -d "Megatron-DeepSpeed" ]]; then + # rm -rfv Megatron-DeepSpeed/ + echo "Found existing Megatron-DeepSpeed. + Remove existing directory to run test." + exit + fi + git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed + git checkout remove-apex-deps +} + + +main() { + setup_conda + setup_megatron_deepspeed + # NOTE: to use OPT=adamwschedulefree, you will need to pip install schedulefree + DEBUG=1 PBS_O_WORKDIR="$(pwd)" DATA_FILE_LIST=./ALCF/data-lists/sunspot/books.txt LR=0.0008 GRAD_ACC_STEPS=8 ZERO_STAGE=1 NUM_LAYERS=10 MICRO_BATCH=8 OPT=adamwschedulefree TIMING_LOG_LEVEL=1 bash train_llama_alcf.sh +} + +main From 9796eacf3c7392e20ff03aa2ea594ef3eb46ecfd Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 19:09:33 -0500 Subject: [PATCH 206/268] Add `ALCF/data-lists/sirius/books.txt` --- ALCF/data-lists/sirius/books.txt | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 ALCF/data-lists/sirius/books.txt diff --git a/ALCF/data-lists/sirius/books.txt b/ALCF/data-lists/sirius/books.txt new file mode 100644 index 0000000000..7567ba5227 --- /dev/null +++ b/ALCF/data-lists/sirius/books.txt @@ -0,0 +1,3 @@ +0.006 /lus/tegu/projects/PolarisAT/foremans/projects/argonne-lcf/Megatron-DeepSpeed/data/books-0000_text_document +0.006 /lus/tegu/projects/PolarisAT/foremans/projects/argonne-lcf/Megatron-DeepSpeed/data/books-0001_text_document +0.006 /lus/tegu/projects/PolarisAT/foremans/projects/argonne-lcf/Megatron-DeepSpeed/data/books-0002_text_document From 7b2ab6d984ddf4aaa380b8421ae39d1c9dec5d2a Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 19:10:01 -0500 Subject: [PATCH 207/268] Add `ALCF/test_sirius.sh` --- ALCF/test_sirius.sh | 66 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 66 insertions(+) create mode 100755 ALCF/test_sirius.sh diff --git a/ALCF/test_sirius.sh b/ALCF/test_sirius.sh new file mode 100755 index 0000000000..273d511afa --- /dev/null +++ b/ALCF/test_sirius.sh @@ -0,0 +1,66 @@ +#!/bin/bash --login +# +# Run complete test of +# https://github.com/argonne-lcf/Megatron-DeepSpeed +# on Sunspot @ ALCF + +# EXIT ON ERROR(s) +set -euxo pipefail + +NOW="$(date "+%Y-%m-%d-%H%M%S")" + +######################################################## +# Setup / activate conda environment, +# mine is called q4-drop +######################################################## +setup_conda() { + export MAMBA_ROOT_PREFIX=/lus/tegu/projects/PolarisAT/foremans/micromamba + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook --shell ${shell_name})" + micromamba activate 2024-04-23 + # if [[ "${SHELL}" = "/bin/zsh" ]]; then + # eval "$(~/miniconda3/bin/conda shell.zsh hook)" + # else + # eval "$(~/miniconda3/bin/conda shell.bash hook)" + # fi + # conda activate q4-drop +} + + +######################################## +# Make sure ./tmp/Megatron-DeepSpeed +# does not already exist +######################################## +setup_megatron_deepspeed() { + OUTDIR="test-sirius-${NOW}" && mkdir -p "${OUTDIR}" && cd "${OUTDIR}" + echo "Running test in: ${OUTDIR}" + echo "WORKING DIRECTORY: $(realpath $(pwd .))" + if [[ -d "Megatron-DeepSpeed" ]]; then + # rm -rfv Megatron-DeepSpeed/ + echo "Found existing Megatron-DeepSpeed. + Remove existing directory to run test." + exit + fi + git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed + git checkout remove-apex-deps +} + + +main() { + setup_conda + setup_megatron_deepspeed + # NOTE: to use OPT=adamwschedulefree, you will need to pip install schedulefree + DEBUG=1 + PBS_O_WORKDIR="$(pwd)" + DATA_FILE_LIST=./ALCF/data-lists/sirius/books.txt + # LR=0.0008 + # GRAD_ACC_STEPS=8 + ZERO_STAGE=1 + NUM_LAYERS=10 + MICRO_BATCH=8 + # OPT=adamwschedulefree + TIMING_LOG_LEVEL=1 + bash train_llama_alcf.sh |& tee test-sirius.log +} + +main From 58cdccaa2438ac1da2a310652df3dc410e7a1138 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 19:17:30 -0500 Subject: [PATCH 208/268] Update `ALCF/test_sirius.sh` --- ALCF/test_sirius.sh | 36 ++++++++++++++++++------------------ 1 file changed, 18 insertions(+), 18 deletions(-) diff --git a/ALCF/test_sirius.sh b/ALCF/test_sirius.sh index 273d511afa..6199c5c157 100755 --- a/ALCF/test_sirius.sh +++ b/ALCF/test_sirius.sh @@ -2,7 +2,14 @@ # # Run complete test of # https://github.com/argonne-lcf/Megatron-DeepSpeed -# on Sunspot @ ALCF +# on Sirius @ ALCF +# to launch (inside an interactive `qsub -I` job) on Sirius: +# +# ```bash` +# $ git clone https://github.com/argonne-lcf/Megatron-DeepSpeed +# $ cd Megatron-DeepSpeed/ALCF +# $ bash test_sirius.sh +# ```` # EXIT ON ERROR(s) set -euxo pipefail @@ -18,12 +25,6 @@ setup_conda() { shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook --shell ${shell_name})" micromamba activate 2024-04-23 - # if [[ "${SHELL}" = "/bin/zsh" ]]; then - # eval "$(~/miniconda3/bin/conda shell.zsh hook)" - # else - # eval "$(~/miniconda3/bin/conda shell.bash hook)" - # fi - # conda activate q4-drop } @@ -32,7 +33,7 @@ setup_conda() { # does not already exist ######################################## setup_megatron_deepspeed() { - OUTDIR="test-sirius-${NOW}" && mkdir -p "${OUTDIR}" && cd "${OUTDIR}" + OUTDIR="OUTPUTS/test-sirius-${NOW}" && mkdir -p "${OUTDIR}" && cd "${OUTDIR}" echo "Running test in: ${OUTDIR}" echo "WORKING DIRECTORY: $(realpath $(pwd .))" if [[ -d "Megatron-DeepSpeed" ]]; then @@ -49,18 +50,17 @@ setup_megatron_deepspeed() { main() { setup_conda setup_megatron_deepspeed - # NOTE: to use OPT=adamwschedulefree, you will need to pip install schedulefree - DEBUG=1 - PBS_O_WORKDIR="$(pwd)" - DATA_FILE_LIST=./ALCF/data-lists/sirius/books.txt + export DEBUG=1 + export PBS_O_WORKDIR="$(pwd)" + export DATA_FILE_LIST=./ALCF/data-lists/sirius/books.txt # LR=0.0008 # GRAD_ACC_STEPS=8 - ZERO_STAGE=1 - NUM_LAYERS=10 - MICRO_BATCH=8 - # OPT=adamwschedulefree - TIMING_LOG_LEVEL=1 - bash train_llama_alcf.sh |& tee test-sirius.log + export ZERO_STAGE=1 + export NUM_LAYERS=10 + export MICRO_BATCH=8 + export TRAIN_ITERS=20 + export TIMING_LOG_LEVEL=1 + bash train_llama_alcf.sh |& tee "test-sirius-${NOW}".log } main From 02a955c410429e8d1a39356b89ad4d1c191e88e5 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 19:46:53 -0500 Subject: [PATCH 209/268] Create `alcf-tests` branch --- ALCF/test_sunspot.sh | 25 +++++++++++++++++++++---- 1 file changed, 21 insertions(+), 4 deletions(-) diff --git a/ALCF/test_sunspot.sh b/ALCF/test_sunspot.sh index a8a4a21f32..29ec46fc03 100755 --- a/ALCF/test_sunspot.sh +++ b/ALCF/test_sunspot.sh @@ -3,10 +3,19 @@ # Run complete test of # https://github.com/argonne-lcf/Megatron-DeepSpeed # on Sunspot @ ALCF +# to launch (inside an interactive `qsub -I` job) on Sirius: +# +# ```bash` +# $ git clone https://github.com/argonne-lcf/Megatron-DeepSpeed +# $ cd Megatron-DeepSpeed/ALCF +# $ bash test_sunspot.sh +# ```` # EXIT ON ERROR(s) set -euxo pipefail +NOW="$(date "+%Y-%m-%d-%H%M%S")" + ######################################################## # Setup / activate conda environment, # mine is called q4-drop @@ -26,9 +35,10 @@ setup_conda() { # does not already exist ######################################## setup_megatron_deepspeed() { - mkdir tmp && cd tmp + OUTDIR="OUTPUTS/test-sunspot-${NOW}" && mkdir -p "${OUTDIR}" && cd "${OUTDIR}" + echo "Running test in: ${OUTDIR}" + echo "WORKING DIRECTORY: $(realpath $(pwd .))" if [[ -d "Megatron-DeepSpeed" ]]; then - # rm -rfv Megatron-DeepSpeed/ echo "Found existing Megatron-DeepSpeed. Remove existing directory to run test." exit @@ -41,8 +51,15 @@ setup_megatron_deepspeed() { main() { setup_conda setup_megatron_deepspeed - # NOTE: to use OPT=adamwschedulefree, you will need to pip install schedulefree - DEBUG=1 PBS_O_WORKDIR="$(pwd)" DATA_FILE_LIST=./ALCF/data-lists/sunspot/books.txt LR=0.0008 GRAD_ACC_STEPS=8 ZERO_STAGE=1 NUM_LAYERS=10 MICRO_BATCH=8 OPT=adamwschedulefree TIMING_LOG_LEVEL=1 bash train_llama_alcf.sh + export DEBUG=1 + export PBS_O_WORKDIR="$(pwd)" + export DATA_FILE_LIST=./ALCF/data-lists/sunspot/books.txt + export ZERO_STAGE=1 + export NUM_LAYERS=10 + export MICRO_BATCH=8 + export TRAIN_ITER=20 + export TIMING_LOG_LEVEL=1 + bash train_llama_alcf.sh |& tee "test-suntpot-${NOW}".log } main From 23c953124d6025e9aef4eb7516c2d9dbe01169e2 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 19:49:41 -0500 Subject: [PATCH 210/268] Update `ALCF/{test_sirius.sh,test_sunspot.sh}` --- ALCF/test_sirius.sh | 4 ++-- ALCF/test_sunspot.sh | 6 +++--- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/ALCF/test_sirius.sh b/ALCF/test_sirius.sh index 6199c5c157..19cb9405dc 100755 --- a/ALCF/test_sirius.sh +++ b/ALCF/test_sirius.sh @@ -43,7 +43,7 @@ setup_megatron_deepspeed() { exit fi git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed - git checkout remove-apex-deps + git checkout alcf-tests } @@ -58,7 +58,7 @@ main() { export ZERO_STAGE=1 export NUM_LAYERS=10 export MICRO_BATCH=8 - export TRAIN_ITERS=20 + export TRAIN_ITER=20 export TIMING_LOG_LEVEL=1 bash train_llama_alcf.sh |& tee "test-sirius-${NOW}".log } diff --git a/ALCF/test_sunspot.sh b/ALCF/test_sunspot.sh index 29ec46fc03..ca3a59cc87 100755 --- a/ALCF/test_sunspot.sh +++ b/ALCF/test_sunspot.sh @@ -5,7 +5,7 @@ # on Sunspot @ ALCF # to launch (inside an interactive `qsub -I` job) on Sirius: # -# ```bash` +# ```bash # $ git clone https://github.com/argonne-lcf/Megatron-DeepSpeed # $ cd Megatron-DeepSpeed/ALCF # $ bash test_sunspot.sh @@ -44,7 +44,7 @@ setup_megatron_deepspeed() { exit fi git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed - git checkout remove-apex-deps + git checkout alcf-tests } @@ -59,7 +59,7 @@ main() { export MICRO_BATCH=8 export TRAIN_ITER=20 export TIMING_LOG_LEVEL=1 - bash train_llama_alcf.sh |& tee "test-suntpot-${NOW}".log + bash train_llama_alcf.sh |& tee "test-sunspot-${NOW}.log" } main From 5fff0af7bdaafebb75f713ad088edac3be3d2d60 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 20:08:57 -0500 Subject: [PATCH 211/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 65 ++++++++++++++++++++++++-------------------- 1 file changed, 36 insertions(+), 29 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 6530340c19..fe903e04f7 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -8,7 +8,7 @@ import math from functools import partial from megatron import get_args -from megatron import print_rank_0 +from megatron import log.info from megatron import get_timers from megatron import get_tokenizer from megatron.core import mpu, tensor_parallel @@ -74,7 +74,7 @@ def model_provider(pre_process=True, post_process=True): """Build the model.""" - print_rank_0('building GPT model ...') + log.info('building GPT model ...') see_memory_usage("Before Building Model", force=True) args = get_args() config = core_transformer_config_from_args(args) @@ -118,7 +118,7 @@ def model_provider(pre_process=True, post_process=True): # We need to call model.set_batch_fn after deepspeed.initialize model._megatron_batch_fn = get_batch_pipe - # Predompute the attention mask and store it in args. + # Precompute the attention mask and store it in args. # This avoids having to pipeline it # as an activation during training. # The mask is constant, and thus we can reuse it. @@ -154,12 +154,9 @@ def model_provider(pre_process=True, post_process=True): ) num_params = sum(p.numel() for p in model.parameters() if p.requires_grad) - # print_rank_0('\n ------------------------ ') - # print_rank_0(f'num of parameters {num_params}') - # print_rank_0('------------------------\n ') - print_rank_0(80 * '-') - print_rank_0(f"Number of parameters in model: {num_params}") - print_rank_0(80 * '-') + log.info(80 * '-') + log.info(f"Number of parameters in model: {num_params}") + log.info(80 * '-') see_memory_usage("After Building Model", force=True) if wandb.run is not None: tbdir = args.tensorboard_dir @@ -342,7 +339,7 @@ def loss_func(loss_mask, moe_loss, mos_loss, output_tensor): 'moe loss': moe_loss, 'kd loss': mos_loss } - print_rank_0( + log.info( f'>>> total loss: {loss}, ' f'lm loss {averaged_loss[0]}, ' f'kd loss {mos_loss}' @@ -419,7 +416,8 @@ def forward_step(data_iterator, model): # Get the batch. timers('batch-generator', log_level=2).start() tokens, labels, loss_mask, attention_mask, position_ids = get_batch( - data_iterator) + data_iterator + ) timers('batch-generator').stop() if args.data_efficiency_curriculum_learning: @@ -492,11 +490,12 @@ def train_valid_test_datasets_provider(train_val_test_num_samples): """Build train, valid, and test datasets.""" args = get_args() - print_rank_0('> building train, validation, and test datasets ' - 'for GPT ...') + log.info( + '> building train, validation, and test datasets for GPT ...' + ) files = [] if args.data_file_list is not None: - print_rank_0(f"Reading datasets from {args.data_file_list}") + log.info(f"Reading datasets from {args.data_file_list}") with open(args.data_file_list, 'r') as flist: for f in flist.readlines(): w, fname = f.split() @@ -523,8 +522,9 @@ def train_valid_test_datasets_provider(train_val_test_num_samples): train_data_prefix=args.train_data_path, valid_data_prefix=args.valid_data_path, test_data_prefix=args.test_data_path, - data_cache_path=args.data_cache_path) - print_rank_0("> finished creating GPT datasets ...") + data_cache_path=args.data_cache_path, + ) + log.info("> finished creating GPT datasets ...") return train_ds, valid_ds, test_ds @@ -566,8 +566,6 @@ def git_ds_info(): def main(): - # if RANK == 0: - # setup_wandb() if os.getenv('TORCH_PROFILER_ENABLED') == '1': from torch.profiler import profile, record_function, ProfilerActivity with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: @@ -593,17 +591,26 @@ def main(): # args_defaults={'tokenizer_type': 'GPT2BPETokenizer'}, data_post_process=data_post_process ) - try: - from megatron.text_generation import generate_and_post_process - with torch.autocast(device_type=ez.get_torch_device(), dtype=torch.float16): - response, _, _, _ = generate_and_post_process(model, prompts=["Hello world", "Nature is", "Turing test comprises", "Explain solar eclipse"], tokens_to_generate=32) - if RANK == 0: - log.info(f'generation completed..\n response:{response}') - except ValueError as ve: - log.critical(f'ValueError: {ve}') - pass + # try: + # from megatron.text_generation import generate_and_post_process + # with torch.autocast(device_type=DEVICE, dtype=args.dtype): + # response, _, _, _ = generate_and_post_process( + # model, + # prompts=[ + # "Hello world", + # "Nature is", + # "Turing test comprises", + # "Explain solar eclipse" + # ], + # tokens_to_generate=32 + # ) + # if RANK == 0: + # log.info(f'generation completed..\n response:{response}') + # except ValueError as ve: + # log.critical(f'ValueError: {ve}') + # pass # dist.barrier() - model.train() + # model.train() return model @@ -623,4 +630,4 @@ def main(): print(f"wandb.run.name: {wandb.run.name}") print(f"wandb.run.url: {wandb.run.url}") wandb.finish() - sys.exit() + sys.exit(0) From 005272b586b08e88619b4c7e341bf7951ae563d3 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 20:10:25 -0500 Subject: [PATCH 212/268] Update `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index fe903e04f7..7ed38614a7 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -8,7 +8,7 @@ import math from functools import partial from megatron import get_args -from megatron import log.info +# from megatron import print_rank_0 from megatron import get_timers from megatron import get_tokenizer from megatron.core import mpu, tensor_parallel @@ -19,12 +19,12 @@ from megatron.utils import get_ltor_masks_and_position_ids from megatron.utils import average_losses_across_data_parallel_group, update_rotary_pos_emb from megatron.arguments import core_transformer_config_from_args -from megatron.utils import ( - report_memory, - throughput_calculator, - checkpoint_throughput_calculator -) -from pathlib import Path +# from megatron.utils import ( +# # report_memory, +# # throughput_calculator, +# # checkpoint_throughput_calculator +# ) +# from pathlib import Path from enrich import get_logger import deepspeed @@ -33,7 +33,7 @@ import subprocess import wandb -import time +# import time from torch import nn import torch.nn.functional as F import ezpz as ez From fdb17075f0a84f0ca61bb76e6bb4d3d37087b649 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 20:58:38 -0500 Subject: [PATCH 213/268] Remove `ds_report` from `train_llama_alcf.sh` --- train_llama_alcf.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 4aac1153c7..cd2d8213dd 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -132,7 +132,7 @@ run_cmd=" # ds_exec # echo "! Using $(which deepspeed)" -ds_report +# ds_report echo "${run_cmd}" From 936c423355d36102b51c9f885079952e15a856b8 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 21:17:41 -0500 Subject: [PATCH 214/268] Update `.gitignore` --- .gitignore | 30 ++++++++++++++++++++++++++++++ 1 file changed, 30 insertions(+) diff --git a/.gitignore b/.gitignore index 3e46cef4c5..edbde3c246 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,33 @@ +# User Added +*tmp* +*core.* +*old* +*.bak +**index-cache** +**pbslogs** +ezpz +*.o17* +*.e17* +*hostfile* +.deepspeed_env +*.DS_Store +old/* +**venv** +*.json +*.o1 +*.e1 +outputs/ +venvs/ +wandb/ +llama-logs/ +checkpoints/ +*.gz +*.txt +*.idx +*.bin +*.log +__pycache__ + .deepspeed_env *.bak .cache/* From a59a532b332b788d26919d94c6470a8593314775 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 24 Apr 2024 21:39:34 -0500 Subject: [PATCH 215/268] Update `ALCF/test_{sunspot,sirius}.sh` --- ALCF/test_sirius.sh | 8 ++------ ALCF/test_sunspot.sh | 5 ++--- 2 files changed, 4 insertions(+), 9 deletions(-) diff --git a/ALCF/test_sirius.sh b/ALCF/test_sirius.sh index 19cb9405dc..108649612c 100755 --- a/ALCF/test_sirius.sh +++ b/ALCF/test_sirius.sh @@ -37,13 +37,11 @@ setup_megatron_deepspeed() { echo "Running test in: ${OUTDIR}" echo "WORKING DIRECTORY: $(realpath $(pwd .))" if [[ -d "Megatron-DeepSpeed" ]]; then - # rm -rfv Megatron-DeepSpeed/ - echo "Found existing Megatron-DeepSpeed. - Remove existing directory to run test." + echo "Found existing Megatron-DeepSpeed in ${OUTDIR}" + echo "Remove Megatron-DeepSpeed from ${OUTDIR} to run test." exit fi git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed - git checkout alcf-tests } @@ -53,8 +51,6 @@ main() { export DEBUG=1 export PBS_O_WORKDIR="$(pwd)" export DATA_FILE_LIST=./ALCF/data-lists/sirius/books.txt - # LR=0.0008 - # GRAD_ACC_STEPS=8 export ZERO_STAGE=1 export NUM_LAYERS=10 export MICRO_BATCH=8 diff --git a/ALCF/test_sunspot.sh b/ALCF/test_sunspot.sh index ca3a59cc87..67f6868d43 100755 --- a/ALCF/test_sunspot.sh +++ b/ALCF/test_sunspot.sh @@ -39,12 +39,11 @@ setup_megatron_deepspeed() { echo "Running test in: ${OUTDIR}" echo "WORKING DIRECTORY: $(realpath $(pwd .))" if [[ -d "Megatron-DeepSpeed" ]]; then - echo "Found existing Megatron-DeepSpeed. - Remove existing directory to run test." + echo "Found existing Megatron-DeepSpeed in ${OUTDIR}" + echo "Remove Megatron-DeepSpeed from ${OUTDIR} to run test." exit fi git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed - git checkout alcf-tests } From c9c87d9ff40d013e93dd623ed68cada4086cce9f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 10:53:29 -0500 Subject: [PATCH 216/268] Update `ALCF/data-lists/polaris/*.txt` --- ALCF/data-lists/polaris/algebraic.txt | 16 + ALCF/data-lists/polaris/arxiv.txt | 100 + ALCF/data-lists/polaris/books.txt | 3 + ALCF/data-lists/polaris/c4.txt | 171 + ALCF/data-lists/polaris/cc.txt | 1108 ++++ .../polaris/data_file_list_books.txt | 3 - ALCF/data-lists/polaris/data_file_list_c4.txt | 86 - ALCF/data-lists/polaris/data_file_list_cc.txt | 2878 ----------- .../polaris/data_file_list_peS2o.txt | 42 - .../polaris/data_file_list_stack.txt | 4435 ----------------- .../polaris/data_file_list_wiki.txt | 2 - .../polaris/dolma_v1_7_file_list.txt | 2419 +++++++++ ALCF/data-lists/polaris/falcon.txt | 501 ++ ALCF/data-lists/polaris/megawiki.txt | 262 + .../polaris/open-web-math-train.txt | 13 + ALCF/data-lists/polaris/pes2o.txt | 26 + ALCF/data-lists/polaris/reddit.txt | 78 + ALCF/data-lists/polaris/stack.txt | 26 + ALCF/data-lists/polaris/starcoder.txt | 50 + ALCF/data-lists/polaris/tulu.txt | 66 + ALCF/data-lists/polaris/wiki.txt | 2 + 21 files changed, 4841 insertions(+), 7446 deletions(-) create mode 100644 ALCF/data-lists/polaris/algebraic.txt create mode 100644 ALCF/data-lists/polaris/arxiv.txt create mode 100644 ALCF/data-lists/polaris/books.txt create mode 100644 ALCF/data-lists/polaris/c4.txt create mode 100644 ALCF/data-lists/polaris/cc.txt delete mode 100644 ALCF/data-lists/polaris/data_file_list_books.txt delete mode 100644 ALCF/data-lists/polaris/data_file_list_c4.txt delete mode 100644 ALCF/data-lists/polaris/data_file_list_cc.txt delete mode 100644 ALCF/data-lists/polaris/data_file_list_peS2o.txt delete mode 100644 ALCF/data-lists/polaris/data_file_list_stack.txt delete mode 100644 ALCF/data-lists/polaris/data_file_list_wiki.txt create mode 100644 ALCF/data-lists/polaris/dolma_v1_7_file_list.txt create mode 100644 ALCF/data-lists/polaris/falcon.txt create mode 100644 ALCF/data-lists/polaris/megawiki.txt create mode 100644 ALCF/data-lists/polaris/open-web-math-train.txt create mode 100644 ALCF/data-lists/polaris/pes2o.txt create mode 100644 ALCF/data-lists/polaris/reddit.txt create mode 100644 ALCF/data-lists/polaris/stack.txt create mode 100644 ALCF/data-lists/polaris/starcoder.txt create mode 100644 ALCF/data-lists/polaris/tulu.txt create mode 100644 ALCF/data-lists/polaris/wiki.txt diff --git a/ALCF/data-lists/polaris/algebraic.txt b/ALCF/data-lists/polaris/algebraic.txt new file mode 100644 index 0000000000..505276d3bf --- /dev/null +++ b/ALCF/data-lists/polaris/algebraic.txt @@ -0,0 +1,16 @@ +0.0018520780893211373 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/algebraic-stack-train-0000_text_document +0.0017591050606817512 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/algebraic-stack-train-0001_text_document +0.001459052794333798 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/algebraic-stack-train-0002_text_document +0.0007405667281569194 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/algebraic-stack-train-0003_text_document +0.00019420030110896795 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/algebraic-stack-train-0004_text_document +0.0009008668715801845 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/algebraic-stack-train-0005_text_document 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+0.00033784225259118157 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0029_text_document +0.0003367278459543952 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0030_text_document +0.00029843279042852765 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0031_text_document +0.0002926583661257988 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0032_text_document +0.00029320337282010673 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0033_text_document +0.00029281450669483455 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0034_text_document +0.0002915338187002653 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0035_text_document +0.0002864226923084572 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0036_text_document +0.00028643439083586396 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0037_text_document +0.00028253710956299054 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/eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0057_text_document +0.0002514844936507595 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0058_text_document +0.00031638782778107964 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0059_text_document +0.0002749197545278445 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0060_text_document +0.00026159721512464495 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0061_text_document +0.0002630052420096968 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0062_text_document +0.00031106811228913666 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0063_text_document +0.0002852973415334161 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0064_text_document +3.7555372465932136e-05 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0065_text_document diff --git a/ALCF/data-lists/polaris/wiki.txt b/ALCF/data-lists/polaris/wiki.txt new file mode 100644 index 0000000000..7759120d87 --- /dev/null +++ b/ALCF/data-lists/polaris/wiki.txt @@ -0,0 +1,2 @@ +0.003548077173506675 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/wiki-0000_text_document +0.0018372203137874265 /eagle/datasets/dolma/data_v1.7_Llama2Tokenizer/wiki-0001_text_document From caa1a4bfdd159594de2615fc36a580a86a735386 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 11:02:07 -0500 Subject: [PATCH 217/268] Add `ALCF/test_polaris.sh` --- ALCF/test_polaris.sh | 84 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 84 insertions(+) create mode 100644 ALCF/test_polaris.sh diff --git a/ALCF/test_polaris.sh b/ALCF/test_polaris.sh new file mode 100644 index 0000000000..cbe2b41c5e --- /dev/null +++ b/ALCF/test_polaris.sh @@ -0,0 +1,84 @@ +#!/bin/bash --login +# +# Run complete test of +# https://github.com/argonne-lcf/Megatron-DeepSpeed +# on Polaris @ ALCF +# to launch (inside an interactive `qsub -I` job) on Polaris: +# +# ```bash` +# $ git clone https://github.com/argonne-lcf/Megatron-DeepSpeed +# $ cd Megatron-DeepSpeed/ALCF +# $ bash test_polaris.sh +# ```` + +# EXIT ON ERROR(s) +set -euxo pipefail + +NOW="$(date "+%Y-%m-%d-%H%M%S")" + +######################################################## +# Setup / activate conda environment, +# mine is called q4-drop +######################################################## +setup_conda() { + if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" + micromamba activate 2024-04-25 + else + echo "Found existing python at: $(which python3)" + fi +} + + +######################################## +# Make sure ./tmp/Megatron-DeepSpeed +# does not already exist +######################################## +setup_megatron_deepspeed() { + OUTDIR="OUTPUTS/test-polaris-${NOW}" && mkdir -p "${OUTDIR}" && cd "${OUTDIR}" + echo "Running test in: ${OUTDIR}" + echo "WORKING DIRECTORY: $(realpath $(pwd .))" + if [[ -d "Megatron-DeepSpeed" ]]; then + echo "Found existing Megatron-DeepSpeed in ${OUTDIR}" + echo "Remove Megatron-DeepSpeed from ${OUTDIR} to run test." + exit + fi + git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed + if [[ -z "${GIT_BRANCH-}" ]]; then + git checkout "${GIT_BRANCH}" + fi +} + + +main() { + local virtual_env="${VIRTUAL_ENV-}" + local conda_prefix="${CONDA_PREFIX}" + if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "Using conda from: ${conda_prefix}" + elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then + echo "Using virtual_env from: ${virtual_env}" + elif [[ -n "${virtual_env}" && -n "${conda_prefix}" ]]; then + echo "Using virtual_env: ${virtual_env} on top of CONDA: ${conda_prefix}" + elif [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "No conda_prefix or virtual_env found in environment..." + echo "Setting up conda" + setup_conda + else + echo "Unable to setup python. Exiting" + exit 1 + fi + setup_megatron_deepspeed + export DEBUG=1 + export PBS_O_WORKDIR="$(pwd)" + export DATA_FILE_LIST=./ALCF/data-lists/polaris/books.txt + export ZERO_STAGE=1 + export NUM_LAYERS=10 + export MICRO_BATCH=8 + export TRAIN_ITER=20 + export TIMING_LOG_LEVEL=1 + bash train_llama_alcf.sh |& tee "test-polaris-${NOW}".log +} + +main From b534e09d000a343af0d65b0b6feb652303b74aa1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 11:02:26 -0500 Subject: [PATCH 218/268] Fix duplicate loggers in `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 7ed38614a7..f83ef05fc8 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -25,7 +25,7 @@ # # checkpoint_throughput_calculator # ) # from pathlib import Path -from enrich import get_logger +import logging import deepspeed from deepspeed.runtime.utils import see_memory_usage @@ -49,7 +49,7 @@ torch.cuda.set_device(LOCAL_RANK) # ------------------------------------------- # --- [TURN OFF LOGGER ON ALL RANK != 0] ---- -log = get_logger(__name__) +log = logging.getLogger(__name__) log.setLevel("INFO") if RANK == 0 else log.setLevel("CRITICAL") # ---- [SETUP WANDB FROM RANK 0] -------------- WANDB_MODE = os.environ.get('WANDB_MODE', None) From 2c4d7728fa15e762ad9ef896c2bf15c440d70f5e Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 11:03:11 -0500 Subject: [PATCH 219/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 88 ++++++++++++++++++++++++++++++++----------------- 1 file changed, 57 insertions(+), 31 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index fdd42b56b8..9b057e0c03 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -16,7 +16,19 @@ export WORKING_DIR="${WORKING_DIR}" printf "Using WORKING_DIR: %s\n" ${WORKING_DIR} -printJobInfo() { +function setupSrun() { + if [[ $(hostname) == login* || $(hostname) == nid* ]]; then + export NHOSTS="${SLURM_NNODES:-1}" + export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" + export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" + export SRUN_EXEC="srun --gpus ${NGPUS} --gpus-per-node ${NGPU_PER_HOST} -N ${NHOSTS} -n ${NGPUS} -l -u --verbose" + else + echo "Skipping setupSrun() on $(hostname)" + fi +} + + +function printJobInfo() { echo "++++++++++++++++++++++++++++++++++++++++++++++++++" echo "- MPICH_DIR=${MPICH_DIR:-${MPI_ROOT}}" echo "- Using $(which python3)" @@ -27,20 +39,33 @@ printJobInfo() { echo "++++++++++++++++++++++++++++++++++++++++++++++++++" } +function setupVenv() { + VENV_DIR="$1" + if [[ -d "${VENV_DIR}" ]]; then + echo "Found venv at: ${VENV_DIR}" + source "${VENV_DIR}/bin/activate" + else + echo "Skipping setupVenv() on $(hostname)" + fi +} -setupSrun() { - if [[ $(hostname) == login* || $(hostname) == nid* ]]; then - export NHOSTS="${SLURM_NNODES:-1}" - export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" - export NGPUS="$(( NHOSTS * NGPU_PER_HOST ))" - export SRUN_EXEC="srun --gpus ${NGPUS} --gpus-per-node ${NGPU_PER_HOST} -N ${NHOSTS} -n ${NGPUS} -l -u --verbose" +function loadCondaEnv() { + if [[ "${CONDA_EXE}" ]]; then + echo "Already inside ${CONDA_EXE}, exiting!" else - echo "Skipping setupSrun() on $(hostname)" + MODULE_STR="$1" + module load "conda/${MODULE_STR}" + nargs="$#" + if [[ "${nargs}" -ge 2 ]]; then + conda activate "$2" + else + conda activate base + fi fi } -setupLauncher() { +function setupLauncher() { # outdir=$1 if [[ -n "${DIST_LAUNCH}" && ${LAUNCH_CMD:-"MPICH"} != "deepspeed" ]]; then export LAUNCH_CMD="${DIST_LAUNCH} --cpu-bind depth -d 16 python3 -Wignore ${EXEC}" @@ -53,7 +78,7 @@ setupLauncher() { printf " %s" "$(printMagenta ${LAUNCH_CMD})" } -setDSlauncher() { +function setDSlauncher() { # launcher setting outdir=$1 export hfds="$outdir/hostfile_deepspeed" @@ -68,7 +93,7 @@ setDSlauncher() { fi } -setParams() { +function setParams() { LLAMA_ARGS="" # +----[Parallelism Settings] -------------------------------------------+ # +------[Aurora]--------||-------[SunSpot]-------------+ @@ -155,7 +180,7 @@ setParams() { } -setArgs() { +function setArgs() { # ---- Set DeepSpeed arguments -------------------------------- ds_args=" " ds_args=" --deepspeed ${ds_args}" @@ -186,7 +211,7 @@ setArgs() { } -make_ds_hostfile() { +function make_ds_hostfile() { export GPUS_PER_NODE="${GPUS_PER_NODE:-${NGPU_PER_HOST:-${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}}}" # ---- Make MPICH hostfile ---------------- hf="${HOSTFILE:-${PBS_NODEFILE}}" @@ -202,7 +227,7 @@ make_ds_hostfile() { # | 1. Git clone ezpz (if not found) | # | 2. Install ezpz (if not installed) | # +---------------------------------------+ -ezpz() { +function ezpz() { if [[ ! -d "${WORKING_DIR}/deps/ezpz" ]]; then mkdir -p "${WORKING_DIR}/deps" git clone https://github.com/saforem2/ezpz "${WORKING_DIR}/deps/ezpz" @@ -228,7 +253,7 @@ ezpz() { # | Save important environment variables to .deepspeed_env, which will be | # | forwarded to ALL ranks with DeepSpeed | # +------------------------------------------------------------------------+ -saveDSenv() { +function saveDSenv() { echo "Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env" { echo "PATH=${PATH}" ; @@ -240,7 +265,7 @@ saveDSenv() { } > .deepspeed_env } -setOutput() { +function setOutput() { # ---- Specify output location -------------------------------- export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" # OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" @@ -253,7 +278,7 @@ setOutput() { echo "!!!Please see logs at ${OUTPUT_DIR}" } -buildDSconfig() { +function buildDSconfig() { # ---- Build DeepSpeed Config --------------------------------- export CPU_OPTIMIZER="${CPU_OPTIMIZER:-0}" export DS_CONFIG="${WORKING_DIR}/ds-configs/ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" @@ -267,13 +292,13 @@ buildDSconfig() { } -sumWeights() { +function sumWeights() { local file_list=$1 weights=$(cat "${file_list}" | awk '{print $1}' | tr '\n' '\ ,\ ' | sed 's/^/[/g' | sed 's/$/]/g' | tr '\ ' "\,\ ") python3 -c "import numpy as np; print(np.sum(${weights}))" } -sumFiles() { +function sumFiles() { local rd=$1 for f in $("${rd}/*.txt"); do ws=$(sumWeights "${rd}/${f}") @@ -282,7 +307,7 @@ sumFiles() { } -setEnv() { +function setEnv() { # ---- [SunSpot] ------- || ---- [Aurora] -------------- if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then # PBS_PARENT=$(dirname ${PBS_O_WORKDIR}) @@ -323,7 +348,7 @@ setEnv() { } -makeHostfiles() { +function makeHostfiles() { if [[ -n "${HOSTFILE}" ]]; then printf "!! USING CUSTOM HOSTFILE FROM: %s" "${HOSTFILE}" else @@ -333,7 +358,7 @@ makeHostfiles() { fi } -setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- +function setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- if [[ $(hostname) == x4* ]]; then # ---- [AURORA] ---- dfl_fallback="/home/foremans/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed/data_file_list_reweighted.txt" elif [[ $(hostname) == x1* ]]; then @@ -370,7 +395,7 @@ setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- echo "--------------------" } -generateDSconfig() { +function generateDSconfig() { for v in "$GLOBAL_BATCH" "$MICRO_BATCH" "$GRAD_ACC_STEPS" "$ZERO_STAGE" \ "$PP" "$DTYPE" do @@ -532,33 +557,34 @@ $flops_profiler EOT } -printBlack() { +function printBlack() { printf "\e[1;30m%s\e[0m\n" "$@" } -printRed() { +function printRed() { printf "\e[1;31m%s\e[0m\n" "$@" } -printGreen() { +function printGreen() { printf "\e[1;32m%s\e[0m\n" "$@" } -printYellow() { +function printYellow() { printf "\e[1;33m%s\e[0m\n" "$@" } -printBlue() { +function printBlue() { printf "\e[1;34m%s\e[0m\n" "$@" } -printMagenta() { +function printMagenta() { printf "\e[1;35m%s\e[0m\n" "$@" } -printCyan() { +function printCyan() { printf "\e[1;36m%s\e[0m\n" "$@" } -printWhite() { + +function printWhite() { printf "\e[1;37m%s\e[0m\n" "$@" } From cfa6b52e82c29018ebe92642e0379f393fe26eb5 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 11:14:02 -0500 Subject: [PATCH 220/268] Update `ALCF/test_{polaris,sirius,sunspot}.sh` --- ALCF/test_polaris.sh | 10 +++++++--- ALCF/test_sirius.sh | 38 ++++++++++++++++++++++++++++++++------ ALCF/test_sunspot.sh | 35 +++++++++++++++++++++++++++++------ 3 files changed, 68 insertions(+), 15 deletions(-) diff --git a/ALCF/test_polaris.sh b/ALCF/test_polaris.sh index cbe2b41c5e..3a6734f61e 100644 --- a/ALCF/test_polaris.sh +++ b/ALCF/test_polaris.sh @@ -22,7 +22,7 @@ NOW="$(date "+%Y-%m-%d-%H%M%S")" ######################################################## setup_conda() { if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then - export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba + export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" micromamba activate 2024-04-25 @@ -46,7 +46,7 @@ setup_megatron_deepspeed() { exit fi git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed - if [[ -z "${GIT_BRANCH-}" ]]; then + if [[ -n "${GIT_BRANCH-}" ]]; then git checkout "${GIT_BRANCH}" fi } @@ -72,7 +72,11 @@ main() { setup_megatron_deepspeed export DEBUG=1 export PBS_O_WORKDIR="$(pwd)" - export DATA_FILE_LIST=./ALCF/data-lists/polaris/books.txt + export DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/polaris/books.txt" + if [[ ! -f "${DATA_FILE_LIST}" ]]; then + echo "Unable to find / use ${DATA_FILE_LIST}. Exiting." + exit 1 + fi export ZERO_STAGE=1 export NUM_LAYERS=10 export MICRO_BATCH=8 diff --git a/ALCF/test_sirius.sh b/ALCF/test_sirius.sh index 108649612c..39170fa47c 100755 --- a/ALCF/test_sirius.sh +++ b/ALCF/test_sirius.sh @@ -21,10 +21,14 @@ NOW="$(date "+%Y-%m-%d-%H%M%S")" # mine is called q4-drop ######################################################## setup_conda() { - export MAMBA_ROOT_PREFIX=/lus/tegu/projects/PolarisAT/foremans/micromamba - shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') - eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook --shell ${shell_name})" - micromamba activate 2024-04-23 + if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + export MAMBA_ROOT_PREFIX=/lus/tegu/projects/PolarisAT/foremans/micromamba + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook --shell ${shell_name})" + micromamba activate 2024-04-23 + else + echo "Found existing python at: $(which python3)" + fi } @@ -42,15 +46,37 @@ setup_megatron_deepspeed() { exit fi git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed + if [[ -n "${GIT_BRANCH-}" ]]; then + git checkout "${GIT_BRANCH}" + fi } main() { - setup_conda + local virtual_env="${VIRTUAL_ENV-}" + local conda_prefix="${CONDA_PREFIX}" + if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "Using conda from: ${conda_prefix}" + elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then + echo "Using virtual_env from: ${virtual_env}" + elif [[ -n "${virtual_env}" && -n "${conda_prefix}" ]]; then + echo "Using virtual_env: ${virtual_env} on top of CONDA: ${conda_prefix}" + elif [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "No conda_prefix or virtual_env found in environment..." + echo "Setting up conda" + setup_conda + else + echo "Unable to setup python. Exiting" + exit 1 + fi setup_megatron_deepspeed export DEBUG=1 export PBS_O_WORKDIR="$(pwd)" - export DATA_FILE_LIST=./ALCF/data-lists/sirius/books.txt + export DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/sirius/books.txt" + if [[ ! -f "${DATA_FILE_LIST}" ]]; then + echo "Unable to find / use ${DATA_FILE_LIST}. Exiting." + exit 1 + fi export ZERO_STAGE=1 export NUM_LAYERS=10 export MICRO_BATCH=8 diff --git a/ALCF/test_sunspot.sh b/ALCF/test_sunspot.sh index 67f6868d43..b39bff7736 100755 --- a/ALCF/test_sunspot.sh +++ b/ALCF/test_sunspot.sh @@ -21,12 +21,13 @@ NOW="$(date "+%Y-%m-%d-%H%M%S")" # mine is called q4-drop ######################################################## setup_conda() { - if [[ "${SHELL}" = "/bin/zsh" ]]; then - eval "$(~/miniconda3/bin/conda shell.zsh hook)" + if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$(~/miniconda3/bin/conda shell hook -s posix)" + conda activate q4-drop else - eval "$(~/miniconda3/bin/conda shell.bash hook)" + echo "Found existing python at: $(which python3)" fi - conda activate q4-drop } @@ -44,15 +45,37 @@ setup_megatron_deepspeed() { exit fi git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed + if [[ -n "${GIT_BRANCH-}" ]]; then + git checkout "${GIT_BRANCH}" + fi } main() { - setup_conda + local virtual_env="${VIRTUAL_ENV-}" + local conda_prefix="${CONDA_PREFIX}" + if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "Using conda from: ${conda_prefix}" + elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then + echo "Using virtual_env from: ${virtual_env}" + elif [[ -n "${virtual_env}" && -n "${conda_prefix}" ]]; then + echo "Using virtual_env: ${virtual_env} on top of CONDA: ${conda_prefix}" + elif [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "No conda_prefix or virtual_env found in environment..." + echo "Setting up conda" + setup_conda + else + echo "Unable to setup python. Exiting" + exit 1 + fi setup_megatron_deepspeed export DEBUG=1 export PBS_O_WORKDIR="$(pwd)" - export DATA_FILE_LIST=./ALCF/data-lists/sunspot/books.txt + export DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/sunspot/books.txt" + if [[ ! -f "${DATA_FILE_LIST}" ]]; then + echo "Unable to find / use ${DATA_FILE_LIST}. Exiting." + exit 1 + fi export ZERO_STAGE=1 export NUM_LAYERS=10 export MICRO_BATCH=8 From a3114bf898c035b4c4db366af4e6745c9bc82276 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 11:15:36 -0500 Subject: [PATCH 221/268] Add `ALCF/data-lists/sunspot/dolma_v1_7_file_list.txt` --- .../sunspot/dolma_v1_7_file_list.txt | 2419 +++++++++++++++++ 1 file changed, 2419 insertions(+) create mode 100644 ALCF/data-lists/sunspot/dolma_v1_7_file_list.txt diff --git a/ALCF/data-lists/sunspot/dolma_v1_7_file_list.txt b/ALCF/data-lists/sunspot/dolma_v1_7_file_list.txt new file mode 100644 index 0000000000..5d142522a7 --- /dev/null +++ b/ALCF/data-lists/sunspot/dolma_v1_7_file_list.txt @@ -0,0 +1,2419 @@ +0.0018520780893211373 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/algebraic-stack-train-0000_text_document +0.0017591050606817512 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/algebraic-stack-train-0001_text_document 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/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0058_text_document +0.00031638782778107964 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0059_text_document +0.0002749197545278445 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0060_text_document +0.00026159721512464495 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0061_text_document +0.0002630052420096968 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0062_text_document +0.00031106811228913666 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0063_text_document +0.0002852973415334161 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0064_text_document +3.7555372465932136e-05 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/tulu_flan-0065_text_document +0.003548077173506675 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/wiki-0000_text_document +0.0018372203137874265 /gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_v1.7_Llama2Tokenizer/wiki-0001_text_document From f63aad14f230c60a0ad523019c09c34075326445 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 12:02:46 -0500 Subject: [PATCH 222/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 68 +++++++++++++++++++++++++++++++++++++------------ 1 file changed, 52 insertions(+), 16 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 9b057e0c03..a0d191bb8c 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -306,13 +306,46 @@ function sumFiles() { done } +######################################################## +# Setup / activate conda environment, +# mine is called q4-drop +######################################################## +setup_conda_sunspot() { + if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$(~/miniconda3/bin/conda shell hook -s posix)" + conda activate q4-drop + else + echo "Found existing python at: $(which python3)" + fi +} + +setup_conda_sirius() { + if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + export MAMBA_ROOT_PREFIX=/lus/tegu/projects/PolarisAT/foremans/micromamba + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook --shell ${shell_name})" + micromamba activate 2024-04-23 + else + echo "Found existing python at: $(which python3)" + fi +} + +setup_conda_polaris() { + if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" + micromamba activate 2024-04-25 + else + echo "Found existing python at: $(which python3)" + fi +} + function setEnv() { # ---- [SunSpot] ------- || ---- [Aurora] -------------- if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then - # PBS_PARENT=$(dirname ${PBS_O_WORKDIR}) - # echo "Sourcing ${PBS_PARENT}/setenv.sh..." - # source "${PBS_PARENT}/setenv.sh" || exit source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit # ----- [Aurora] ----------------------------------- if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then @@ -321,20 +354,22 @@ function setEnv() { # ----- [SunSpot] ---------------------------------- elif [[ $(hostname) == x1* ]]; then echo "Running on SunSpot !!" - eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate q4-drop + setup_conda_sunspot + # eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate q4-drop fi fi # ----- [Polaris] --------------------------------------- elif [[ $(hostname) == x3* ]]; then if [[ "${PBS_O_HOST}" == sirius* ]]; then export MACHINE="Running on Sirius !!" + setup_conda_sirius else echo "Running on Polaris !!" # ---- [load conda] --------------------- - # module load conda/2023-10-04; conda activate cu118-pt221 ; unset PYTHONUSERBASE - if [[ -d "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221" ]]; then - source "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221/bin/activate" - fi + setup_conda_polaris + # if [[ -d "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221" ]]; then + # source "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221/bin/activate" + # fi fi elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then echo "Running on Perlmutter !!" @@ -353,8 +388,6 @@ function makeHostfiles() { printf "!! USING CUSTOM HOSTFILE FROM: %s" "${HOSTFILE}" else make_ds_hostfile - # source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv" || exit #> /tmp/savejobenv.log 2>&1 & - # source "${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv" || exit fi } @@ -362,24 +395,27 @@ function setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------ if [[ $(hostname) == x4* ]]; then # ---- [AURORA] ---- dfl_fallback="/home/foremans/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed/data_file_list_reweighted.txt" elif [[ $(hostname) == x1* ]]; then - dfl_fallback="${WORKING_DIR}/ALCF/data-lists/sunspot/data_file_list_books.txt" - # dfl_fallback="/gila/Aurora_deployment/AuroraGPT/datasets/dolma/data_file_list_reweighted.txt" + # shellcheck: source ./data-lists/sunspot/books.txt + dfl_fallback="${WORKING_DIR}/ALCF/data-lists/sunspot/books.txt" elif [[ $(hostname) == x3* ]]; then - # dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" - dfl_fallback="${WORKING_DIR}/ALCF/data-lists/polaris/data_file_list_books.txt" + if [[ "${PBS_O_HOST}" == sirius* ]]; then + # shellcheck: source ./data-lists/sirius/books.txt + dfl_fallback="${WORKING_DIR}/ALCF/data-lists/sirius/books.txt" + elif [[ "${PBS_O_HOST}" == polaris* ]]; then + # shellcheck: source ./data-lists/polaris/books.txt + dfl_fallback="${WORKING_DIR}/ALCF/data-lists/polaris/books.txt" + fi elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then dfl_fallback="${SLURM_SUBMIT_DIR}/genslm-subsample.txt" else echo "Unknown hostname. Must manually specify DATA_FILE_LIST." fi dfl="${1:-${dfl_fallback}}" - # dfl_fallback="/eagle/datasets/dolma/data_file_list_reweighted.txt" printf "Calling: setData() with %s\n" "${dfl}" ndocs=$(wc -l < "${dfl}") ws=$(sumWeights "${dfl}") dfl_stem=$(echo "${dfl}" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") dcp=".cache/${dfl_stem}/index-cache" - # mkdir -p dcp export DATA_FILE_LIST="${dfl}" export NUM_DOCS="${ndocs}" export WEIGHT_SUM="${ws}" From d329801a8e48a6da10b0a4d2da59961d293691dd Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 12:02:54 -0500 Subject: [PATCH 223/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index a0d191bb8c..868f0e194b 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -361,7 +361,7 @@ function setEnv() { # ----- [Polaris] --------------------------------------- elif [[ $(hostname) == x3* ]]; then if [[ "${PBS_O_HOST}" == sirius* ]]; then - export MACHINE="Running on Sirius !!" + echo "Running on Sirius !!" setup_conda_sirius else echo "Running on Polaris !!" From 585c15e3557157df2f31e1d5d3ccbf343ca6088c Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 12:03:08 -0500 Subject: [PATCH 224/268] Update `train_llama_alcf.sh` --- train_llama_alcf.sh | 32 +++++++++++++------------------- 1 file changed, 13 insertions(+), 19 deletions(-) diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index cd2d8213dd..462da0c4e1 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -35,39 +35,38 @@ sourceFile "${HERE}/ALCF/helpers.sh" || exit # ----[3. Call fns from `./ALCF/helpers_alcf.sh`]------------------------------ setEnv || exit # 1. load `conda` environment -# saveDSenv || exit # 2. save env vars to `.deepspeed_env` +# saveDSenv || exit # 2. save env vars to `.deepspeed_env` ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars - -# if [[ -z "${HOSTFILE}" ]]; then -# makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` -# else -# echo "!! USING CUSTOM HOSTFILE FROM: ${HOSTFILE}" -# fi setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} setArgs || exit # 8. specify additional `deepspeed` arguments setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset -# setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` printJobInfo || exit # 11. print job info setupLauncher || exit # ----------------------------------------------------------------------------- - +#### [DEPRECATED] ########################################################### +# if [[ -z "${HOSTFILE}" ]]; then +# makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +# else +# echo "!! USING CUSTOM HOSTFILE FROM: ${HOSTFILE}" +# fi +# ---------------------------------------------------------------------------- +# setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` +# ---------------------------------------------------------------------------- # TORCH_DEVICE=$(python3 -c 'import ezpz as ez; print(ez.get_torch_device())') # printf %s "Using TORCH_DEVICE=${TORCH_DEVICE}" -# # if [[ "${TORCH_DEVICE}" == "cuda" ]]; then # printf %s "Setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True" # PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True # fi - - +# ---------------------------------------------------------------------------- # export MPICH_GPU_SUPPORT_ENABLED=1 # export CUDA_DEVICE_MAX_CONNECTIONS=1 # export NCCL_DEBUG=INFO -# -# +############################################################################# + # Assert TBDIR exists inside our $CKPT_DIR TBDIR="${CKPT_DIR}/tensorboard" mkdir -p "${TBDIR}" @@ -130,12 +129,7 @@ run_cmd=" |& tee ${OUTPUT_LOG} " -# ds_exec -# echo "! Using $(which deepspeed)" -# ds_report - echo "${run_cmd}" - printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" eval "${run_cmd}" From 3444b99dd8639659a4c5ed987952df093d09d46a Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 12:03:25 -0500 Subject: [PATCH 225/268] Update `.gitignore` --- .gitignore | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.gitignore b/.gitignore index edbde3c246..3b18d4956a 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,7 @@ # User Added +deps/* +OUTPUTS/* +ALCF/OUTPUTS/* *tmp* *core.* *old* From 505aef062892ef1da3e1124e7bab8c383dc54fe9 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 12:15:03 -0500 Subject: [PATCH 226/268] Update defaults in `ALCF/helpers.sh` --- ALCF/helpers.sh | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 868f0e194b..7fa8e748c1 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -113,12 +113,13 @@ function setParams() { ####################################################### # +--------[Polaris]-----------------------------------+ elif [[ $(hostname) == x3* ]]; then - TP=${TP:-2} # TP = 2 + TP=${TP:-1} # TP = 2 export NCCL=${NCCL:-nccl} # NCCL export BE="${NCCL}" # BE = NCCL # export DTYPE=${DTYPE:-bf16} # DTYPE: BF16 ?? export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 - MICRO_BATCH=${MICRO_BATCH:-8} # MICRO_BATCH = 8 + export GRAD_ACC_STEPS=4 # GRADIENT_ACCUMULATION_STEPS + MICRO_BATCH=${MICRO_BATCH:-2} # MICRO_BATCH = 8 if [[ -n "${NO_FLASH_ATTN-}" ]]; then echo "Not using flash-attn!!" else @@ -160,7 +161,7 @@ function setParams() { # +---[Run Settings]------------------------------------------------------+ export LR=${LR:-0.0003} # LEARNING_RATE export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 - export ZERO_STAGE=${ZERO_STAGE:-2} # ZERO OFFLOADING STAGE + export ZERO_STAGE=${ZERO_STAGE:-1} # ZERO OFFLOADING STAGE export MICRO_BATCH=${MICRO_BATCH:-8} # MICRO BATCH SIZE export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} # GRADIENT ACCUMULATION STEPS export EVAL_ITERS="${EVAL_ITERS:-10}" # NUMBER OF EVAL ITERS TO RUN From e31bb23b9c7e865b873c9d888439ba81018ba387 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 12:15:24 -0500 Subject: [PATCH 227/268] Add `train_agpt.sh` --- train_agpt.sh | 11 +++++++++++ 1 file changed, 11 insertions(+) create mode 100644 train_agpt.sh diff --git a/train_agpt.sh b/train_agpt.sh new file mode 100644 index 0000000000..4129f553e2 --- /dev/null +++ b/train_agpt.sh @@ -0,0 +1,11 @@ +#!/bin/bash --login + +NOW="$(date "+%Y-%m-%d-%H%M%S")" +cd "${PBS_O_WORKDIR}" || exit + +OUTDIR="${PBS_O_WORKDIR}/pbslogs" +mkdir -p "${OUTDIR}" +OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" +echo "${OUTFILE}" >> "${OUTDIR}/latest" +echo "Logging job output to: ${OUTFILE}" +bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" From a73e9af36ef12ae8435ed72bc15bd78e58bdc670 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 13:58:31 -0500 Subject: [PATCH 228/268] Update `ALCF/test_{polaris,sirius,sunspot}.sh` --- ALCF/test_polaris.sh | 4 ++-- ALCF/test_sirius.sh | 2 +- ALCF/test_sunspot.sh | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/ALCF/test_polaris.sh b/ALCF/test_polaris.sh index 3a6734f61e..a18c87fad7 100644 --- a/ALCF/test_polaris.sh +++ b/ALCF/test_polaris.sh @@ -21,7 +21,7 @@ NOW="$(date "+%Y-%m-%d-%H%M%S")" # mine is called q4-drop ######################################################## setup_conda() { - if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" @@ -54,7 +54,7 @@ setup_megatron_deepspeed() { main() { local virtual_env="${VIRTUAL_ENV-}" - local conda_prefix="${CONDA_PREFIX}" + local conda_prefix="${CONDA_PREFIX-}" if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then echo "Using conda from: ${conda_prefix}" elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then diff --git a/ALCF/test_sirius.sh b/ALCF/test_sirius.sh index 39170fa47c..0a528a9519 100755 --- a/ALCF/test_sirius.sh +++ b/ALCF/test_sirius.sh @@ -54,7 +54,7 @@ setup_megatron_deepspeed() { main() { local virtual_env="${VIRTUAL_ENV-}" - local conda_prefix="${CONDA_PREFIX}" + local conda_prefix="${CONDA_PREFIX-}" if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then echo "Using conda from: ${conda_prefix}" elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then diff --git a/ALCF/test_sunspot.sh b/ALCF/test_sunspot.sh index b39bff7736..b3b22c78b4 100755 --- a/ALCF/test_sunspot.sh +++ b/ALCF/test_sunspot.sh @@ -53,7 +53,7 @@ setup_megatron_deepspeed() { main() { local virtual_env="${VIRTUAL_ENV-}" - local conda_prefix="${CONDA_PREFIX}" + local conda_prefix="${CONDA_PREFIX-}" if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then echo "Using conda from: ${conda_prefix}" elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then From 57f1c964052074e8b75d04ec1a0d4242e3ef1678 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 13:58:47 -0500 Subject: [PATCH 229/268] Add `ALCF/test_alcf.sh` --- ALCF/test_alcf.sh | 166 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 166 insertions(+) create mode 100644 ALCF/test_alcf.sh diff --git a/ALCF/test_alcf.sh b/ALCF/test_alcf.sh new file mode 100644 index 0000000000..367b40d17c --- /dev/null +++ b/ALCF/test_alcf.sh @@ -0,0 +1,166 @@ +#!/bin/bash --login +# +# Run complete test of +# https://github.com/argonne-lcf/Megatron-DeepSpeed +# on {Polaris, Sunspot, Sirius} @ ALCF +# to launch (inside an interactive `qsub -I` job) on Polaris: +# +# ```bash` +# $ git clone https://github.com/argonne-lcf/Megatron-DeepSpeed +# $ cd Megatron-DeepSpeed/ALCF +# $ bash test_alcf.sh +# ```` + +# EXIT ON ERROR(s) +set -euxo pipefail + +NOW="$(date "+%Y-%m-%d-%H%M%S")" + +setup_conda_sunspot() { + if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$(~/miniconda3/bin/conda shell hook -s posix)" + conda activate q4-drop + else + echo "Found existing python at: $(which python3)" + fi +} + +setup_conda_sirius() { + if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then + export MAMBA_ROOT_PREFIX=/lus/tegu/projects/PolarisAT/foremans/micromamba + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook --shell ${shell_name})" + micromamba activate 2024-04-23 + else + echo "Found existing python at: $(which python3)" + fi +} + +setup_conda_polaris() { + if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then + # export CUDA_HOME=/soft/compilers/cudatoolkit/cuda-12.2.2 + # && export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba && eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" ; mm activate 2024-04-25 + export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba + shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" + micromamba activate 2024-04-25 + else + echo "Found existing python at: $(which python3)" + fi +} + + +function setEnv() { + local virtual_env="${VIRTUAL_ENV-}" + local conda_prefix="${CONDA_PREFIX-}" + if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "Using conda from: ${conda_prefix}" + elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then + echo "Using virtual_env from: ${virtual_env}" + elif [[ -n "${virtual_env}" && -n "${conda_prefix}" ]]; then + echo "Using virtual_env: ${virtual_env} on top of CONDA: ${conda_prefix}" + elif [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "No conda_prefix or virtual_env found in environment..." + echo "Setting up conda" + # setup_conda + # ---- [SunSpot] ------- || ---- [Aurora] -------------- + if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then + source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit + # ----- [Aurora] ----------------------------------- + if [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then + if [[ $(hostname) == x4* ]]; then + eval "$(conda shell.zsh hook)" && conda activate anl_release_q4v2 + # ----- [SunSpot] ---------------------------------- + elif [[ $(hostname) == x1* ]]; then + echo "Running on SunSpot !!" + setup_conda_sunspot + # eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate q4-drop + fi + fi + # ----- [Polaris] --------------------------------------- + elif [[ $(hostname) == x3* ]]; then + if [[ "${PBS_O_HOST}" == sirius* ]]; then + echo "Running on Sirius !!" + setup_conda_sirius + else + echo "Running on Polaris !!" + # ---- [load conda] --------------------- + setup_conda_polaris + # if [[ -d "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221" ]]; then + # source "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221/bin/activate" + # fi + fi + elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then + echo "Running on Perlmutter !!" + module load pytorch + source "${SLURM_SUBMIT_DIR}/venvs/perlmutter/pytorch-2.1.0-cu12/bin/activate" + else # ------------------------------------- [Unknown] ------------------- + echo "Unknown hostname $(hostname)" + exit 1 + fi + else + echo "Unable to setup python environment. Exiting" + exit 1 + fi + echo "[python] Using: $(which python3)" +} + + + +######################################## +# Make sure ./tmp/Megatron-DeepSpeed +# does not already exist +######################################## +setup_megatron_deepspeed() { + OUTDIR="OUTPUTS/test-polaris-${NOW}" && mkdir -p "${OUTDIR}" && cd "${OUTDIR}" + echo "Running test in: ${OUTDIR}" + echo "WORKING DIRECTORY: $(realpath $(pwd .))" + if [[ -d "Megatron-DeepSpeed" ]]; then + echo "Found existing Megatron-DeepSpeed in ${OUTDIR}" + echo "Remove Megatron-DeepSpeed from ${OUTDIR} to run test." + exit + fi + git clone https://github.com/argonne-lcf/Megatron-DeepSpeed && cd Megatron-DeepSpeed + if [[ -n "${GIT_BRANCH-}" ]]; then + git checkout "${GIT_BRANCH}" + fi +} + + +main() { + local virtual_env="${VIRTUAL_ENV-}" + local conda_prefix="${CONDA_PREFIX-}" + if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "Using conda from: ${conda_prefix}" + elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then + echo "Using virtual_env from: ${virtual_env}" + elif [[ -n "${virtual_env}" && -n "${conda_prefix}" ]]; then + echo "Using virtual_env: ${virtual_env} on top of CONDA: ${conda_prefix}" + elif [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "No conda_prefix or virtual_env found in environment..." + echo "Setting up conda" + setup_conda + else + echo "Unable to setup python. Exiting" + exit 1 + fi + setup_megatron_deepspeed + export DEBUG=1 + export PBS_O_WORKDIR="$(pwd)" + SUBMITTED_FROM=$(echo $PBS_O_HOST | tr '-' ' ' | awk '{print $1}') + export DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/${SUBMITTED_FROM}/books.txt" + if [[ ! -f "${DATA_FILE_LIST}" ]]; then + echo "Unable to find / use ${DATA_FILE_LIST}. Exiting." + exit 1 + fi + export ZERO_STAGE=1 + export NUM_LAYERS=10 + export MICRO_BATCH=8 + export TRAIN_ITER=20 + export TIMING_LOG_LEVEL=1 + bash train_llama_alcf.sh |& tee "test-${SUBMITTED_FROM}-${NOW}".log +} + +main + From 455126caa6a4bf21c2ab87eaee53b1ac7404acde Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 13:59:04 -0500 Subject: [PATCH 230/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 162 ++++++++++++++++++++++++++++-------------------- 1 file changed, 95 insertions(+), 67 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 7fa8e748c1..516bc59f4c 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -16,6 +16,17 @@ export WORKING_DIR="${WORKING_DIR}" printf "Using WORKING_DIR: %s\n" ${WORKING_DIR} +function check_and_kill_if_running() { + # kill $(ps aux | grep -E "$USER.+(mpi|main.py)" | grep -v grep | awk '{print $2}') + RUNNING_PIDS=$(lsof -i:29500 -Fp | head -n 1 | sed 's/^p//') + if [[ -n "${RUNNING_PIDS}" ]]; + then echo "Caught ${RUNNING_PIDS}" && kill "${RUNNING_PIDS}"; + else + echo "Not currently running. Continuing!" + fi +} + + function setupSrun() { if [[ $(hostname) == login* || $(hostname) == nid* ]]; then export NHOSTS="${SLURM_NNODES:-1}" @@ -100,26 +111,27 @@ function setParams() { if [[ $(hostname) == x4* || $(hostname) == x1* ]]; then TP=${TP:-1} # TP = 1 export CCL=${CCL:-ccl} # CCL - export BE="${CCL}" # BE = CCL + export BE="${CCL}" # COMMUNICATION BACKEND = CCL export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 - ####################################################### - # if NO_FLASH_ATTN is NON-empty; then NO FLASH ATTN !! + ############################################################## + # NOTE: if NO_FLASH_ATTN is NON-empty; then NO FLASH ATTN !! if [[ -n "${NO_FLASH_ATTN-}" ]]; then echo "Not using flash-attn!!" else LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-builder" fi - ####################################################### + ############################################################## # +--------[Polaris]-----------------------------------+ elif [[ $(hostname) == x3* ]]; then - TP=${TP:-1} # TP = 2 - export NCCL=${NCCL:-nccl} # NCCL - export BE="${NCCL}" # BE = NCCL - # export DTYPE=${DTYPE:-bf16} # DTYPE: BF16 ?? - export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 - export GRAD_ACC_STEPS=4 # GRADIENT_ACCUMULATION_STEPS - MICRO_BATCH=${MICRO_BATCH:-2} # MICRO_BATCH = 8 + TP=${TP:-1} # TP = 2 + export NCCL=${NCCL:-nccl} # NCCL + export BE="${NCCL}" # BE = NCCL + # export DTYPE=${DTYPE:-bf16} # DTYPE: BF16 ?? + export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 + export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-16} # GRADIENT_ACC_STEPS + # NOTE: MICRO_BATCH is exported below + MICRO_BATCH=${MICRO_BATCH:-1} # MICRO_BATCH = 8 if [[ -n "${NO_FLASH_ATTN-}" ]]; then echo "Not using flash-attn!!" else @@ -142,42 +154,40 @@ function setParams() { export TP="${TP}" export PP="${PP:-1}" export DTYPE="${DTYPE:-bf16}" - export OPT="${OPT:-adamw}" + export OPT="${OPT:-adamwschedulefree}" export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" NHOSTS=$(wc -l < "${HOSTFILE}") if [[ -z "${NGPU_PER_HOST-}" ]]; then NGPU_PER_HOST=$(python3 -c 'import ezpz as ez; print(ez.get_gpus_per_node())') fi export WORLD_SIZE="${WORLD_SIZE:-$(( NHOSTS * NGPU_PER_HOST ))}" - # export WORLD_SIZE="${WORLD_SIZE:-${NGPUS:-$(( ))}}" - # export WORLD_SIZE=${WORLD_SIZE:-$(wc -l < "${HOSTFILE}")} - # +---[Llama2 7B Config]-----------------------------+ + # +---[Llama2 7B Config]--------------------------------------------------+ export MODEL_KEY="Llama-7B" - export HEADS=${HEADS:-${NHEADS:-32}} - export NLAYERS=${NLAYERS:-${NUM_LAYERS:-32}} - export HIDDEN=${HIDDEN:-4096} - export NUM_KV_HEAD=${NUM_KV_HEAD:-8} - export FFN_HIDDEN_SIZE=${FFN_HIDDEN_SIZE:-11008} + export HEADS=${HEADS:-${NHEADS:-32}} # NUMBER OF ATEN HEADS + export NLAYERS=${NLAYERS:-${NUM_LAYERS:-32}} # NUMBER OF LAYERS + export HIDDEN=${HIDDEN:-4096} # HIDDEN SIZE + export NUM_KV_HEAD=${NUM_KV_HEAD:-8} # GROUP ATTENTION + export FFN_HIDDEN_SIZE=${FFN_HIDDEN_SIZE:-11008} # FFN HIDDEN SIZE # +---[Run Settings]------------------------------------------------------+ - export LR=${LR:-0.0003} # LEARNING_RATE - export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 - export ZERO_STAGE=${ZERO_STAGE:-1} # ZERO OFFLOADING STAGE - export MICRO_BATCH=${MICRO_BATCH:-8} # MICRO BATCH SIZE - export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} # GRADIENT ACCUMULATION STEPS - export EVAL_ITERS="${EVAL_ITERS:-10}" # NUMBER OF EVAL ITERS TO RUN - export TRAIN_ITER=${TRAIN_ITER:-317892} # NUMBER OF TRAIN ITERS - export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" # HOW FREQUENTLY TO RUN EVAL - export SAVE_INTERVAL=${SAVE_INTERVAL:-200} # HOW FREQUENTLY TO SAVE CKPTS - export TIMING_LOG_LEVEL="${TIMING_LOG_LEVEL:-1}" # TIMING VERBOSITY IN LOGS + export LR=${LR:-0.0003} # LEARNING_RATE + export LR_WARMUP_FRAC=${LR_WARMUP_FRAC:-0.05} # LEARNING RATE WARMUP + export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 + export ZERO_STAGE=${ZERO_STAGE:-1} # ZERO OFFLOADING STAGE + export MICRO_BATCH=${MICRO_BATCH:-8} # MICRO BATCH SIZE + export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-1} # GRADIENT ACCUMULATION STEPS + export EVAL_ITERS="${EVAL_ITERS:-10}" # NUMBER OF EVAL ITERS TO RUN + export TRAIN_ITER=${TRAIN_ITER:-317892} # NUMBER OF TRAIN ITERS + export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" # HOW FREQUENTLY TO RUN EVAL + export SAVE_INTERVAL=${SAVE_INTERVAL:-200} # HOW FREQUENTLY TO SAVE CKPTS + export TIMING_LOG_LEVEL="${TIMING_LOG_LEVEL:-1}" # TIMING VERBOSITY IN LOGS export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # USE ACTIVATION CHECKPOINTING ? export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) # MAX GLOBAL BATCH SIZE export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" # WILL USE MAX IF NOT SET IN ENVIRONMENT - tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model + tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" # USE TOKENIZER_MODEL from env, else fallback from ^ export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" # STRING FOR IDENTIFYING MODEL # +----[ADDITIONAL LLAMA SPECIFIC ARGUMENTS]------------------------------ export LLAMA_ARGS="${LLAMA_ARGS} --no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" - # +----------------------------------------------------------------------+ } @@ -312,7 +322,7 @@ function sumFiles() { # mine is called q4-drop ######################################################## setup_conda_sunspot() { - if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') eval "$(~/miniconda3/bin/conda shell hook -s posix)" conda activate q4-drop @@ -322,7 +332,7 @@ setup_conda_sunspot() { } setup_conda_sirius() { - if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then export MAMBA_ROOT_PREFIX=/lus/tegu/projects/PolarisAT/foremans/micromamba shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook --shell ${shell_name})" @@ -333,7 +343,9 @@ setup_conda_sirius() { } setup_conda_polaris() { - if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then + if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then + # export CUDA_HOME=/soft/compilers/cudatoolkit/cuda-12.2.2 + # && export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba && eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" ; mm activate 2024-04-25 export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" @@ -345,39 +357,55 @@ setup_conda_polaris() { function setEnv() { - # ---- [SunSpot] ------- || ---- [Aurora] -------------- - if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then - source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit - # ----- [Aurora] ----------------------------------- - if [[ -z "${CONDA_PREFIX}" && -z "${VIRTUAL_ENV}" ]]; then - if [[ $(hostname) == x4* ]]; then - eval "$(conda shell.zsh hook)" && conda activate anl_release_q4v2 - # ----- [SunSpot] ---------------------------------- - elif [[ $(hostname) == x1* ]]; then - echo "Running on SunSpot !!" - setup_conda_sunspot - # eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate q4-drop + local virtual_env="${VIRTUAL_ENV-}" + local conda_prefix="${CONDA_PREFIX-}" + if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "Using conda from: ${conda_prefix}" + elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then + echo "Using virtual_env from: ${virtual_env}" + elif [[ -n "${virtual_env}" && -n "${conda_prefix}" ]]; then + echo "Using virtual_env: ${virtual_env} on top of CONDA: ${conda_prefix}" + elif [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "No conda_prefix or virtual_env found in environment..." + echo "Setting up conda" + # setup_conda + # ---- [SunSpot] ------- || ---- [Aurora] -------------- + if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then + source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit + # ----- [Aurora] ----------------------------------- + if [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then + if [[ $(hostname) == x4* ]]; then + eval "$(conda shell.zsh hook)" && conda activate anl_release_q4v2 + # ----- [SunSpot] ---------------------------------- + elif [[ $(hostname) == x1* ]]; then + echo "Running on SunSpot !!" + setup_conda_sunspot + # eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate q4-drop + fi fi + # ----- [Polaris] --------------------------------------- + elif [[ $(hostname) == x3* ]]; then + if [[ "${PBS_O_HOST}" == sirius* ]]; then + echo "Running on Sirius !!" + setup_conda_sirius + else + echo "Running on Polaris !!" + # ---- [load conda] --------------------- + setup_conda_polaris + # if [[ -d "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221" ]]; then + # source "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221/bin/activate" + # fi + fi + elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then + echo "Running on Perlmutter !!" + module load pytorch + source "${SLURM_SUBMIT_DIR}/venvs/perlmutter/pytorch-2.1.0-cu12/bin/activate" + else # ------------------------------------- [Unknown] ------------------- + echo "Unknown hostname $(hostname)" + exit 1 fi - # ----- [Polaris] --------------------------------------- - elif [[ $(hostname) == x3* ]]; then - if [[ "${PBS_O_HOST}" == sirius* ]]; then - echo "Running on Sirius !!" - setup_conda_sirius - else - echo "Running on Polaris !!" - # ---- [load conda] --------------------- - setup_conda_polaris - # if [[ -d "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221" ]]; then - # source "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221/bin/activate" - # fi - fi - elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then - echo "Running on Perlmutter !!" - module load pytorch - source "${SLURM_SUBMIT_DIR}/venvs/perlmutter/pytorch-2.1.0-cu12/bin/activate" - else # ------------------------------------- [Unknown] ------------------- - echo "Unknown hostname $(hostname)" + else + echo "Unable to setup python environment. Exiting" exit 1 fi echo "[python] Using: $(which python3)" @@ -473,7 +501,7 @@ function generateDSconfig() { \"gradient_clipping\": 1.0, \"activation_checkpointing\": { \"partition_activations\": true, - \"contiguous_memory_optimization\": false + \"contiguous_memory_optimization\": true }, \"wall_clock_breakdown\": false," flops_profiler="\ From 2a49f6dcb55771fba1b8737060848a4f04ecdd2f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 13:59:49 -0500 Subject: [PATCH 231/268] Update `train_agpt.sh` --- train_agpt.sh | 1 + 1 file changed, 1 insertion(+) diff --git a/train_agpt.sh b/train_agpt.sh index 4129f553e2..a21b988073 100644 --- a/train_agpt.sh +++ b/train_agpt.sh @@ -8,4 +8,5 @@ mkdir -p "${OUTDIR}" OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" echo "${OUTFILE}" >> "${OUTDIR}/latest" echo "Logging job output to: ${OUTFILE}" +# export DEBUG=1 bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" From 482dffd1b27fa85f8f8b2365e65151624c078e95 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 26 Apr 2024 13:59:57 -0500 Subject: [PATCH 232/268] Update `train_llama_alcf.sh` --- train_llama_alcf.sh | 23 +++++++++++++++++------ 1 file changed, 17 insertions(+), 6 deletions(-) diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 462da0c4e1..5d728068a5 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -41,7 +41,7 @@ setParams || exit # 5. set command line arguments to pass to ` buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} setArgs || exit # 8. specify additional `deepspeed` arguments -setData "${DATA_FILE_LIST}"|| exit # 9. specify `DATA_FILE_LIST` for dolma dataset +setData "${DATA_FILE_LIST-}" || exit # 9. specify `DATA_FILE_LIST` for dolma dataset printJobInfo || exit # 11. print job info setupLauncher || exit # ----------------------------------------------------------------------------- @@ -75,6 +75,17 @@ data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" mkdir -p "${data_cache_path}" module list +if [[ "${TIMING_LOG_LEVEL}" -ge 1 ]]; then + TIMING_STR="\ + --timing-log-level ${TIMING_LOG_LEVEL} \ + --log-timers-to-tensorboard \ + --log-optimizer-states-to-tensorboard \ + " +else + TIMING_STR="" +fi + + # Take custom args custom_args=" $@" @@ -83,7 +94,6 @@ custom_args=" $@" run_cmd=" ${LAUNCH_CMD} \ --${DTYPE} \ - --optimizer ${OPT} \ --split 100,0,0 \ --log-interval 1 \ --no-bias-gelu-fusion \ @@ -94,16 +104,17 @@ run_cmd=" --no-gradient-accumulation-fusion \ --accumulate-allreduce-grads-in-fp32 \ --use-checkpoint-opt_param-scheduler \ - --tensorboard-dir ${TBDIR} \ --log-timers-to-tensorboard \ --log-optimizer-states-to-tensorboard \ --lr ${LR} \ + --optimizer ${OPT} \ --save ${CKPT_DIR} \ --load ${CKPT_DIR} \ --seq-length ${SEQ} \ --num-layers ${NLAYERS} \ --hidden-size ${HIDDEN} \ --train-iters ${TRAIN_ITER} \ + --tensorboard-dir ${TBDIR} \ --eval-iters ${EVAL_ITERS} \ --distributed-backend ${BE} \ --num-attention-heads ${HEADS} \ @@ -119,16 +130,16 @@ run_cmd=" --data-cache-path ${data_cache_path} \ --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ --tokenizer-model ${TOKENIZER_MODEL} \ - --timing-log-level ${TIMING_LOG_LEVEL} \ - --log-timers-to-tensorboard \ - --log-optimizer-states-to-tensorboard \ + --lr-warmup-fraction ${LR_WARMUP_FRAC} \ ${LLAMA_ARGS} \ + ${TIMING_STR} \ $ds_args \ ${gpt_args[*]} \ $custom_args \ |& tee ${OUTPUT_LOG} " +check_and_kill_if_running || exit echo "${run_cmd}" printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" From c04c42da256eeb809a63b758a1f782514c243958 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 27 Apr 2024 00:22:39 -0500 Subject: [PATCH 233/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 516bc59f4c..8976247b09 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -129,9 +129,9 @@ function setParams() { export BE="${NCCL}" # BE = NCCL # export DTYPE=${DTYPE:-bf16} # DTYPE: BF16 ?? export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 - export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-16} # GRADIENT_ACC_STEPS + export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-8} # GRADIENT_ACC_STEPS # NOTE: MICRO_BATCH is exported below - MICRO_BATCH=${MICRO_BATCH:-1} # MICRO_BATCH = 8 + MICRO_BATCH=${MICRO_BATCH:-2} # MICRO_BATCH = 8 if [[ -n "${NO_FLASH_ATTN-}" ]]; then echo "Not using flash-attn!!" else @@ -180,6 +180,7 @@ function setParams() { export EVAL_INTERVAL="${EVAL_INTERVAL:-50000}" # HOW FREQUENTLY TO RUN EVAL export SAVE_INTERVAL=${SAVE_INTERVAL:-200} # HOW FREQUENTLY TO SAVE CKPTS export TIMING_LOG_LEVEL="${TIMING_LOG_LEVEL:-1}" # TIMING VERBOSITY IN LOGS + export ACT_CKPT_NUM_LAYERS="${ACT_CKPT_NUM_LAYERS:-1}" # NUM LAYERS TO CHECKPOINT ACTIVATIONS export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # USE ACTIVATION CHECKPOINTING ? export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) # MAX GLOBAL BATCH SIZE export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" # WILL USE MAX IF NOT SET IN ENVIRONMENT @@ -215,7 +216,7 @@ function setArgs() { echo "!! Caught USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING} !!" gpt_args+=( "--checkpoint-activations" - "--checkpoint-num-layers 1" + "--checkpoint-num-layers ${ACT_CKPT_NUM_LAYERS}" ) fi export gpt_args @@ -432,7 +433,7 @@ function setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------ dfl_fallback="${WORKING_DIR}/ALCF/data-lists/sirius/books.txt" elif [[ "${PBS_O_HOST}" == polaris* ]]; then # shellcheck: source ./data-lists/polaris/books.txt - dfl_fallback="${WORKING_DIR}/ALCF/data-lists/polaris/books.txt" + dfl_fallback="${WORKING_DIR}/ALCF/data-lists/polaris/dolma_v1_7_file_list.txt" fi elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then dfl_fallback="${SLURM_SUBMIT_DIR}/genslm-subsample.txt" From 36fa52093fa09602bbce890169623c2ac50def6a Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 1 May 2024 12:56:41 -0500 Subject: [PATCH 234/268] Fix for `conda/2024-04-29` on Polaris --- ALCF/helpers.sh | 17 ++++++++++++----- pretrain_gpt_alcf.py | 5 ++++- 2 files changed, 16 insertions(+), 6 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 8976247b09..0f7b1f3559 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -79,7 +79,7 @@ function loadCondaEnv() { function setupLauncher() { # outdir=$1 if [[ -n "${DIST_LAUNCH}" && ${LAUNCH_CMD:-"MPICH"} != "deepspeed" ]]; then - export LAUNCH_CMD="${DIST_LAUNCH} --cpu-bind depth -d 16 python3 -Wignore ${EXEC}" + export LAUNCH_CMD="${DIST_LAUNCH} --genvall --cpu-bind depth -d 16 $(which python3) -Wignore ${EXEC}" else # Assert `./hostfile_deepspeed` exists export hfds="${WORKING_DIR}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit @@ -124,6 +124,7 @@ function setParams() { ############################################################## # +--------[Polaris]-----------------------------------+ elif [[ $(hostname) == x3* ]]; then + # export LAUNCH_CMD="${LAUNCH_CMD:-deepspeed}" TP=${TP:-1} # TP = 2 export NCCL=${NCCL:-nccl} # NCCL export BE="${NCCL}" # BE = NCCL @@ -347,10 +348,16 @@ setup_conda_polaris() { if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then # export CUDA_HOME=/soft/compilers/cudatoolkit/cuda-12.2.2 # && export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba && eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" ; mm activate 2024-04-25 - export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba - shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') - eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" - micromamba activate 2024-04-25 + # export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba + # shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') + # eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" + # micromamba activate 2024-04-25 + module use /soft/modulefiles + module load conda/2024-04-29 ; conda activate base + # unset MPICH_GPU_SUPPORT_ENABLED + # if [[ -d "${WORKING_DIR}/venvs/polaris/2024-04-29" ]]; then + # source "${WORKING_DIR}/venvs/polaris/2024-04-29/bin/activate" + # fi else echo "Found existing python at: $(which python3)" fi diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index f83ef05fc8..2c521a400a 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -2,6 +2,7 @@ """Pretrain GPT""" +from mpi4py import MPI import os from rich import print import torch @@ -40,8 +41,10 @@ # ---- [SETUP COMMS] ------------------------ +# if str(os.environ.get('LAUNCH_CMD', 'mpich')).lower() == 'mpich': RANK = ez.setup_torch(backend="deepspeed") -# RANK = ez.get_rank() +# else: +# RANK = ez.get_rank() WORLD_SIZE = ez.get_world_size() LOCAL_RANK = ez.get_local_rank() DEVICE = ez.get_torch_device() From 3b83b36b1dac258b3ae40d6ba3a3fcfe41165b06 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 1 May 2024 12:57:54 -0500 Subject: [PATCH 235/268] Add `train_agpt_polaris_7B_production.sh` --- train_agpt_polaris_7B_production.sh | 13 +++++++++++++ 1 file changed, 13 insertions(+) create mode 100644 train_agpt_polaris_7B_production.sh diff --git a/train_agpt_polaris_7B_production.sh b/train_agpt_polaris_7B_production.sh new file mode 100644 index 0000000000..8b45ddc30a --- /dev/null +++ b/train_agpt_polaris_7B_production.sh @@ -0,0 +1,13 @@ +#!/bin/bash --login + +NOW="$(date "+%Y-%m-%d-%H%M%S")" +cd "${PBS_O_WORKDIR}" || exit + +OUTDIR="${PBS_O_WORKDIR}/pbslogs" +mkdir -p "${OUTDIR}" +OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" +echo "${OUTFILE}" >> "${OUTDIR}/latest" +echo "Logging job output to: ${OUTFILE}" +export TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC=6000 +# export DEBUG=1 +MICRO_BATCH=2 DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/polaris/dolma_v1_7_file_list.txt" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" From a916a8dd724e232c2db46b5ceb90143469681774 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 1 May 2024 13:50:58 -0500 Subject: [PATCH 236/268] Update `ALCF/helpers.sh` on Sunspot --- ALCF/helpers.sh | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 0f7b1f3559..d42888b56e 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -113,6 +113,7 @@ function setParams() { export CCL=${CCL:-ccl} # CCL export BE="${CCL}" # COMMUNICATION BACKEND = CCL export DTYPE=${DTYPE:-bf16} # DTYPE: bf16 + export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-8} # GRADIENT_ACC_STEPS MICRO_BATCH=${MICRO_BATCH:-4} # MICRO_BATCH = 4 ############################################################## # NOTE: if NO_FLASH_ATTN is NON-empty; then NO FLASH ATTN !! @@ -326,7 +327,7 @@ function sumFiles() { setup_conda_sunspot() { if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') - eval "$(~/miniconda3/bin/conda shell hook -s posix)" + eval "$(~/miniconda3/bin/conda shell.${shell_name} hook)" conda activate q4-drop else echo "Found existing python at: $(which python3)" From 5257721b69e40c635df1e42f08d04bd6f21cdf73 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Wed, 8 May 2024 08:27:09 -0500 Subject: [PATCH 237/268] Update `ALCF/test_alcf.sh` --- ALCF/test_alcf.sh | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/ALCF/test_alcf.sh b/ALCF/test_alcf.sh index 367b40d17c..853addc59d 100644 --- a/ALCF/test_alcf.sh +++ b/ALCF/test_alcf.sh @@ -154,9 +154,9 @@ main() { echo "Unable to find / use ${DATA_FILE_LIST}. Exiting." exit 1 fi - export ZERO_STAGE=1 - export NUM_LAYERS=10 - export MICRO_BATCH=8 + # export ZERO_STAGE=1 + # export NUM_LAYERS=10 + # export MICRO_BATCH=8 export TRAIN_ITER=20 export TIMING_LOG_LEVEL=1 bash train_llama_alcf.sh |& tee "test-${SUBMITTED_FROM}-${NOW}".log From 1ad039c4d76bd661ddd4fddf59d14eb1fffce0b1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 9 May 2024 12:45:49 -0500 Subject: [PATCH 238/268] Add `train_agpt_polaris_7B_production_NCCL_OFI.sh` --- train_agpt_polaris_7B_production_NCCL_OFI.sh | 23 ++++++++++++++++++++ 1 file changed, 23 insertions(+) create mode 100644 train_agpt_polaris_7B_production_NCCL_OFI.sh diff --git a/train_agpt_polaris_7B_production_NCCL_OFI.sh b/train_agpt_polaris_7B_production_NCCL_OFI.sh new file mode 100644 index 0000000000..fd787dc80f --- /dev/null +++ b/train_agpt_polaris_7B_production_NCCL_OFI.sh @@ -0,0 +1,23 @@ +#!/bin/bash --login + +NOW="$(date "+%Y-%m-%d-%H%M%S")" +cd "${PBS_O_WORKDIR}" || exit + +OUTDIR="${PBS_O_WORKDIR}/pbslogs" +mkdir -p "${OUTDIR}" +OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" +echo "${OUTFILE}" >> "${OUTDIR}/latest" +echo "Logging job output to: ${OUTFILE}" + +# export NCCL_NET_GDR_LEVEL=PHB +export NCCL_CROSS_NIC=1 +export NCCL_COLLNET_ENABLE=1 +export NCCL_NET="AWS Libfabric" +export LD_LIBRARY_PATH=/soft/libraries/aws-ofi-nccl/v1.9.1-aws/lib:$LD_LIBRARY_PATH +export LD_LIBRARY_PATH=/soft/libraries/hwloc/lib/:$LD_LIBRARY_PATH +export FI_CXI_DISABLE_HOST_REGISTER=1 +export FI_MR_CACHE_MONITOR=userfaultfd +export FI_CXI_DEFAULT_CQ_SIZE=131072 +# export DEBUG=1 +MICRO_BATCH=4 DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/polaris/dolma_v1_7_file_list.txt" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" +# MICRO_BATCH=1 DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/polaris/books.txt" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" From 328dfda088ac98090627ac95e9abd9932f1d57a3 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 14 May 2024 20:43:19 -0500 Subject: [PATCH 239/268] Create `flash-attn-fix` branch --- ALCF/aws_ofi_nccl_plugin.sh | 20 ++++ ALCF/helpers.sh | 103 ++++++++++++------- pretrain_gpt_alcf.py | 2 +- train_agpt_polaris_7B_production.sh | 28 +++-- train_agpt_polaris_7B_production_NCCL_OFI.sh | 23 ----- 5 files changed, 111 insertions(+), 65 deletions(-) create mode 100644 ALCF/aws_ofi_nccl_plugin.sh delete mode 100644 train_agpt_polaris_7B_production_NCCL_OFI.sh diff --git a/ALCF/aws_ofi_nccl_plugin.sh b/ALCF/aws_ofi_nccl_plugin.sh new file mode 100644 index 0000000000..ffd1471cd3 --- /dev/null +++ b/ALCF/aws_ofi_nccl_plugin.sh @@ -0,0 +1,20 @@ +#!/bin/bash --login + +# AWS NCCL OFI Plugin settings below +export NCCL_CROSS_NIC=1 +export NCCL_COLLNET_ENABLE=1 +export NCCL_NET="AWS Libfabric" +export LD_LIBRARY_PATH=/soft/libraries/aws-ofi-nccl/v1.9.1-aws/lib:$LD_LIBRARY_PATH +export LD_LIBRARY_PATH=/soft/libraries/hwloc/lib/:$LD_LIBRARY_PATH +export FI_CXI_DISABLE_HOST_REGISTER=1 +export FI_MR_CACHE_MONITOR=userfaultfd +export FI_CXI_DEFAULT_CQ_SIZE=131072 +######################################################### +# WARNING: !!! +# - Currently, `export NCCL_NET_GDR_LEVEL=PHB` +# causes a hang on Polaris. +# so, we don't set it for the time being [2024-05-14]. +# - Seems to work on Perlmutter ??? +# +# export NCCL_NET_GDR_LEVEL=PHB +######################################################### diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index d42888b56e..a257c3fb3f 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -156,7 +156,7 @@ function setParams() { export TP="${TP}" export PP="${PP:-1}" export DTYPE="${DTYPE:-bf16}" - export OPT="${OPT:-adamwschedulefree}" + export OPT="${OPT:-adamw}" export HOSTFILE="${HOSTFILE:-${PBS_NODEFILE}}" NHOSTS=$(wc -l < "${HOSTFILE}") if [[ -z "${NGPU_PER_HOST-}" ]]; then @@ -322,9 +322,8 @@ function sumFiles() { ######################################################## # Setup / activate conda environment, -# mine is called q4-drop ######################################################## -setup_conda_sunspot() { +setup_conda_sunspot() { # mine is called `q4-drop` on Sunspot if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') eval "$(~/miniconda3/bin/conda shell.${shell_name} hook)" @@ -334,6 +333,9 @@ setup_conda_sunspot() { fi } +######################## +# Setup conda on Sirius +######################## setup_conda_sirius() { if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then export MAMBA_ROOT_PREFIX=/lus/tegu/projects/PolarisAT/foremans/micromamba @@ -345,20 +347,27 @@ setup_conda_sirius() { fi } +######################## +# Setup conda on Polaris +######################## setup_conda_polaris() { - if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then - # export CUDA_HOME=/soft/compilers/cudatoolkit/cuda-12.2.2 - # && export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba && eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" ; mm activate 2024-04-25 - # export MAMBA_ROOT_PREFIX=/eagle/argonne_tpc/micromamba - # shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') - # eval "$("${MAMBA_ROOT_PREFIX}/bin/micromamba" shell hook -s posix)" - # micromamba activate 2024-04-25 + # unset MPICH_GPU_SUPPORT_ENABLED + ###### check if CONDA_PREFIX non-empty ################ + if [[ -z "${CONDA_PREFIX-}" ]]; then + # if so, load the default conda/2024-04-29 + # module and activate base environment module use /soft/modulefiles module load conda/2024-04-29 ; conda activate base - # unset MPICH_GPU_SUPPORT_ENABLED - # if [[ -d "${WORKING_DIR}/venvs/polaris/2024-04-29" ]]; then - # source "${WORKING_DIR}/venvs/polaris/2024-04-29/bin/activate" - # fi + else + echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" + fi + ###### check if VIRTUAL_ENV non-empty ################# + if [[ -z "${VIRTUAL_ENV:-}" ]]; then + DEFAULT_VENV_PATH=${WORKING_DIR}/venvs/polaris/2024-04-29 + if [[ -d "${DEFAULT_VENV_PATH}" ]]; then + echo "Caught virtual env at ${DEFAULT_VENV_PATH}!" + source "${WORKING_DIR}/venvs/polaris/2024-04-29/bin/activate" + fi else echo "Found existing python at: $(which python3)" fi @@ -369,42 +378,42 @@ function setEnv() { local virtual_env="${VIRTUAL_ENV-}" local conda_prefix="${CONDA_PREFIX-}" if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then + echo "No virtual environment found." echo "Using conda from: ${conda_prefix}" elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then + echo "No conda found." echo "Using virtual_env from: ${virtual_env}" elif [[ -n "${virtual_env}" && -n "${conda_prefix}" ]]; then - echo "Using virtual_env: ${virtual_env} on top of CONDA: ${conda_prefix}" + echo "Using virtual_env: ${virtual_env} on top of conda from: ${conda_prefix}" elif [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then echo "No conda_prefix or virtual_env found in environment..." - echo "Setting up conda" - # setup_conda + echo "Setting up conda..." + ######################## setup_conda ############################ # ---- [SunSpot] ------- || ---- [Aurora] -------------- if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit - # ----- [Aurora] ----------------------------------- + # ----- [Aurora] -------------------------------------------- if [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then if [[ $(hostname) == x4* ]]; then eval "$(conda shell.zsh hook)" && conda activate anl_release_q4v2 - # ----- [SunSpot] ---------------------------------- + # ----- [SunSpot] --------------------------------------- elif [[ $(hostname) == x1* ]]; then echo "Running on SunSpot !!" setup_conda_sunspot - # eval "$(/home/foremans/miniconda3/bin/conda shell.zsh hook)" && conda activate q4-drop fi fi - # ----- [Polaris] --------------------------------------- + # ----- [Polaris] ----------------------------------------------- elif [[ $(hostname) == x3* ]]; then if [[ "${PBS_O_HOST}" == sirius* ]]; then echo "Running on Sirius !!" setup_conda_sirius else echo "Running on Polaris !!" - # ---- [load conda] --------------------- + # ---- [load conda] ------------------------------------- setup_conda_polaris - # if [[ -d "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221" ]]; then - # source "${PBS_O_WORKDIR}/venvs/polaris/cu118-pt221/bin/activate" - # fi fi + echo "Setting up AWS NCCL OFI Plugin on Polaris..." + source "${WORKING_DIR}/ALCF/aws_ofi_nccl_plugin.sh" || exit elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then echo "Running on Perlmutter !!" module load pytorch @@ -417,10 +426,19 @@ function setEnv() { echo "Unable to setup python environment. Exiting" exit 1 fi - echo "[python] Using: $(which python3)" + printf "\n" + pystr="Using: $(which python3)" + printf "[python] %s" "$(printMagenta ${pystr})" + printf "\n" } +###################################################################### +# `makeHostiles`: +# Detect if `HOSTFILE` set in active environment. +# - If so, use this. +# - Otherwise, make default HOSTFILEs from "${PBS_NODEFILE}" +###################################################################### function makeHostfiles() { if [[ -n "${HOSTFILE}" ]]; then printf "!! USING CUSTOM HOSTFILE FROM: %s" "${HOSTFILE}" @@ -429,25 +447,40 @@ function makeHostfiles() { fi } -function setData() { # ---- [dfl: abbrv. for DATA_FILE_LIST] ------------------------- - if [[ $(hostname) == x4* ]]; then # ---- [AURORA] ---- +############################################### +# `setData`: +# Ensure `DATA_FILE_LIST` is set, +# fallback to default values if necessary. +############################################### +function setData() { # ----------------------[dfl: abbrv. for DATA_FILE_LIST] + # dfldir="${WORKING_DIR}/ALCF/data-lists" + # =====[Set DATA_FILE_LIST_FALLBACK based on current machine]============== + if [[ $(hostname) == x4* ]]; then # ---------------------------[AURORA] dfl_fallback="/home/foremans/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed/data_file_list_reweighted.txt" - elif [[ $(hostname) == x1* ]]; then + + elif [[ $(hostname) == x1* ]]; then # --------------------------[SUNSPOT] # shellcheck: source ./data-lists/sunspot/books.txt dfl_fallback="${WORKING_DIR}/ALCF/data-lists/sunspot/books.txt" - elif [[ $(hostname) == x3* ]]; then - if [[ "${PBS_O_HOST}" == sirius* ]]; then + + elif [[ $(hostname) == x3* ]]; then # -------------------[POLARIS / SIRIUS] + if [[ "${PBS_O_HOST}" == sirius* ]]; then # -------------------[SIRIUS] # shellcheck: source ./data-lists/sirius/books.txt dfl_fallback="${WORKING_DIR}/ALCF/data-lists/sirius/books.txt" - elif [[ "${PBS_O_HOST}" == polaris* ]]; then + + elif [[ "${PBS_O_HOST}" == polaris* ]]; then # ---------------[POLARIS] # shellcheck: source ./data-lists/polaris/books.txt dfl_fallback="${WORKING_DIR}/ALCF/data-lists/polaris/dolma_v1_7_file_list.txt" fi - elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then + + elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then # [PERLMUTTER] dfl_fallback="${SLURM_SUBMIT_DIR}/genslm-subsample.txt" - else + + else # -----------------------------------------------------------[UNKNOWN] echo "Unknown hostname. Must manually specify DATA_FILE_LIST." fi + # ========================================================================== + # set `dfl` to `dfl_fallback` if not passed as an argument, + # use this data file list to call `setData` dfl="${1:-${dfl_fallback}}" printf "Calling: setData() with %s\n" "${dfl}" ndocs=$(wc -l < "${dfl}") @@ -516,7 +549,7 @@ function generateDSconfig() { flops_profiler="\ \"flops_profiler\": { \"enabled\": true, - \"profile_step\": 4, + \"profile_step\": 2, \"module_depth\": -1, \"top_modules\": 1, \"detailed\": true, diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 2c521a400a..750bd21e48 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -42,7 +42,7 @@ # ---- [SETUP COMMS] ------------------------ # if str(os.environ.get('LAUNCH_CMD', 'mpich')).lower() == 'mpich': -RANK = ez.setup_torch(backend="deepspeed") +RANK = ez.setup_torch(backend="deepspeed", timeout=7200) # else: # RANK = ez.get_rank() WORLD_SIZE = ez.get_world_size() diff --git a/train_agpt_polaris_7B_production.sh b/train_agpt_polaris_7B_production.sh index 8b45ddc30a..f83b6ebc29 100644 --- a/train_agpt_polaris_7B_production.sh +++ b/train_agpt_polaris_7B_production.sh @@ -1,13 +1,29 @@ #!/bin/bash --login +# +# This script can be submitted with `qsub` via: +# +# ```bash +# $ git clone https://github.com/argonee-lcf/Megatron-DeepSpeed +# $ cd Megatron-DeepSpeed +# $ qsub train_agpt_polaris_7B_production.sh +# ``` -NOW="$(date "+%Y-%m-%d-%H%M%S")" cd "${PBS_O_WORKDIR}" || exit -OUTDIR="${PBS_O_WORKDIR}/pbslogs" -mkdir -p "${OUTDIR}" +TODAY="$(date "+%Y-%m-%d")" +NOW="$(date "+%Y-%m-%d-%H%M%S")" +OUTDIR="${PBS_O_WORKDIR}/pbslogs/${TODAY}" OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" -echo "${OUTFILE}" >> "${OUTDIR}/latest" +mkdir -p $(dirname "${OUTFILE}") + +echo "${OUTFILE}" >> "$(dirname ${OUTDIR})/latest" echo "Logging job output to: ${OUTFILE}" -export TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC=6000 + # export DEBUG=1 -MICRO_BATCH=2 DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/polaris/dolma_v1_7_file_list.txt" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" +# export TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC=6000 + +# Path to the data file list: +DFL="${PBS_O_WORKDIR}/ALCF/data-lists/polaris/dolma_v1_7_file_list.txt" + +# Launch: +MICRO_BATCH=2 DATA_FILE_LIST="${DFL}" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" diff --git a/train_agpt_polaris_7B_production_NCCL_OFI.sh b/train_agpt_polaris_7B_production_NCCL_OFI.sh deleted file mode 100644 index fd787dc80f..0000000000 --- a/train_agpt_polaris_7B_production_NCCL_OFI.sh +++ /dev/null @@ -1,23 +0,0 @@ -#!/bin/bash --login - -NOW="$(date "+%Y-%m-%d-%H%M%S")" -cd "${PBS_O_WORKDIR}" || exit - -OUTDIR="${PBS_O_WORKDIR}/pbslogs" -mkdir -p "${OUTDIR}" -OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" -echo "${OUTFILE}" >> "${OUTDIR}/latest" -echo "Logging job output to: ${OUTFILE}" - -# export NCCL_NET_GDR_LEVEL=PHB -export NCCL_CROSS_NIC=1 -export NCCL_COLLNET_ENABLE=1 -export NCCL_NET="AWS Libfabric" -export LD_LIBRARY_PATH=/soft/libraries/aws-ofi-nccl/v1.9.1-aws/lib:$LD_LIBRARY_PATH -export LD_LIBRARY_PATH=/soft/libraries/hwloc/lib/:$LD_LIBRARY_PATH -export FI_CXI_DISABLE_HOST_REGISTER=1 -export FI_MR_CACHE_MONITOR=userfaultfd -export FI_CXI_DEFAULT_CQ_SIZE=131072 -# export DEBUG=1 -MICRO_BATCH=4 DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/polaris/dolma_v1_7_file_list.txt" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" -# MICRO_BATCH=1 DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/polaris/books.txt" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" From bd8cb0917cf0ca4700f68a0b33ffc26fc20e4718 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 14 May 2024 20:44:13 -0500 Subject: [PATCH 240/268] Add + pass default `LR_DECAY_ITERS` --- ALCF/helpers.sh | 9 +++++++-- train_llama_alcf.sh | 1 + 2 files changed, 8 insertions(+), 2 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index a257c3fb3f..e66d5ff500 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -173,6 +173,7 @@ function setParams() { # +---[Run Settings]------------------------------------------------------+ export LR=${LR:-0.0003} # LEARNING_RATE export LR_WARMUP_FRAC=${LR_WARMUP_FRAC:-0.05} # LEARNING RATE WARMUP + export LR_DECAY_ITERS=${LR_DECAY_ITERS:-320000} # LR DECAY ITERS export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 export ZERO_STAGE=${ZERO_STAGE:-1} # ZERO OFFLOADING STAGE export MICRO_BATCH=${MICRO_BATCH:-8} # MICRO BATCH SIZE @@ -281,7 +282,10 @@ function saveDSenv() { function setOutput() { # ---- Specify output location -------------------------------- - export OUTPUT_PREFIX="ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" + export OUTPUT_PREFIX="ws${WORLD_SIZE}_ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" + if [[ -z "${NO_FLASH_ATTN:-}" ]]; then + export OUTPUT_PREFIX="${OUTPUT_PREFIX}_flash" + fi # OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%Y%m%d-%H%M%S)_${WORLD_SIZE}_${HOSTNAME}" export OUTPUT_DIR="${OUTPUT_DIR}" @@ -289,7 +293,8 @@ function setOutput() { export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" echo "${OUTPUT_LOG}" >> "logs/latest" mkdir -p "${OUTPUT_DIR}" - echo "!!!Please see logs at ${OUTPUT_DIR}" + printf "Please see logs at: %s\n" $(printGreen "${OUTPUT_DIR}") + printf "Checkpoints will be saved to: %s\n" $(printYellow "${CKPT_DIR}") } function buildDSconfig() { diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 5d728068a5..3e0f9390cb 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -124,6 +124,7 @@ run_cmd=" --micro-batch-size ${MICRO_BATCH} \ --data-file-list ${DATA_FILE_LIST} \ --tensor-model-parallel-size ${TP} \ + --lr-decay-iters ${LR_DECAY_ITERS} \ --global-batch-size ${GLOBAL_BATCH} \ --pipeline-model-parallel-size ${PP} \ --num-key-value-heads ${NUM_KV_HEAD} \ From 59f60522b486738e443177296af43c5807f8a57b Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 14 May 2024 20:45:16 -0500 Subject: [PATCH 241/268] Add `aGPT_7B.sh` --- aGPT_7B.sh | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100644 aGPT_7B.sh diff --git a/aGPT_7B.sh b/aGPT_7B.sh new file mode 100644 index 0000000000..0c192b1b4f --- /dev/null +++ b/aGPT_7B.sh @@ -0,0 +1,34 @@ +#!/bin/bash --login +# +HOSTNAME=$(hostname) +if [[ "${HOSTNAME}" == x3* ]]; then + MACHINE="polaris" +elif [[ "${HOSTNAME}" == x1* ]]; then + MACHINE="sunspot" +elif [[ "${HOSTNAME}" == x4* ]]; then + MACHINE="aurora" +fi + +NOW="$(date "+%Y-%m-%d-%H%M%S")" +cd "${PBS_O_WORKDIR}" || exit +nhosts=$(wc -l < "${HOSTFILE}") + +if [[ "${nhosts}" == 1 || "${nhosts}" == 2 ]]; then + MBS=1 +elif [[ "${nhosts}" -ge 2 ]]; then + MBS=2 +elif [[ "${nhosts}" -ge 8 ]]; then + MBS=4 +fi + +printf "Detected %s hosts. Running with micro_batch:\n" ${nhosts} ${MBS} + +OUTDIR="${PBS_O_WORKDIR}/pbslogs" +mkdir -p "${OUTDIR}" +OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" +echo "Running on: ${MACHINE}" +echo "${OUTFILE}" >> "${OUTDIR}/latest" +echo "Logging job output to: ${OUTFILE}" +export TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC=6000 +# export DEBUG=1 +MICRO_BATCH="${MBS}" DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/${MACHINE}/dolma_v1_7_file_list.txt" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" From 9f98c0912437f2abbd05c663e54c5329210c7d91 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 14 May 2024 20:46:21 -0500 Subject: [PATCH 242/268] Update `.gitignore` --- .gitignore | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.gitignore b/.gitignore index 3b18d4956a..0a1387f56a 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,6 @@ # User Added +**.e1** +**.o1** deps/* OUTPUTS/* ALCF/OUTPUTS/* From 2cc2965c4831cda9621ce4781b3b24f478faa68c Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Tue, 14 May 2024 20:47:54 -0500 Subject: [PATCH 243/268] Rename `aGPT_7B.sh` -> `train_aGPT_7B.sh` --- aGPT_7B.sh => train_aGPT_7B.sh | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename aGPT_7B.sh => train_aGPT_7B.sh (100%) diff --git a/aGPT_7B.sh b/train_aGPT_7B.sh similarity index 100% rename from aGPT_7B.sh rename to train_aGPT_7B.sh From 05e8af3ad75b969f05c1a294ac7ccedfdf30a171 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 16 May 2024 10:43:50 -0500 Subject: [PATCH 244/268] Add `ALCF/aws_ofi_nccl_plugin.sh` for Polaris --- ALCF/helpers.sh | 44 +++++++++++++++++++++++++++++++++----------- train_aGPT_7B.sh | 25 ++++++++++++++++--------- train_llama_alcf.sh | 21 +++++++++++---------- 3 files changed, 60 insertions(+), 30 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index e66d5ff500..1bd0febf24 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -16,6 +16,27 @@ export WORKING_DIR="${WORKING_DIR}" printf "Using WORKING_DIR: %s\n" ${WORKING_DIR} +function get_machine() { + if [[ $(hostname) == x4* ]]; then + machine="aurora" + elif [[ $(hostname) == x1* ]]; then + machine="sunspot" + elif [[ $(hostname) == x3* ]]; then + if [[ "${PBS_O_HOST}" == sirius* ]]; then + machine="sirius" + else + machine="polaris" + fi + elif [[ $(hostname) == nid* ]]; then + machine="perlmutter" + else + echo "Unknown MACHINE. Setting MACHINE to $(hostname) and continuing..." + fi + export MACHINE="${machine}" + printf "Running on: %s\n" "$(printBlue ${MACHINE})" +} + + function check_and_kill_if_running() { # kill $(ps aux | grep -E "$USER.+(mpi|main.py)" | grep -v grep | awk '{print $2}') RUNNING_PIDS=$(lsof -i:29500 -Fp | head -n 1 | sed 's/^p//') @@ -139,6 +160,8 @@ function setParams() { else LLAMA_ARGS="${LLAMA_ARGS} --use-flash-attn-v2" fi + echo "Setting up AWS NCCL OFI Plugin on Polaris..." + source "${WORKING_DIR}/ALCF/aws_ofi_nccl_plugin.sh" || exit # +--------[Perlmutter]---------------------------------+ elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then TP="${TP:-2}" @@ -293,7 +316,7 @@ function setOutput() { export CKPT_DIR="checkpoints/${OUTPUT_PREFIX}" echo "${OUTPUT_LOG}" >> "logs/latest" mkdir -p "${OUTPUT_DIR}" - printf "Please see logs at: %s\n" $(printGreen "${OUTPUT_DIR}") + printf "\n Please see logs at: %s\n" $(printGreen "${OUTPUT_DIR}") printf "Checkpoints will be saved to: %s\n" $(printYellow "${CKPT_DIR}") } @@ -394,12 +417,13 @@ function setEnv() { echo "No conda_prefix or virtual_env found in environment..." echo "Setting up conda..." ######################## setup_conda ############################ - # ---- [SunSpot] ------- || ---- [Aurora] -------------- + # ---- [SunSpot @ ALCF] || [Aurora @ ALCF] --------------------- if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit # ----- [Aurora] -------------------------------------------- if [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then if [[ $(hostname) == x4* ]]; then + # TODO: Update once Aurora back online eval "$(conda shell.zsh hook)" && conda activate anl_release_q4v2 # ----- [SunSpot] --------------------------------------- elif [[ $(hostname) == x1* ]]; then @@ -407,7 +431,7 @@ function setEnv() { setup_conda_sunspot fi fi - # ----- [Polaris] ----------------------------------------------- + # ----- [Polaris @ ALCF] -------------------------------------------- elif [[ $(hostname) == x3* ]]; then if [[ "${PBS_O_HOST}" == sirius* ]]; then echo "Running on Sirius !!" @@ -417,8 +441,7 @@ function setEnv() { # ---- [load conda] ------------------------------------- setup_conda_polaris fi - echo "Setting up AWS NCCL OFI Plugin on Polaris..." - source "${WORKING_DIR}/ALCF/aws_ofi_nccl_plugin.sh" || exit + # ----- [Perlmutter @ NERSC] ---------------------------------------- elif [[ $(hostname) == login* || $(hostname) == nid* ]]; then echo "Running on Perlmutter !!" module load pytorch @@ -431,10 +454,9 @@ function setEnv() { echo "Unable to setup python environment. Exiting" exit 1 fi - printf "\n" + ##################################################################### pystr="Using: $(which python3)" - printf "[python] %s" "$(printMagenta ${pystr})" - printf "\n" + printf "\n[python] %s\n" "$(printMagenta ${pystr})" } @@ -457,13 +479,13 @@ function makeHostfiles() { # Ensure `DATA_FILE_LIST` is set, # fallback to default values if necessary. ############################################### -function setData() { # ----------------------[dfl: abbrv. for DATA_FILE_LIST] +function setData() { # ------------------------[dfl: abbrv. for DATA_FILE_LIST] # dfldir="${WORKING_DIR}/ALCF/data-lists" # =====[Set DATA_FILE_LIST_FALLBACK based on current machine]============== - if [[ $(hostname) == x4* ]]; then # ---------------------------[AURORA] + if [[ $(hostname) == x4* ]]; then # -----------------------------[AURORA] dfl_fallback="/home/foremans/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed/data_file_list_reweighted.txt" - elif [[ $(hostname) == x1* ]]; then # --------------------------[SUNSPOT] + elif [[ $(hostname) == x1* ]]; then # ----------------------------[SUNSPOT] # shellcheck: source ./data-lists/sunspot/books.txt dfl_fallback="${WORKING_DIR}/ALCF/data-lists/sunspot/books.txt" diff --git a/train_aGPT_7B.sh b/train_aGPT_7B.sh index 0c192b1b4f..6bc8f1f9dc 100644 --- a/train_aGPT_7B.sh +++ b/train_aGPT_7B.sh @@ -11,24 +11,31 @@ fi NOW="$(date "+%Y-%m-%d-%H%M%S")" cd "${PBS_O_WORKDIR}" || exit -nhosts=$(wc -l < "${HOSTFILE}") +export nhosts=$(wc -l < "${PBS_NODEFILE}") -if [[ "${nhosts}" == 1 || "${nhosts}" == 2 ]]; then - MBS=1 +if [[ "${nhosts}" == 1 ]]; then + export MBS=1 +elif [[ "${nhosts}" == 2 ]]; then + export MBS=1 elif [[ "${nhosts}" -ge 2 ]]; then - MBS=2 + export MBS=2 elif [[ "${nhosts}" -ge 8 ]]; then - MBS=4 + export MBS=4 fi -printf "Detected %s hosts. Running with micro_batch:\n" ${nhosts} ${MBS} +# printf "Detected %s hosts. Running with micro_batch:\n" ${nhosts} ${MBS} OUTDIR="${PBS_O_WORKDIR}/pbslogs" mkdir -p "${OUTDIR}" OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" -echo "Running on: ${MACHINE}" -echo "${OUTFILE}" >> "${OUTDIR}/latest" -echo "Logging job output to: ${OUTFILE}" + +echo "+---------------------------------------------------------+" +echo "| Running on: ${MACHINE}" +echo "| Detected ${nhosts} hosts. Running with micro batch: ${MBS}" +echo "| Logging job output to: ${OUTFILE}" +echo "+---------------------------------------------------------+" + export TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC=6000 +echo "${OUTFILE}" >> "${OUTDIR}/latest" # export DEBUG=1 MICRO_BATCH="${MBS}" DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/${MACHINE}/dolma_v1_7_file_list.txt" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 3e0f9390cb..237bcf7c15 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -34,16 +34,17 @@ export EXEC="${HERE}/pretrain_gpt_alcf.py" sourceFile "${HERE}/ALCF/helpers.sh" || exit # ----[3. Call fns from `./ALCF/helpers_alcf.sh`]------------------------------ -setEnv || exit # 1. load `conda` environment -# saveDSenv || exit # 2. save env vars to `.deepspeed_env` -ezpz || exit # 3. determine WORLD_SIZE, etc. from `PBS_*` vars -setParams || exit # 5. set command line arguments to pass to `"${EXEC}"` -buildDSconfig || exit # 6. create `deepspeed_config.json` from runtime params from ^ -setOutput || exit # 7. specify output directory for {logs, checkpoints, etc.} -setArgs || exit # 8. specify additional `deepspeed` arguments -setData "${DATA_FILE_LIST-}" || exit # 9. specify `DATA_FILE_LIST` for dolma dataset -printJobInfo || exit # 11. print job info -setupLauncher || exit +get_machine || exit # 01. Identify machine we're on +setEnv || exit # 02. Load `conda` environment +# saveDSenv || exit # 03. Save env vars to `.deepspeed_env` +ezpz || exit # 04. Determine WORLD_SIZE, etc. from `PBS_*` vars +setParams || exit # 05. Set command line arguments to pass to `"${EXEC}"` +buildDSconfig || exit # 06. Create `deepspeed_config.json` from runtime params from ^ +setOutput || exit # 07. Specify output directory for {logs, checkpoints, etc.} +setArgs || exit # 08. Specify additional `deepspeed` arguments +setData "${DATA_FILE_LIST-}" || exit # 09. Specify `DATA_FILE_LIST` for dolma dataset +printJobInfo || exit # 11. Print job info +setupLauncher || exit # 12. set launcher to one of `MPICH` (default), or `deepspeed` # ----------------------------------------------------------------------------- #### [DEPRECATED] ########################################################### From 6b4ea4c7085c0588214dca07b28a9fa76b0f6657 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 16 May 2024 10:49:20 -0500 Subject: [PATCH 245/268] Update `ALCF/{helpers.sh,train_llama_alcf.sh}` --- ALCF/helpers.sh | 52 +++++++++++++++++++++++++++++++++++---------- train_llama_alcf.sh | 13 ++++++------ 2 files changed, 48 insertions(+), 17 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 1bd0febf24..2422ecbe7a 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -125,6 +125,18 @@ function setDSlauncher() { fi } +function set_lr_args() { + LR_ARGS="--lr ${LR} --lr-decay-style cosine" + if [[ -n "${LR_DECAY_ITERS:-}" ]]; then + LR_ARGS="${LR_ARGS} --lr-decay-iters ${LR_DECAY_ITERS}" + fi + if [[ -n "${LR_WARMUP_FRAC}" ]]; then + LR_ARGS="${LR_ARGS} --lr-warmup-fraction ${LR_WARMUP_FRAC}" + fi + echo "LR_ARGS: ${LR_ARGS}" + export LR_ARGS="${LR_ARGS}" +} + function setParams() { LLAMA_ARGS="" # +----[Parallelism Settings] -------------------------------------------+ @@ -194,9 +206,6 @@ function setParams() { export NUM_KV_HEAD=${NUM_KV_HEAD:-8} # GROUP ATTENTION export FFN_HIDDEN_SIZE=${FFN_HIDDEN_SIZE:-11008} # FFN HIDDEN SIZE # +---[Run Settings]------------------------------------------------------+ - export LR=${LR:-0.0003} # LEARNING_RATE - export LR_WARMUP_FRAC=${LR_WARMUP_FRAC:-0.05} # LEARNING RATE WARMUP - export LR_DECAY_ITERS=${LR_DECAY_ITERS:-320000} # LR DECAY ITERS export SEQ=${SEQ:-4096} # SEQ_LEN: 4096 export ZERO_STAGE=${ZERO_STAGE:-1} # ZERO OFFLOADING STAGE export MICRO_BATCH=${MICRO_BATCH:-8} # MICRO BATCH SIZE @@ -215,6 +224,11 @@ function setParams() { export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" # STRING FOR IDENTIFYING MODEL # +----[ADDITIONAL LLAMA SPECIFIC ARGUMENTS]------------------------------ export LLAMA_ARGS="${LLAMA_ARGS} --no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" + export LR=${LR:-0.0003} # LEARNING_RATE + export LR_WARMUP_FRAC=${LR_WARMUP_FRAC:-0.05} # LEARNING RATE WARMUP + # export LR_DECAY_ITERS=${LR_DECAY_ITERS:-320000} # LR DECAY ITERS + export LR_DECAY_ITERS=${LR_DECAY_ITERS:-} # LR DECAY ITERS + set_lr_args } @@ -305,10 +319,15 @@ function saveDSenv() { function setOutput() { # ---- Specify output location -------------------------------- - export OUTPUT_PREFIX="ws${WORLD_SIZE}_ds_stage${ZERO_STAGE}_nl${NLAYERS}_hs${HIDDEN}_mb${MICRO_BATCH}_seq${SEQ}_gb${GLOBAL_BATCH}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" + OUTPUT_PREFIX="ws${WORLD_SIZE}_ds_stage${ZERO_STAGE}_nl${NLAYERS}" + OUTPUT_PREFIX="${OUTPUT_PREFIX}_hs${HIDDEN}_mb${MICRO_BATCH}" + OUTPUT_PREFIX="${OUTPUT_PREFIX}_seq${SEQ}_gb${GLOBAL_BATCH}" + OUTPUT_PREFIX="${OUTPUT_PREFIX}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" + OUTPUT_PREFIX="${OUTPUT_PREFIX}_lr${LR}_lwf${LR_WARMUP_FRAC}_ldi${LR_DECAY_ITERS}" if [[ -z "${NO_FLASH_ATTN:-}" ]]; then - export OUTPUT_PREFIX="${OUTPUT_PREFIX}_flash" + OUTPUT_PREFIX="${OUTPUT_PREFIX}_flash" fi + export OUTPUT_PREFIX="${OUTPUT_PREFIX}" # OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%Y%m%d-%H%M%S)_${WORLD_SIZE}_${HOSTNAME}" export OUTPUT_DIR="${OUTPUT_DIR}" @@ -351,11 +370,20 @@ function sumFiles() { ######################################################## # Setup / activate conda environment, ######################################################## -setup_conda_sunspot() { # mine is called `q4-drop` on Sunspot - if [[ -z "${CONDA_PREFIX-}" && -z "${VIRTUAL_ENV-}" ]]; then - shell_name=$(echo "${SHELL}" | tr "\/" "\t" | awk '{print $NF}') - eval "$(~/miniconda3/bin/conda shell.${shell_name} hook)" - conda activate q4-drop +setup_conda_sunspot() { + ###### check if CONDA_PREFIX non-empty ################ + if [[ -z "${CONDA_PREFIX-}" ]]; then + module use -a /home/jmitche1/anl_release/2024/q2 ; module load frameworks_2024_5_v2 + else + echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" + fi + ###### check if VIRTUAL_ENV non-empty ################# + if [[ -z "${VIRTUAL_ENV:-}" ]]; then + DEFAULT_VENV_PATH=${WORKING_DIR}/venvs/frameworks_2024_5_v2 + if [[ -d "${DEFAULT_VENV_PATH}" ]]; then + echo "Caught virtual env at ${DEFAULT_VENV_PATH}!" + source "${WORKING_DIR}/${DEFAULT_VENV_PATH}/bin/activate" + fi else echo "Found existing python at: $(which python3)" fi @@ -456,7 +484,9 @@ function setEnv() { fi ##################################################################### pystr="Using: $(which python3)" - printf "\n[python] %s\n" "$(printMagenta ${pystr})" + printf "[python] %s" "$(printMagenta ${pystr})" + printf "\n" + export "PYTHON_EXEC=$(which python3)" } diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 237bcf7c15..d877c19a06 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -75,6 +75,7 @@ mkdir -p "${TBDIR}" data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" mkdir -p "${data_cache_path}" module list +printenv > "${CKPT_DIR}/.env" if [[ "${TIMING_LOG_LEVEL}" -ge 1 ]]; then TIMING_STR="\ @@ -87,6 +88,8 @@ else fi + + # Take custom args custom_args=" $@" @@ -98,7 +101,6 @@ run_cmd=" --split 100,0,0 \ --log-interval 1 \ --no-bias-gelu-fusion \ - --lr-decay-style cosine \ --no-bias-dropout-fusion \ --no-masked-softmax-fusion \ --tokenizer-type Llama2Tokenizer \ @@ -107,7 +109,6 @@ run_cmd=" --use-checkpoint-opt_param-scheduler \ --log-timers-to-tensorboard \ --log-optimizer-states-to-tensorboard \ - --lr ${LR} \ --optimizer ${OPT} \ --save ${CKPT_DIR} \ --load ${CKPT_DIR} \ @@ -125,14 +126,13 @@ run_cmd=" --micro-batch-size ${MICRO_BATCH} \ --data-file-list ${DATA_FILE_LIST} \ --tensor-model-parallel-size ${TP} \ - --lr-decay-iters ${LR_DECAY_ITERS} \ --global-batch-size ${GLOBAL_BATCH} \ --pipeline-model-parallel-size ${PP} \ --num-key-value-heads ${NUM_KV_HEAD} \ --data-cache-path ${data_cache_path} \ --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ --tokenizer-model ${TOKENIZER_MODEL} \ - --lr-warmup-fraction ${LR_WARMUP_FRAC} \ + ${LR_ARGS} \ ${LLAMA_ARGS} \ ${TIMING_STR} \ $ds_args \ @@ -143,7 +143,8 @@ run_cmd=" check_and_kill_if_running || exit echo "${run_cmd}" -printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" -printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" +printf "[!! %s] View output at:\n %s\n" "$(printBlue "NOTE")" "$(printYellow ${OUTPUT_LOG})" +# printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" +# printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" eval "${run_cmd}" set +x From 14970b9a01a1055c143b1969dff89d6aed99bfb1 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 16 May 2024 11:54:21 -0500 Subject: [PATCH 246/268] Update `ALCF/helpers.sh` on Sunspot --- ALCF/helpers.sh | 34 +++++++++++++++++++++++----------- 1 file changed, 23 insertions(+), 11 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 2422ecbe7a..9fe9934dab 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -372,18 +372,30 @@ function sumFiles() { ######################################################## setup_conda_sunspot() { ###### check if CONDA_PREFIX non-empty ################ - if [[ -z "${CONDA_PREFIX-}" ]]; then - module use -a /home/jmitche1/anl_release/2024/q2 ; module load frameworks_2024_5_v2 - else - echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" + if [[ -z "${CONDA_PREFIX:-}" ]]; then + eval "$(~/miniconda3/bin/conda shell.zsh hook)" + conda activate anl_24_q2_release fi - ###### check if VIRTUAL_ENV non-empty ################# + # ------------------------------------------------------------------------ + # XXX: Jerome's `frameworks_2024_5_v2` seems broken ?? + # - seems to be missing `python3 -c 'from mpi4py import MPI'` ??? + # - consequently, we leave the setup below commented out (for the time + # being): + # if [[ -z "${CONDA_PREFIX-}" ]]; then + # module use -a /home/jmitche1/anl_release/2024/q2 ; module load frameworks_2024_5_v2 + # else + # echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" + # fi + # + # ------------------------------------------------------------------------ + ###### check if VIRTUAL_ENV non-empty #################################### if [[ -z "${VIRTUAL_ENV:-}" ]]; then - DEFAULT_VENV_PATH=${WORKING_DIR}/venvs/frameworks_2024_5_v2 - if [[ -d "${DEFAULT_VENV_PATH}" ]]; then - echo "Caught virtual env at ${DEFAULT_VENV_PATH}!" - source "${WORKING_DIR}/${DEFAULT_VENV_PATH}/bin/activate" - fi + DEFAULT_VENV_PATH="${WORKING_DIR}/venvs/anl_24_q2_release" + # venvs/anl_24_q2_release/bin/activate + # if [[ -d "${DEFAULT_VENV_PATH}" ]]; then + echo "Caught virtual env at ${DEFAULT_VENV_PATH}!" + source "${DEFAULT_VENV_PATH}/bin/activate" || exit + # fi else echo "Found existing python at: $(which python3)" fi @@ -447,7 +459,6 @@ function setEnv() { ######################## setup_conda ############################ # ---- [SunSpot @ ALCF] || [Aurora @ ALCF] --------------------- if [[ $(hostname) == x1* || $(hostname) == x4* ]]; then - source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit # ----- [Aurora] -------------------------------------------- if [[ -z "${conda_prefix}" && -z "${virtual_env}" ]]; then if [[ $(hostname) == x4* ]]; then @@ -459,6 +470,7 @@ function setEnv() { setup_conda_sunspot fi fi + source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit # ----- [Polaris @ ALCF] -------------------------------------------- elif [[ $(hostname) == x3* ]]; then if [[ "${PBS_O_HOST}" == sirius* ]]; then From d1aec5d7afe4ca68196e325f32bd185584caaf9a Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 16 May 2024 11:54:55 -0500 Subject: [PATCH 247/268] Update `ALCF/sunspot-env.sh` with new modules for `anl_24_q2_release` --- ALCF/sunspot-env.sh | 31 ++++++------------------------- 1 file changed, 6 insertions(+), 25 deletions(-) diff --git a/ALCF/sunspot-env.sh b/ALCF/sunspot-env.sh index e97545aafe..8b02542b20 100644 --- a/ALCF/sunspot-env.sh +++ b/ALCF/sunspot-env.sh @@ -1,27 +1,8 @@ #!/bin/bash --login - -export CCL_OP_SYNC=1 # Required by current oneCCL (HPCS-8067) -export CCL_PROCESS_LAUNCHER=pmix # Required by Aurora mpich -export FI_PROVIDER=cxi # Required by Aurora mpich -export PALS_PMI=pmix # Required by Aurora mpich -export CCL_ATL_TRANSPORT=mpi # Required by Aurora mpich -export FI_MR_CACHE_MONITOR=disabled # Required by Aurora mpich (HPCS-6501) -export CCL_SKIP_SCHEDULER=1 # Required by current oneCCL, will remove when set by default -export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1 -export CCL_TOPO_COLOR="card:{0,1},{2,3},{4,5},{6,7},{8,9},{10,11};plane:{0,3,4,6,8,11},{1,2,5,7,9,10}" -export UR_L0_IN_ORDER_BARRIER_BY_SIGNAL=0 # Required by current oneCCL - - -export LLM_DK_DIR=/home/$(whoami)/q4-drop_sunspot/llm.devkit - -module load oneapi/release/2023.12.15.001 -unset MPIR_CVAR_CH4_COLL_SELECTION_TUNING_JSON_FILE -unset MPIR_CVAR_COLL_SELECTION_TUNING_JSON_FILE -unset MPIR_CVAR_CH4_POSIX_COLL_SELECTION_TUNING_JSON_FILE - - +# module use /home/ftartagl/graphics-compute-runtime/modulefiles -module load graphics-compute-runtime/agama-ci-devel-736.9 -source /home/$(whoami)/q4-drop_sunspot/llm.devkit/torch-ccl/third_party/oneCCL/build/_install/env/vars.sh -module load gcc/12.1.0 -module unload intel_compute_runtime/release/agama-devel-647 +module load graphics-compute-runtime/agama-ci-devel-803.29 +module load spack-pe-gcc/0.6.1-23.275.2 +module load gcc/12.2.0 +module use /soft/preview-modulefiles/24.086.0 +module load oneapi/release/2024.04.15.001 From 13700cfc05ef71f6052cf876f8431d5d2eba58bc Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 17 May 2024 07:19:09 -0500 Subject: [PATCH 248/268] Update `ALCF/helpers.sh` with new release on Sunspot --- ALCF/helpers.sh | 88 +++++++++++++++++++++++++++++++++++++++---------- 1 file changed, 70 insertions(+), 18 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 9fe9934dab..a805a34e28 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -229,6 +229,15 @@ function setParams() { # export LR_DECAY_ITERS=${LR_DECAY_ITERS:-320000} # LR DECAY ITERS export LR_DECAY_ITERS=${LR_DECAY_ITERS:-} # LR DECAY ITERS set_lr_args + if [[ "${TIMING_LOG_LEVEL}" -ge 1 ]]; then + TIMING_STR="\ + --timing-log-level ${TIMING_LOG_LEVEL} \ + --log-timers-to-tensorboard \ + --log-optimizer-states-to-tensorboard \ + " + else + TIMING_STR="" + fi } @@ -323,7 +332,10 @@ function setOutput() { OUTPUT_PREFIX="${OUTPUT_PREFIX}_hs${HIDDEN}_mb${MICRO_BATCH}" OUTPUT_PREFIX="${OUTPUT_PREFIX}_seq${SEQ}_gb${GLOBAL_BATCH}" OUTPUT_PREFIX="${OUTPUT_PREFIX}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" - OUTPUT_PREFIX="${OUTPUT_PREFIX}_lr${LR}_lwf${LR_WARMUP_FRAC}_ldi${LR_DECAY_ITERS}" + OUTPUT_PREFIX="${OUTPUT_PREFIX}_lr${LR}_lwf${LR_WARMUP_FRAC}" + if [[ -n "${LR_DECAY_ITERS}" ]]; then + OUTPUT_PREFIX="${OUTPUT_PREFIX}_ldi${LR_DECAY_ITERS}" + fi if [[ -z "${NO_FLASH_ATTN:-}" ]]; then OUTPUT_PREFIX="${OUTPUT_PREFIX}_flash" fi @@ -373,29 +385,39 @@ function sumFiles() { setup_conda_sunspot() { ###### check if CONDA_PREFIX non-empty ################ if [[ -z "${CONDA_PREFIX:-}" ]]; then - eval "$(~/miniconda3/bin/conda shell.zsh hook)" - conda activate anl_24_q2_release + # eval "$(~/miniconda3/bin/conda shell.zsh hook)" + # conda activate anl_24_q2_release + module use /soft/preview-modulefiles/24.086.0 ; module load frameworks/2024.04.15.002.lua fi - # ------------------------------------------------------------------------ - # XXX: Jerome's `frameworks_2024_5_v2` seems broken ?? + # XXX: ------------------------------------------------------------------- + # Jerome's `frameworks_2024_5_v2` seems broken ?? # - seems to be missing `python3 -c 'from mpi4py import MPI'` ??? # - consequently, we leave the setup below commented out (for the time # being): - # if [[ -z "${CONDA_PREFIX-}" ]]; then - # module use -a /home/jmitche1/anl_release/2024/q2 ; module load frameworks_2024_5_v2 - # else - # echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" - # fi - # + # if [[ -z "${CONDA_PREFIX-}" ]]; then + # module use -a /home/jmitche1/anl_release/2024/q2 ; module load frameworks_2024_5_v2 + # else + # echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" + # fi # ------------------------------------------------------------------------ + ###### check if VIRTUAL_ENV non-empty #################################### + # venvs/anl_24_q2_release/bin/activate + # if [[ -d "${DEFAULT_VENV_PATH}" ]]; then if [[ -z "${VIRTUAL_ENV:-}" ]]; then - DEFAULT_VENV_PATH="${WORKING_DIR}/venvs/anl_24_q2_release" - # venvs/anl_24_q2_release/bin/activate - # if [[ -d "${DEFAULT_VENV_PATH}" ]]; then - echo "Caught virtual env at ${DEFAULT_VENV_PATH}!" - source "${DEFAULT_VENV_PATH}/bin/activate" || exit - # fi + if [[ -n "${CONDA_PREFIX}" ]]; then + VENV_DIR="${WORKING_DIR}/venvs/$(echo ${CONDA_PREFIX} | tr '\/' '\t' | awk '{print $NF}')" + else + VENV_DIR="${WORKING_DIR}/venvs/anl_24_q2_release" + fi + echo "Caught virtual env at ${VENV_DIR}!" + # source "${VENV_DIR}/bin/activate" || + if [[ ! -f "${VENV_DIR}/bin/activate" ]]; then + printf "[!! %s]: Unable to locate %s\n" "$(printRed "ERROR")" "$(printMagenta "${VENV_DIR}/bin/activate")" + # echo "[!ERROR]: Unable to locate ${VENV_DIR}/bin/activate !!" + else + source "${VENV_DIR}/bin/activate" + fi else echo "Found existing python at: $(which python3)" fi @@ -415,6 +437,10 @@ setup_conda_sirius() { fi } +setup_venv_from_conda() { + source "venvs/$(echo ${CONDA_PREFIX} | tr '\/' '\t' | awk '{print $NF}')/bin/activate" +} + ######################## # Setup conda on Polaris ######################## @@ -470,7 +496,12 @@ function setEnv() { setup_conda_sunspot fi fi - source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit + # MPICH_MODULES=$(echo $LOADEDMODULES | tr ':' '\n' | grep mpich) + # if [[ -z "${MPICH_MODULES" ]]; then + # source "${WORKING_DIR}/ALCF/sunspot-env.sh" || exit + # else + # echo "Caught MPICH_MODULES: ${MPICH_MODULES}" + # fi # ----- [Polaris @ ALCF] -------------------------------------------- elif [[ $(hostname) == x3* ]]; then if [[ "${PBS_O_HOST}" == sirius* ]]; then @@ -764,3 +795,24 @@ function printCyan() { function printWhite() { printf "\e[1;37m%s\e[0m\n" "$@" } + +#### [DEPRECATED] ########################################################### +# if [[ -z "${HOSTFILE}" ]]; then +# makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` +# else +# echo "!! USING CUSTOM HOSTFILE FROM: ${HOSTFILE}" +# fi +# ---------------------------------------------------------------------------- +# setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` +# ---------------------------------------------------------------------------- +# TORCH_DEVICE=$(python3 -c 'import ezpz as ez; print(ez.get_torch_device())') +# printf %s "Using TORCH_DEVICE=${TORCH_DEVICE}" +# if [[ "${TORCH_DEVICE}" == "cuda" ]]; then +# printf %s "Setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True" +# PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True +# fi +# ---------------------------------------------------------------------------- +# export MPICH_GPU_SUPPORT_ENABLED=1 +# export CUDA_DEVICE_MAX_CONNECTIONS=1 +# export NCCL_DEBUG=INFO +############################################################################# From 530c7c80cee7ff10a01b432fed01e5e642fc0cd2 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 17 May 2024 07:19:30 -0500 Subject: [PATCH 249/268] Update `train_llama_alcf.sh` --- train_llama_alcf.sh | 65 +++++++++++++++++---------------------------- 1 file changed, 24 insertions(+), 41 deletions(-) diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index d877c19a06..b1d4ed9825 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -5,12 +5,25 @@ #PBS -l select=48 #PBS -l filesystems=eagle:home -if [[ -n "${DEBUG-}" ]]; then +#### Make it easy to track experiments by date ################### +YEAR="$(date "+%Y")" +MONTH="$(date "+%m")" +DAY="$(date "+%Y-%m-%d")" +TODAY="$(date "+%Y-%m-%d")" # kept for backwards compatibility +STARTED_AT="$(date "+%Y-%m-%d-%H%M%S")" +################################################################## + +if [[ -n "${DEBUG-}" ]]; then # to use: `DEBUG=1 bash train_llama_alcf.sh` printf "\e[1;31m%s\e[0m\n" "!! RUNNING IN DEBUG MODE !!" set -euxo pipefail fi -function sourceFile() { +if [[ -v NOOP ]]; then # to use: `NOOP=1 bash train_llama_alcf.sh` + echo "Run NOOP mode" + set -o noexec # same as set -n +fi + +sourceFile() { fp="$1" echo "source-ing ${fp}" if [[ -f "${fp}" ]]; then @@ -21,7 +34,7 @@ function sourceFile() { fi } -# ----[0. Navigate into `$PBS_O_WORKDIR`]------------------------------------- +# ----[0. Navigate into `$PBS_O_WORKDIR`]-------------------------------------- cd "${PBS_O_WORKDIR}" || exit HERE=$(python3 -c 'import os; print(os.getcwd())') export HERE @@ -47,48 +60,18 @@ printJobInfo || exit # 11. Print job info setupLauncher || exit # 12. set launcher to one of `MPICH` (default), or `deepspeed` # ----------------------------------------------------------------------------- -#### [DEPRECATED] ########################################################### -# if [[ -z "${HOSTFILE}" ]]; then -# makeHostfiles || exit # 4. create `deepspeed` hostfile from `$PBS_NODEFILE` -# else -# echo "!! USING CUSTOM HOSTFILE FROM: ${HOSTFILE}" -# fi -# ---------------------------------------------------------------------------- -# setDSlauncher "${HERE}" || exit # 10. set `launcher` args for `deepspeed ${launcher} ${EXEC} ${args}` -# ---------------------------------------------------------------------------- -# TORCH_DEVICE=$(python3 -c 'import ezpz as ez; print(ez.get_torch_device())') -# printf %s "Using TORCH_DEVICE=${TORCH_DEVICE}" -# if [[ "${TORCH_DEVICE}" == "cuda" ]]; then -# printf %s "Setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True" -# PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True -# fi -# ---------------------------------------------------------------------------- -# export MPICH_GPU_SUPPORT_ENABLED=1 -# export CUDA_DEVICE_MAX_CONNECTIONS=1 -# export NCCL_DEBUG=INFO -############################################################################# - -# Assert TBDIR exists inside our $CKPT_DIR +################################################ +# Assert `$TBDIR` exists inside our `$CKPT_DIR` +# to ensure metrics are tied to checkpoint +################################################ TBDIR="${CKPT_DIR}/tensorboard" mkdir -p "${TBDIR}" -data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" -mkdir -p "${data_cache_path}" -module list -printenv > "${CKPT_DIR}/.env" - -if [[ "${TIMING_LOG_LEVEL}" -ge 1 ]]; then - TIMING_STR="\ - --timing-log-level ${TIMING_LOG_LEVEL} \ - --log-timers-to-tensorboard \ - --log-optimizer-states-to-tensorboard \ - " -else - TIMING_STR="" -fi - - +data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" && mkdir -p "${data_cache_path}" +# Print info about loaded modules and runtime environment +module list +printenv |& tee "${CKPT_DIR}/.env" # Take custom args custom_args=" $@" From b8cb2e8bfd3459d2f08a6c55b9b07f9f20447ac6 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 17 May 2024 07:51:15 -0500 Subject: [PATCH 250/268] Update `train_aGPT_7B.sh` --- train_aGPT_7B.sh | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/train_aGPT_7B.sh b/train_aGPT_7B.sh index 6bc8f1f9dc..d2719b088e 100644 --- a/train_aGPT_7B.sh +++ b/train_aGPT_7B.sh @@ -38,4 +38,6 @@ echo "+---------------------------------------------------------+" export TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC=6000 echo "${OUTFILE}" >> "${OUTDIR}/latest" # export DEBUG=1 -MICRO_BATCH="${MBS}" DATA_FILE_LIST="${PBS_O_WORKDIR}/ALCF/data-lists/${MACHINE}/dolma_v1_7_file_list.txt" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" +MICRO_BATCH="${MICRO_BATCH:-${MBS}}" +DATA_FILE_LIST="${DATA_FILE_LIST:-${PBS_O_WORKDIR}/ALCF/data-lists/${MACHINE}/dolma_v1_7_file_list.txt}" +bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" From 0f180319cc9e48b4c52b32400a26297a91937c40 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 20 May 2024 09:43:45 -0500 Subject: [PATCH 251/268] Add `setup_venv_from_conda` fn to `ALCF/helpers.sh` --- ALCF/helpers.sh | 33 ++++++++++++++++++++++++++++++++- 1 file changed, 32 insertions(+), 1 deletion(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index a805a34e28..9e7e2b582b 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -438,7 +438,38 @@ setup_conda_sirius() { } setup_venv_from_conda() { - source "venvs/$(echo ${CONDA_PREFIX} | tr '\/' '\t' | awk '{print $NF}')/bin/activate" + if [[ -z "${CONDA_PREFIX}" ]]; then + echo "No ${CONDA_PREFIX} found." # Exiting." + # exit 1 + else + if [[ -n "${VIRTUAL_ENV}" ]]; then + echo "Already inside virtual env at ${VENV_DIR}!" + elif [[ -z "${VIRTUAL_ENV}" ]]; then + echo "No VIRTUAL_ENV found in environment!" + echo " - Trying to setup from ${CONDA_PREFIX}" + CONDA_NAME=$(echo ${CONDA_PREFIX} | tr '\/' '\t' | sed -E 's/mconda3|\/base//g' | awk '{print $NF}') + VENV_DIR="${WORKING_DIR}/venvs/${CONDA_NAME}" + echo " - Using VENV_DIR=${VENV_DIR}" + # VENV_DIR="venvs/$(echo ${CONDA_PREFIX} | tr '\/' '\t' | sed -E 's/mconda3|\/base//g' | awk '{print $NF}')" + # VENV_DIR="${WORKING_DIR}/venvs/$(echo ${CONDA_PREFIX} | tr '\/' '\t' | awk '{print $NF}')" + # VENV_DIR="${WORKING_DIR}/venvs/anl_24_q2_release" + # if [[ -f "${VENV_DIR}/bin/activate" ]]; then + if [[ ! -f "${VENV_DIR}/bin/activate" ]]; then + printf "\n - Creating a new virtual env on top of %s in %s" "$(printBlue "${CONDA_NAME}")" "$(printGreen "${VENV_DIR}")" + mkdir -p "${VENV_DIR}" + python3 -m venv "${VENV_DIR}" --system-site-packages + source "${VENV_DIR}/bin/activate" || exit + elif [[ -f "${VENV_DIR}/bin/activate" ]]; then + echo " - Found existing venv, activating from $(printBlue "${VENV_DIR}")" + source "${VENV_DIR}/bin/activate" + else + printf "\n [!! %s]: Unable to locate %s\n" "$(printRed "ERROR")" "$(printMagenta "${VENV_DIR}/bin/activate")" + fi + fi + # else + # printf "[!! %s]: Unable to locate %s\n" "$(printRed "ERROR")" "$(printMagenta "${VENV_DIR}/bin/activate")" + fi + } ######################## From 061e2cc9e0f4a6c98e857b850f0113dc310f1b09 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 20 May 2024 09:44:17 -0500 Subject: [PATCH 252/268] Update `train_aGPT_7B.sh` --- train_aGPT_7B.sh | 40 ++++++++++++++++++++++------------------ 1 file changed, 22 insertions(+), 18 deletions(-) diff --git a/train_aGPT_7B.sh b/train_aGPT_7B.sh index d2719b088e..0907f8163c 100644 --- a/train_aGPT_7B.sh +++ b/train_aGPT_7B.sh @@ -1,30 +1,34 @@ #!/bin/bash --login # + +NOW="$(date "+%Y-%m-%d-%H%M%S")" +cd "${PBS_O_WORKDIR}" || exit + HOSTNAME=$(hostname) if [[ "${HOSTNAME}" == x3* ]]; then MACHINE="polaris" + # XXX: ¯\_(ツ)_/¯ + # - On Polaris, we see that: + # - on 1 or 2 nodes, only MICRO_BATCH=1 will fit in memory + # - on 8 nodes, MICRO_BATCH=2 will fit in memory + # - on 48 nodes, MICRO_BATCH=4 will fit in memory + # + export nhosts=$(wc -l < "${PBS_NODEFILE}") + if [[ "${nhosts}" == 1 ]]; then + export MBS=1 + elif [[ "${nhosts}" == 2 ]]; then + export MBS=1 + elif [[ "${nhosts}" -ge 3 ]]; then + export MBS=2 + elif [[ "${nhosts}" -ge 8 ]]; then + export MBS=4 + fi elif [[ "${HOSTNAME}" == x1* ]]; then MACHINE="sunspot" elif [[ "${HOSTNAME}" == x4* ]]; then MACHINE="aurora" fi -NOW="$(date "+%Y-%m-%d-%H%M%S")" -cd "${PBS_O_WORKDIR}" || exit -export nhosts=$(wc -l < "${PBS_NODEFILE}") - -if [[ "${nhosts}" == 1 ]]; then - export MBS=1 -elif [[ "${nhosts}" == 2 ]]; then - export MBS=1 -elif [[ "${nhosts}" -ge 2 ]]; then - export MBS=2 -elif [[ "${nhosts}" -ge 8 ]]; then - export MBS=4 -fi - -# printf "Detected %s hosts. Running with micro_batch:\n" ${nhosts} ${MBS} - OUTDIR="${PBS_O_WORKDIR}/pbslogs" mkdir -p "${OUTDIR}" OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" @@ -38,6 +42,6 @@ echo "+---------------------------------------------------------+" export TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC=6000 echo "${OUTFILE}" >> "${OUTDIR}/latest" # export DEBUG=1 -MICRO_BATCH="${MICRO_BATCH:-${MBS}}" -DATA_FILE_LIST="${DATA_FILE_LIST:-${PBS_O_WORKDIR}/ALCF/data-lists/${MACHINE}/dolma_v1_7_file_list.txt}" +export MICRO_BATCH="${MICRO_BATCH:-${MBS}}" +export DATA_FILE_LIST="${DATA_FILE_LIST:-${PBS_O_WORKDIR}/ALCF/data-lists/${MACHINE}/dolma_v1_7_file_list.txt}" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" From 47bf9b50088069f960a9ee52d4d535530427d8ae Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 20 May 2024 09:44:34 -0500 Subject: [PATCH 253/268] Update `train_llama_alcf.sh` --- train_llama_alcf.sh | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index b1d4ed9825..fee2e392dc 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -71,7 +71,9 @@ data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" && mkdir -p "${data_cache_path} # Print info about loaded modules and runtime environment module list -printenv |& tee "${CKPT_DIR}/.env" +dotenv_file="${CKPT_DIR}/.env" +echo "Saving environment to ${dotenv_file}" +printenv | grep -v "LS_COLORS" > "${dotenv_file}" # Take custom args custom_args=" $@" From e68d270faf4780018ae954f38e83b002adadb55f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 20 May 2024 09:47:57 -0500 Subject: [PATCH 254/268] Update `ALCF/README.md` --- ALCF/README.md | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index d405986fdf..8c097c699a 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -1,4 +1,4 @@ -# Megatron-DeepSpeed @ ALCF +- [>] # Megatron-DeepSpeed @ ALCF ## ✅ TODOs @@ -82,13 +82,16 @@ To launch: +### Polaris + ```bash $ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I $ cd /path/to/Megatron-DeepSpeed/ -# load your favorite {conda, venv} environment, requires: {pytorch, deepspeed} -# e.g. on Polaris: $ module load conda/2023-10-04 # ; conda activate cu118-pt221 ; unset PYTHONUSERBASE -$ export PBS_O_WORKDIR="$(pwd)" && DATA_FILE_LIST=./convergence_debug_small.txt DTYPE=bf16 OPT=adamw bash train_llama_alcf.sh +$ module use /soft/modulefiles +$ module load conda/2024-04-29 +$ conda activate base +$ export PBS_O_WORKDIR="$(pwd)" && DATA_FILE_LIST=./ALCF/data-lists/polaris/books.txt DTYPE=bf16 OPT=adamw bash train_llama_alcf.sh ```
[output]: From ac414a0479b69f4968405c682cd49700eb3faebb Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 20 May 2024 09:57:28 -0500 Subject: [PATCH 255/268] Update README.md --- ALCF/README.md | 60 ++++++++++++++++++++++++++++++++------------------ 1 file changed, 39 insertions(+), 21 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 8c097c699a..0b436792d9 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -1,4 +1,4 @@ -- [>] # Megatron-DeepSpeed @ ALCF +# Megatron-DeepSpeed @ ALCF ## ✅ TODOs @@ -80,19 +80,35 @@ > [`train_llama_alcf.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/train_llama_alcf.sh) is the main entry point for launching > distributed training on {Polaris, Aurora, Sunspot} @ ALCF. -To launch: - -### Polaris - -```bash -$ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I -$ cd /path/to/Megatron-DeepSpeed/ -$ module load conda/2023-10-04 # ; conda activate cu118-pt221 ; unset PYTHONUSERBASE -$ module use /soft/modulefiles -$ module load conda/2024-04-29 -$ conda activate base -$ export PBS_O_WORKDIR="$(pwd)" && DATA_FILE_LIST=./ALCF/data-lists/polaris/books.txt DTYPE=bf16 OPT=adamw bash train_llama_alcf.sh -``` +To launch on Polaris @ ALCF: + +> [!IMPORTANT] +> **Launch Instructions** on Polaris @ ALCF +> +> 1. Request an interactive job with `qsub -I`: +> +> ```bash +> $ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I +> ``` +> +> 2. Clone repo + navigate into it: +> ```sh +> $ cd /path/to/Megatron-DeepSpeed/ # or git clone https://github.com/argonne-lcf/Megatron-DeepSpeed +> ``` +> +> 3. Load required modules: +> +> ```sh +> $ module use /soft/modulefiles +> $ module load conda/2024-04-29 +> $ conda activate base +> ``` +> +> 4. Launch: +> +> ```sh +> $ export PBS_O_WORKDIR="$(pwd)" && DATA_FILE_LIST=./ALCF/data-lists/polaris/books.txt DTYPE=bf16 OPT=adamw bash train_llama_alcf.sh +> ```
[output]: @@ -461,6 +477,8 @@ training ...
+ + + + ## 📝 Data Preprocessing
Data Pre-Processing: From 9aa7fabfc70ead7470183c31e9ea5c7449d6da08 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Mon, 20 May 2024 13:26:09 -0500 Subject: [PATCH 256/268] Fix path in `prof.export_chrome_trace()` from `pretrain_gpt_alcf.py` --- pretrain_gpt_alcf.py | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/pretrain_gpt_alcf.py b/pretrain_gpt_alcf.py index 750bd21e48..94186fea83 100644 --- a/pretrain_gpt_alcf.py +++ b/pretrain_gpt_alcf.py @@ -2,6 +2,7 @@ """Pretrain GPT""" +from pathlib import Path from mpi4py import MPI import os from rich import print @@ -581,9 +582,13 @@ def main(): data_post_process=data_post_process ) args = get_args() - prof.export_chrome_trace( - f"{args.tensorboard_dir}" - "/torch-trace-{RANK}-of-{WORLD_SIZE}.json" + assert args is not None + trace_output = Path(f"{args.tensorboard_dir}").joinpath( + f"torch-trace-{RANK}-of-{WORLD_SIZE}.json" + ) + prof.export_chrome_trace(trace_output.as_posix()) + log.info( + f'Saved trace output to: {trace_output.as_posix()}' ) else: model = pretrain( From 2f0154394bbdf3c64b4669f9d944645e2cdb8f2b Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Thu, 23 May 2024 17:49:32 -0500 Subject: [PATCH 257/268] Update README.md --- ALCF/README.md | 251 +++++++++++++++++++++++++++++++------------------ 1 file changed, 162 insertions(+), 89 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 0b436792d9..82577ab372 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -1,114 +1,84 @@ # Megatron-DeepSpeed @ ALCF -## ✅ TODOs -
-TODOs: +## 🆘 Getting Started -- [ ] Ensure / double check that optimizer settings from `ds_config.json` aren't being overwritten by some defaults in `megatron/arguments.py` - - [ ] specifically, `momentum, beta{1, 2}, etc` - -
✅ Completed +> [!NOTE] +> [`train_llama_alcf.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/train_llama_alcf.sh) is the main entry point for launching +> distributed training on {Polaris, Aurora, Sunspot} @ ALCF. -- Continue runs on Polaris @ - - [x] 48 Nodes - - [x] 32 Nodes - - [x] 16 Nodes - - [x] 8 Nodes - - [x] 4 Nodes -- [x] Then, try re-creating ( / fixing) conda with `cuda==12.1` - - 😔, failed. - -- ~~‼️ Unable to save checkpoints with `torch==2.1` + `cuda==11.8`~~: - - Fixed in [a57a21f](https://github.com/argonne-lcf/Megatron-DeepSpeed/commit/a57a21f6b2a8abf847f5ef599e1b1edcb5a5e1b5) + -
🐛 Bug - - - Training progresses OK: +## 🏃‍♂️ Running - ```bash - [2024-03-07 15:27:02,646] [INFO] [timer.py:260:stop] epoch=0/micro_step=199/global_step=199, RunningAvgSamplesPerSec=58.730622229657506, CurrSamplesPerSec=61.35304005128382, MemAllocated=6.01GB, MaxMemAllocated=19.52GB - iteration 199/ 317892 | consumed samples: 152832 | consumed tokens: 625999872 | elapsed time per iteration (ms): 14287.5 | learning rate: 2.407E-04 | global batch size: 768 | lm loss: 5.905366E+00 | loss scale: 8192.0 | actual seqlen: 4096 | number of skipped iterations: 0 | number of nan iterations: 0 | samples per second: 53.753 | tokens per gpu per second (tgs): 1146.733 | TFLOPs: 69.85 | - [2024-03-07 15:27:15,063] [INFO] [logging.py:96:log_dist] [Rank 0] step=200, skipped=4, lr=[0.000240653265864008, 0.000240653265864008], mom=[(0.9, 0.999), (0.9, 0.999)] - [2024-03-07 15:27:17,188] [INFO] [timer.py:260:stop] epoch=0/micro_step=200/global_step=200, RunningAvgSamplesPerSec=58.730745476291396, CurrSamplesPerSec=58.75503515561452, MemAllocated=6.01GB, MaxMemAllocated=19.52GB - iteration 200/ 317892 | consumed samples: 153600 | consumed tokens: 629145600 | elapsed time per iteration (ms): 14541.4 | learning rate: 2.407E-04 | global batch size: 768 | lm loss: 5.897035E+00 | loss scale: 8192.0 | actual seqlen: 4096 | number of skipped iterations: 0 | number of nan iterations: 0 | samples per second: 52.815 | tokens per gpu per second (tgs): 1126.713 | TFLOPs: 68.63 | - saving checkpoint at iteration 200 to checkpoints/ds_stage2_nl32_hs4096_mb8_seq4096_gb768_pp1_tp2_fp16 - # ... - ``` +To launch on Polaris @ ALCF: - - Then crashes with: - ```python - Traceback (most recent call last): - Traceback (most recent call last): - File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/pretrain_gpt_alcf.py", line 575, in - model = main() - File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/pretrain_gpt_alcf.py", line 554, in main - model = pretrain( - File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/training.py", line 226, in pretrain - iteration = train(forward_step_func, - File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/training.py", line 1290, in train - save_checkpoint_and_time(iteration, model, optimizer, - File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/training.py", line 1151, in save_checkpoint_and_time - save_checkpoint(iteration, model, optimizer, opt_param_scheduler) - File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/checkpointing.py", line 259, in save_checkpoint - state_dict[UNIVERSAL_CHECKPOINT_INFO] = _universal_checkpoint_info(model) - File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/checkpointing.py", line 783, in _universal_checkpoint_info - info.update(model[0].universal_checkpoint_info()) - File "/lus/eagle/projects/datascience/foremans/tmp/Megatron-DeepSpeed/megatron/model/gpt_model.py", line 203, in universal_checkpoint_info - info[TP_REPLICATED_PARAMETER_PATTERNS] = self._get_tp_replicated_param_patterns() - File "/lus/eagle/projects/datascience/foremans/miniconda3/envs/polaris/2024-03-06/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1695, in __getattr__ - raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'") - AttributeError: 'GPTModel' object has no attribute '_get_tp_replicated_param_patterns' - ``` - 🤔 +
⏳ Request an interactive job with qsub -I: + +```bash +qsub -A -
+
⬇️ Clone repo + navigate into it: -
+```bash +git clone "https://github.com/argonne-lcf/Megatron-DeepSpeed" +cd Megatron-DeepSpeed +```
+
🐍 Setup Python: + +```bash +module use /soft/modulefiles ; module load conda ; conda activate base +PBS_O_WORKDIR=$(pwd) source ALCF/helpers.sh && setup_venv_from_conda +``` + +- 🍋 Install [`ezpz`](https://github.com/saforem2/ezpz): + + ```bash + mkdir deps && git clone https://github.com/saforem2/ezpz deps/ezpz + python3 -m pip install -e deps/ezpz --require-virtualenv + ``` +
-## 🏃‍♂️ Running -> [!NOTE] -> [`train_llama_alcf.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/train_llama_alcf.sh) is the main entry point for launching -> distributed training on {Polaris, Aurora, Sunspot} @ ALCF. +
🚀 Launch: -To launch on Polaris @ ALCF: +In this case, train a ~ 2B Model (with 10 layers), +for 1000 iterations using the data file list in: -> [!IMPORTANT] -> **Launch Instructions** on Polaris @ ALCF -> -> 1. Request an interactive job with `qsub -I`: -> -> ```bash -> $ qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I -> ``` -> -> 2. Clone repo + navigate into it: -> ```sh -> $ cd /path/to/Megatron-DeepSpeed/ # or git clone https://github.com/argonne-lcf/Megatron-DeepSpeed -> ``` -> -> 3. Load required modules: -> -> ```sh -> $ module use /soft/modulefiles -> $ module load conda/2024-04-29 -> $ conda activate base -> ``` -> -> 4. Launch: -> -> ```sh -> $ export PBS_O_WORKDIR="$(pwd)" && DATA_FILE_LIST=./ALCF/data-lists/polaris/books.txt DTYPE=bf16 OPT=adamw bash train_llama_alcf.sh -> ``` +[`ALCF/data-lists/polaris/books.txt`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/data-lists/polaris/books.txt) + +with a micro-batch-size of 2, with the `torch.optim.AdamW` optimizer. + +**Note** that _any_ of the options in the + +[`setParams`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/helpers.sh#L140) + +function from + +[`ALCF/helpers.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/7d203596dbf14e048e756c5ee6705de7dcb22283/ALCF/helpers.sh) + +can be overridden dynamically at runtime using this technique. + +```bash +PBS_O_WORKDIR=$(pwd) DATA_FILE_LIST=./ALCF/data-lists/polaris/books.txt TRAIN_ITER=1000 NLAYERS=10 MICRO_BATCH=2 OPT=adamw bash train_llama_alcf.sh +```
[output]: @@ -477,6 +447,34 @@ training ...
+
+ + + + + + +
🚀 Launch: @@ -66,14 +100,8 @@ for 1000 iterations using the data file list in: with a micro-batch-size of 2, with the `torch.optim.AdamW` optimizer. -**Note** that _any_ of the options in the - -[`setParams`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/helpers.sh#L140) - -function from - -[`ALCF/helpers.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/7d203596dbf14e048e756c5ee6705de7dcb22283/ALCF/helpers.sh) - +**Note** that _any_ of the options in the [`setParams`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/main/ALCF/helpers.sh#L140) +function from [`ALCF/helpers.sh`](https://github.com/argonne-lcf/Megatron-DeepSpeed/blob/7d203596dbf14e048e756c5ee6705de7dcb22283/ALCF/helpers.sh) can be overridden dynamically at runtime using this technique. ```bash From b37174223577f1b6dcc3085f58df77424e3bc222 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 24 May 2024 06:23:09 -0500 Subject: [PATCH 259/268] Add `setup_tokenizer_and_data()` function to `ALCF/helpers.sh` --- ALCF/helpers.sh | 145 +++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 138 insertions(+), 7 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 9e7e2b582b..6a647952ed 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -16,6 +16,22 @@ export WORKING_DIR="${WORKING_DIR}" printf "Using WORKING_DIR: %s\n" ${WORKING_DIR} +save_dotenv() { + if [[ "$#" -ne 1 ]]; then + estr="[error]" + # echo "Expected exactly one argument, specifying outputdir. Received $#" + printf "%s Expected one argument (outdir). Received: %s" "$(printRed ${estr})" "$#" + else + outdir="$1" + module list + dotenv_file="${outdir}/.env" + echo "Saving environment to ${dotenv_file}" + printenv | grep -v "LS_COLORS" > "${dotenv_file}" + export DOTENV_FILE="${dotenv_file}" + fi +} + + function get_machine() { if [[ $(hostname) == x4* ]]; then machine="aurora" @@ -100,14 +116,14 @@ function loadCondaEnv() { function setupLauncher() { # outdir=$1 if [[ -n "${DIST_LAUNCH}" && ${LAUNCH_CMD:-"MPICH"} != "deepspeed" ]]; then - export LAUNCH_CMD="${DIST_LAUNCH} --genvall --cpu-bind depth -d 16 $(which python3) -Wignore ${EXEC}" + export LAUNCHER="${DIST_LAUNCH} --genvall --cpu-bind depth -d 16 $(which python3) -Wignore ${EXEC}" else # Assert `./hostfile_deepspeed` exists export hfds="${WORKING_DIR}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit - export LAUNCH_CMD="deepspeed --hostfile $hfds --launcher MPICH ${EXEC}" + export LAUNCHER="deepspeed --hostfile $hfds --launcher MPICH ${EXEC}" fi - printf "%s" "$(printRed 'Launching with:')" - printf " %s" "$(printMagenta ${LAUNCH_CMD})" + printf "Launching with: %s\n" "$(printRed "${LAUNCH_CMD}")" + printf " %s" "$(printMagenta ${LAUNCHER})" } function setDSlauncher() { @@ -219,8 +235,8 @@ function setParams() { export USE_ACTIVATION_CHECKPOINTING=${USE_ACTIVATION_CHECKPOINTING:-1} # USE ACTIVATION CHECKPOINTING ? export GLOBAL_BATCH_MAX=$(( $WORLD_SIZE * $MICRO_BATCH * $GRAD_ACC_STEPS / $TP / $PP )) # MAX GLOBAL BATCH SIZE export GLOBAL_BATCH="${GLOBAL_BATCH:-${GLOBAL_BATCH_MAX}}" # WILL USE MAX IF NOT SET IN ENVIRONMENT - tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model - export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" # USE TOKENIZER_MODEL from env, else fallback from ^ + # tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model + # export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" # USE TOKENIZER_MODEL from env, else fallback from ^ export MODEL_TYPE="llama-seq${SEQ}-pp${PP}-tp${TP}-${NLAYERS}layers-${HEADS}heads-${HIDDEN}hidden" # STRING FOR IDENTIFYING MODEL # +----[ADDITIONAL LLAMA SPECIFIC ARGUMENTS]------------------------------ export LLAMA_ARGS="${LLAMA_ARGS} --no-query-key-layer-scaling --use-rotary-position-embeddings --untie-embeddings-and-output-weights --swiglu --normalization rmsnorm --disable-bias-linear" @@ -498,6 +514,23 @@ setup_conda_polaris() { fi } +########################################################## +# Check that we can find the `.py` file we wish to launch +########################################################## +check_executable() { + fp=$1 + if [[ -f "${fp}" ]]; then + export EXEC="${EXEC}" + # ----[1.5 Keep track of stem from file path]------------------------- + exec_stem=$(echo "${EXEC}" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.py//g") + export EXEC_STEM="${exec_stem}" + else + estr="Unable to locate executable ${fp}" + printf "[ALCF.helpers:check_executable] %s" "$(printRed ${estr})" + fi +} + + function setEnv() { local virtual_env="${VIRTUAL_ENV-}" @@ -578,17 +611,109 @@ function makeHostfiles() { fi } +################################################## +# Setup tokenizer as either Llama2 or GPT2 style +################################################## +setup_tokenizer_and_data() { + # if [[ ${tok} == Llama* || ${tok} == llama* || ${tok} == LLAMA* ]]; then + # tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model + # export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" # USE TOKENIZER_MODEL from env, else fallback from ^ + # export TOKENIZER_TYPE="Llama2" + # setData + # elif [[ ${tok} == gpt* || ${tok} == GPT* ]]; then + # export DATA_PARENT="${DATA_PARENT:-/gila/Aurora_deployment/foremans/anl_24_q2_release/Megatron-DeepSpeed/dataset}" + # export VOCAB_FILE="${DATA_PARENT}/gpt2-vocab.json" + # export MERGE_FILE="${DATA_PARENT}/gpt2-merges.txt" + # export DATA_PATH="${DATA_PARENT}/BookCorpusDataset_text_document" + # export TOKENIZER_FLAGS="--data-path $DATA_PATH--vocab-file $VOCAB_FILE --merge-file $MERGE_FILE" + # # export TOKENIZER_TYPE="${TOKENIZER_TYPE:-GPT2}" + # export TOKENIZER_TYPE="GPT2" + # else + # echo "Unknown tokenizer ${tok} passed" + # fi + if [[ "$#" == 1 ]]; then + tok="$1" + dfl="${DATA_FILE_LIST:-}" + # echo "Setting up tokenizer with ${tok}" + # elif [[ "$#" -ne 2 ]]; then + elif [[ "$#" == 2 ]]; then + tok="$1" + dfl="$2" + # tok="${TOKENIZER_TYPE:-Llama2}" + else + echo "Incorrect number of arguments passed. Received: $#, expected 2" + fi + echo "Setting up tokenizer with ${tok}" + echo "Using data_file_list: ${dfl}" + if [[ ${tok} == gpt* || ${tok} == GPT* ]]; then + export TOKENIZER_TYPE="GPT2" + export TOKENIZER_FLAGS="--tokenizer-type GPT2BPETokenizer" + export DATA_PARENT="${DATA_PARENT:-/gila/Aurora_deployment/foremans/anl_24_q2_release/Megatron-DeepSpeed/dataset}" + export VOCAB_FILE="${DATA_PARENT}/gpt2-vocab.json" + export MERGE_FILE="${DATA_PARENT}/gpt2-merges.txt" + export DATA_PATH="${DATA_PARENT}/BookCorpusDataset_text_document" + # TOKENIZER_FLAGS="--data-path $DATA_PATH--vocab-file $VOCAB_FILE --merge-file ${MERGE_FILE}" + export DATA_FLAGS="--data-path ${DATA_PATH} --vocab-file ${VOCAB_FILE} --merge-file ${MERGE_FILE}" + # export TOKENIZER_TYPE="${TOKENIZER_TYPE:-GPT2}" + # else [[ ${tok} == Llama* || ${tok} == llama* || ${tok} == LLAMA* ]]; then + else + export DATA_FLAGS="" + export TOKENIZER_TYPE="Llama2" + tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model + export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" # USE TOKENIZER_MODEL from env, else fallback from ^ + export TOKENIZER_FLAGS="${TOKENIZER_FLAGS} --tokenizer-type Llama2Tokenizer --tokenizer-model ${TOKENIZER_MODEL}" + if [[ "${TOKENIZER_TYPE}" != "GPT2" ]]; then + echo "Using tokenizer: ${TOKENIZER_TYPE}. Setting up data with ${DATA_FILE_LIST-}" + setData "${dfl}" || exit + # setData "${DATA_FILE_LIST-}" || exit # 09. Specify `DATA_FILE_LIST` for dolma dataset + fi + # --tokenizer-model ${TOKENIZER_MODEL} \ + fi + # export DATA_FLAGS="${DATA_FLAGS}" + # export TOKENIZER_TYPE="${TOKENIZER_TYPE}" + # export TOKENIZER_FLAGS="${TOKENIZER_FLAGS}" + printf "[setData] DATA_FLAGS: %s\n" "$(printGreen ${DATA_FLAGS})" + printf "[setData] TOKENIZER_FLAGS: %s\n" "$(printMagenta ${TOKENIZER_FLAGS})" + # if [[ "${TOKENIZER_TYPE}" != "GPT2" ]]; then + # echo "Using tokenizer: ${TOKENIZER_TYPE}. Setting up data with ${DATA_FILE_LIST-}" + # setData "${DATA_FILE_LIST-}" || exit # 09. Specify `DATA_FILE_LIST` for dolma dataset + # fi +} + + ############################################### # `setData`: # Ensure `DATA_FILE_LIST` is set, # fallback to default values if necessary. ############################################### function setData() { # ------------------------[dfl: abbrv. for DATA_FILE_LIST] + # if [[ "$#" -ne 1 ]]; then + # tok="${TOKENIZER_TYPE:-Llama2}" + # else + # tok="$1" + # fi + # echo "Setting up tokenizer with ${tok}" + # setup_tokenizer "${tok}" + # tok="${TOKENIZER_TYPE:-}" + # if [[ ${tok} == gpt* || ${tok} == GPT* ]]; then + # export TOKENIZER_TYPE="GPT2" + # export DATA_PARENT="${DATA_PARENT:-/gila/Aurora_deployment/foremans/anl_24_q2_release/Megatron-DeepSpeed/dataset}" + # export VOCAB_FILE="${DATA_PARENT}/gpt2-vocab.json" + # export MERGE_FILE="${DATA_PARENT}/gpt2-merges.txt" + # export DATA_PATH="${DATA_PARENT}/BookCorpusDataset_text_document" + # # TOKENIZER_FLAGS="--data-path $DATA_PATH--vocab-file $VOCAB_FILE --merge-file ${MERGE_FILE}" + # DATA_FLAGS="--data-path ${DATA_PATH} --vocab-file ${VOCAB_FILE} --merge-file ${MERGE_FILE}" + # # export TOKENIZER_TYPE="${TOKENIZER_TYPE:-GPT2}" + # # else [[ ${tok} == Llama* || ${tok} == llama* || ${tok} == LLAMA* ]]; then + # else + # export TOKENIZER_TYPE="Llama2" + # tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model + # export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" # USE TOKENIZER_MODEL from env, else fallback from ^ + # TOKENIZER_FLAGS="${TOKENIZER_FLAGS} --tokenizer-type Llama2Tokenizer" # dfldir="${WORKING_DIR}/ALCF/data-lists" # =====[Set DATA_FILE_LIST_FALLBACK based on current machine]============== if [[ $(hostname) == x4* ]]; then # -----------------------------[AURORA] dfl_fallback="/home/foremans/anl_24_release_q4/llm.devkit/Megatron-DeepSpeed/data_file_list_reweighted.txt" - elif [[ $(hostname) == x1* ]]; then # ----------------------------[SUNSPOT] # shellcheck: source ./data-lists/sunspot/books.txt dfl_fallback="${WORKING_DIR}/ALCF/data-lists/sunspot/books.txt" @@ -623,6 +748,7 @@ function setData() { # ------------------------[dfl: abbrv. for DATA_FILE_LIST] export WEIGHT_SUM="${ws}" export DFL_STEM="${dfl_stem}" export DATA_CACHE_PATH="${dcp}" + export DATA_FLAGS="${DATA_FLAGS} --data-file-list ${DATA_FILE_LIST} --data-cache-path ${DATA_CACHE_PATH}" echo "--------------------" echo "Updated environment:" printf "DATA_FILE_LIST: %s\n" "${DATA_FILE_LIST}" @@ -631,6 +757,11 @@ function setData() { # ------------------------[dfl: abbrv. for DATA_FILE_LIST] printf "DFL_STEM: %s\n" "${DFL_STEM}" printf "DATA_CACHE_PATH: %s\n" "${DATA_CACHE_PATH}" echo "--------------------" + # fi + # export DATA_FLAGS="${DATA_FLAGS}" + # export TOKENIZER_FLAGS="${TOKENIZER_FLAGS}" + # printf "[setData] DATA_FLAGS: %s\n" "$(printGreen ${DATA_FLAGS})" + # printf "[setData] TOKENIZER_FLAGS: %s\n" "$(printMagenta ${TOKENIZER_FLAGS})" } function generateDSconfig() { From d93fb7f41eeda59a3c90f90984979da4db4212bf Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 24 May 2024 06:23:22 -0500 Subject: [PATCH 260/268] Update `train_llama_alcf.sh` --- train_llama_alcf.sh | 83 +++++++++++++++++++++++++++++---------------- 1 file changed, 54 insertions(+), 29 deletions(-) diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index fee2e392dc..9a6d39923c 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -5,14 +5,26 @@ #PBS -l select=48 #PBS -l filesystems=eagle:home + #### Make it easy to track experiments by date ################### -YEAR="$(date "+%Y")" -MONTH="$(date "+%m")" -DAY="$(date "+%Y-%m-%d")" -TODAY="$(date "+%Y-%m-%d")" # kept for backwards compatibility -STARTED_AT="$(date "+%Y-%m-%d-%H%M%S")" +year="$(date "+%Y")" +month="$(date "+%m")" +day="$(date "+%Y-%m-%d")" +today="$(date "+%Y-%m-%d")" # kept for backwards compatibility +started_at="$(date "+%Y-%m-%d-%H%M%S")" +export YEAR="${year}" +export MONTH="${month}" +export DAY="${day}" +export TODAY="${today}" +export STARTED_AT="${started_at}" ################################################################## + +############################################################################# +# Check if running in `DEBUG=1` mode. +# - If so, this will print each command before it is ran and exit if any of +# them return a nonzero exit status. +############################################################################# if [[ -n "${DEBUG-}" ]]; then # to use: `DEBUG=1 bash train_llama_alcf.sh` printf "\e[1;31m%s\e[0m\n" "!! RUNNING IN DEBUG MODE !!" set -euxo pipefail @@ -23,6 +35,9 @@ if [[ -v NOOP ]]; then # to use: `NOOP=1 bash train_llama_alcf.sh` set -o noexec # same as set -n fi +################################################## +# Helper function for `source`-ing another file +################################################## sourceFile() { fp="$1" echo "source-ing ${fp}" @@ -34,6 +49,8 @@ sourceFile() { fi } +############################################################################## +###################### MAIN LOGIC ############################################ # ----[0. Navigate into `$PBS_O_WORKDIR`]-------------------------------------- cd "${PBS_O_WORKDIR}" || exit HERE=$(python3 -c 'import os; print(os.getcwd())') @@ -43,6 +60,11 @@ export HERE export EXEC="${HERE}/pretrain_gpt_alcf.py" [ -f "${EXEC}" ] || exit +# ----[1.5 Keep track of ] +exec_stem=$(echo "${EXEC}" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.py//g") +export EXEC_STEM="${exec_stem}" + + # ----[2. `source ./ALCF/helpers_alcf.sh`:]------------------------------------ sourceFile "${HERE}/ALCF/helpers.sh" || exit @@ -55,10 +77,15 @@ setParams || exit # 05. Set command line arguments to pass t buildDSconfig || exit # 06. Create `deepspeed_config.json` from runtime params from ^ setOutput || exit # 07. Specify output directory for {logs, checkpoints, etc.} setArgs || exit # 08. Specify additional `deepspeed` arguments -setData "${DATA_FILE_LIST-}" || exit # 09. Specify `DATA_FILE_LIST` for dolma dataset -printJobInfo || exit # 11. Print job info -setupLauncher || exit # 12. set launcher to one of `MPICH` (default), or `deepspeed` +dfl="${DATA_FILE_LIST:-}" # 09. Setup data + tokenizer +tok="${TOKENIZER_TYPE:-Llama2}" # via `DATA_FILE_LIST` and `TOKENIZER_TYPE` +setup_tokenizer_and_data "${tok}" "${dfl}" || exit +printJobInfo || exit # 10. Print job info +setupLauncher || exit # 11. set launcher to one of `MPICH` (default), or `deepspeed` +save_dotenv "${CKPT_DIR}" || exit # 12. Print info about loaded modules and runtime environment +check_and_kill_if_running || exit # 13. Check that were not already running, if so, exit. # ----------------------------------------------------------------------------- +############################################################################## ################################################ # Assert `$TBDIR` exists inside our `$CKPT_DIR` @@ -69,31 +96,33 @@ mkdir -p "${TBDIR}" data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" && mkdir -p "${data_cache_path}" -# Print info about loaded modules and runtime environment -module list -dotenv_file="${CKPT_DIR}/.env" -echo "Saving environment to ${dotenv_file}" -printenv | grep -v "LS_COLORS" > "${dotenv_file}" - -# Take custom args -custom_args=" $@" - # --log-num-zeros-in-grad \ - # --log-memory-to-tensorboard \ -run_cmd=" - ${LAUNCH_CMD} \ - --${DTYPE} \ +export DEFAULTS="\ --split 100,0,0 \ --log-interval 1 \ --no-bias-gelu-fusion \ --no-bias-dropout-fusion \ --no-masked-softmax-fusion \ - --tokenizer-type Llama2Tokenizer \ --no-gradient-accumulation-fusion \ --accumulate-allreduce-grads-in-fp32 \ --use-checkpoint-opt_param-scheduler \ --log-timers-to-tensorboard \ - --log-optimizer-states-to-tensorboard \ + --log-optimizer-states-to-tensorboard" + +# Take custom args +custom_args=" $@" + + # --log-num-zeros-in-grad \ + # --log-memory-to-tensorboard \ + # --data-file-list ${DATA_FILE_LIST} \ + # --data-file-list ${DATA_FILE_LIST} \ + # --data-cache-path ${data_cache_path} \ + # --tokenizer-type Llama2Tokenizer \ + # --tokenizer-model ${TOKENIZER_MODEL} \ +run_cmd=" + ${LAUNCHER} \ + --${DTYPE} \ + ${DEFAULTS} \ --optimizer ${OPT} \ --save ${CKPT_DIR} \ --load ${CKPT_DIR} \ @@ -109,27 +138,23 @@ run_cmd=" --eval-interval ${EVAL_INTERVAL} \ --max-position-embeddings ${SEQ} \ --micro-batch-size ${MICRO_BATCH} \ - --data-file-list ${DATA_FILE_LIST} \ --tensor-model-parallel-size ${TP} \ --global-batch-size ${GLOBAL_BATCH} \ --pipeline-model-parallel-size ${PP} \ --num-key-value-heads ${NUM_KV_HEAD} \ - --data-cache-path ${data_cache_path} \ --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ - --tokenizer-model ${TOKENIZER_MODEL} \ ${LR_ARGS} \ ${LLAMA_ARGS} \ ${TIMING_STR} \ + ${DATA_FLAGS} \ + ${TOKENIZER_FLAGS} \ $ds_args \ ${gpt_args[*]} \ $custom_args \ |& tee ${OUTPUT_LOG} " -check_and_kill_if_running || exit echo "${run_cmd}" printf "[!! %s] View output at:\n %s\n" "$(printBlue "NOTE")" "$(printYellow ${OUTPUT_LOG})" -# printf "[!! \e[1;31m%s\e[0m] View output at:\n" "NOTE" -# printf "\e[1;34m%s\e[0m\n" "${OUTPUT_LOG}" eval "${run_cmd}" set +x From 05d82c3911f2643d55ef3da5f497c9bfba70313b Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 24 May 2024 06:23:56 -0500 Subject: [PATCH 261/268] Update `train_aGPT_7B.sh` --- train_aGPT_7B.sh | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/train_aGPT_7B.sh b/train_aGPT_7B.sh index 0907f8163c..e5035ae27b 100644 --- a/train_aGPT_7B.sh +++ b/train_aGPT_7B.sh @@ -7,13 +7,12 @@ cd "${PBS_O_WORKDIR}" || exit HOSTNAME=$(hostname) if [[ "${HOSTNAME}" == x3* ]]; then MACHINE="polaris" - # XXX: ¯\_(ツ)_/¯ + # XXX: # - On Polaris, we see that: # - on 1 or 2 nodes, only MICRO_BATCH=1 will fit in memory # - on 8 nodes, MICRO_BATCH=2 will fit in memory # - on 48 nodes, MICRO_BATCH=4 will fit in memory - # - export nhosts=$(wc -l < "${PBS_NODEFILE}") + nhosts=$(wc -l < "${PBS_NODEFILE}") if [[ "${nhosts}" == 1 ]]; then export MBS=1 elif [[ "${nhosts}" == 2 ]]; then @@ -29,6 +28,7 @@ elif [[ "${HOSTNAME}" == x4* ]]; then MACHINE="aurora" fi +export nhosts OUTDIR="${PBS_O_WORKDIR}/pbslogs" mkdir -p "${OUTDIR}" OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" From 6de8496e435fdf9a2c32ac5b627afecc62f1aa32 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 24 May 2024 06:24:21 -0500 Subject: [PATCH 262/268] Update `ALCF/README.md` --- ALCF/README.md | 20 ++++++++++++++------ 1 file changed, 14 insertions(+), 6 deletions(-) diff --git a/ALCF/README.md b/ALCF/README.md index 29169932d2..907cbd36cc 100644 --- a/ALCF/README.md +++ b/ALCF/README.md @@ -19,10 +19,10 @@ ## 🏃‍♂️ Running -To launch on Polaris @ [ALCF](https://alcf.anl.gov): +To launch on {`Polaris`, `Sunspot`} @ [ALCF](https://alcf.anl.gov):
⏳ Request an interactive job with qsub -I: - + ```bash qsub -A -q debug -l select=2 -l walltime=01:00:00,filesystems=eagle:home -I ``` @@ -42,14 +42,22 @@ cd Megatron-DeepSpeed 1. 📂 Load `conda` module and activate base environment: - ```bash - module use /soft/modulefiles ; module load conda ; conda activate base - ``` + - **Polaris**: + + ```bash + module use /soft/modulefiles ; module load conda ; conda activate base + ``` + + - **Sunspot**: + + ```bash + source ALCF/sunspot-env-2024-04-15-002.sh + ``` 3. 👻 Create virtual environment _on top of the base `conda`_[^venv]: ```bash - PBS_O_WORKDIR=$(pwd) source ALCF/helpers.sh && setup_venv_from_conda + export PBS_O_WORKDIR=$(pwd) && source ALCF/helpers.sh && setup_venv_from_conda ``` From 03aa7c11c0d5afd5c516b52b341b078c04c594fe Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 24 May 2024 08:22:23 -0500 Subject: [PATCH 263/268] Update `ALCF/helpers.sh` --- ALCF/helpers.sh | 265 ++++++++++++++++++++++++------------------------ 1 file changed, 130 insertions(+), 135 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index 6a647952ed..a9af22416d 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -23,6 +23,7 @@ save_dotenv() { printf "%s Expected one argument (outdir). Received: %s" "$(printRed ${estr})" "$#" else outdir="$1" + mkdir -p "${outdir}" module list dotenv_file="${outdir}/.env" echo "Saving environment to ${dotenv_file}" @@ -32,7 +33,26 @@ save_dotenv() { } -function get_machine() { +where_am_i() { + if [[ $(hostname) == x4* ]]; then + machine="aurora" + elif [[ $(hostname) == x1* ]]; then + machine="sunspot" + elif [[ $(hostname) == x3* ]]; then + if [[ "${PBS_O_HOST}" == sirius* ]]; then + machine="sirius" + else + machine="polaris" + fi + elif [[ $(hostname) == nid* ]]; then + machine="perlmutter" + else + machine=$(hostname) + fi + echo "${machine}" +} + +get_machine() { if [[ $(hostname) == x4* ]]; then machine="aurora" elif [[ $(hostname) == x1* ]]; then @@ -53,7 +73,7 @@ function get_machine() { } -function check_and_kill_if_running() { +check_and_kill_if_running() { # kill $(ps aux | grep -E "$USER.+(mpi|main.py)" | grep -v grep | awk '{print $2}') RUNNING_PIDS=$(lsof -i:29500 -Fp | head -n 1 | sed 's/^p//') if [[ -n "${RUNNING_PIDS}" ]]; @@ -64,7 +84,7 @@ function check_and_kill_if_running() { } -function setupSrun() { +setupSrun() { if [[ $(hostname) == login* || $(hostname) == nid* ]]; then export NHOSTS="${SLURM_NNODES:-1}" export NGPU_PER_HOST="${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}" @@ -76,7 +96,7 @@ function setupSrun() { } -function printJobInfo() { +printJobInfo() { echo "++++++++++++++++++++++++++++++++++++++++++++++++++" echo "- MPICH_DIR=${MPICH_DIR:-${MPI_ROOT}}" echo "- Using $(which python3)" @@ -87,7 +107,7 @@ function printJobInfo() { echo "++++++++++++++++++++++++++++++++++++++++++++++++++" } -function setupVenv() { +setupVenv() { VENV_DIR="$1" if [[ -d "${VENV_DIR}" ]]; then echo "Found venv at: ${VENV_DIR}" @@ -97,7 +117,7 @@ function setupVenv() { fi } -function loadCondaEnv() { +loadCondaEnv() { if [[ "${CONDA_EXE}" ]]; then echo "Already inside ${CONDA_EXE}, exiting!" else @@ -113,7 +133,7 @@ function loadCondaEnv() { } -function setupLauncher() { +setupLauncher() { # outdir=$1 if [[ -n "${DIST_LAUNCH}" && ${LAUNCH_CMD:-"MPICH"} != "deepspeed" ]]; then export LAUNCHER="${DIST_LAUNCH} --genvall --cpu-bind depth -d 16 $(which python3) -Wignore ${EXEC}" @@ -126,7 +146,7 @@ function setupLauncher() { printf " %s" "$(printMagenta ${LAUNCHER})" } -function setDSlauncher() { +setDSlauncher() { # launcher setting outdir=$1 export hfds="$outdir/hostfile_deepspeed" @@ -141,7 +161,7 @@ function setDSlauncher() { fi } -function set_lr_args() { +set_lr_args() { LR_ARGS="--lr ${LR} --lr-decay-style cosine" if [[ -n "${LR_DECAY_ITERS:-}" ]]; then LR_ARGS="${LR_ARGS} --lr-decay-iters ${LR_DECAY_ITERS}" @@ -153,7 +173,22 @@ function set_lr_args() { export LR_ARGS="${LR_ARGS}" } -function setParams() { + +get_batch_size_on_polaris() { + if [[ $(hostname) == x3* ]]; then + local nhosts=$(wc -l < "${PBS_NODEFILE}") + if [[ "${nhosts}" == 1 || "${nhosts}" == 2 ]]; then + mbs=1 + elif [[ "${nhosts}" -ge 3 ]]; then + mbs=2 + elif [[ "${nhosts}" -ge 8 ]]; then + mbs=4 + fi + fi + echo "${mbs}" +} + +setParams() { LLAMA_ARGS="" # +----[Parallelism Settings] -------------------------------------------+ # +------[Aurora]--------||-------[SunSpot]-------------+ @@ -182,7 +217,8 @@ function setParams() { export DTYPE=${DTYPE:-fp16} # DTYPE: FP16 export GRAD_ACC_STEPS=${GRAD_ACC_STEPS:-8} # GRADIENT_ACC_STEPS # NOTE: MICRO_BATCH is exported below - MICRO_BATCH=${MICRO_BATCH:-2} # MICRO_BATCH = 8 + # MICRO_BATCH=${MICRO_BATCH:-2} # MICRO_BATCH = 8 + export MICRO_BATCH="${MICRO_BATCH:-$(get_batch_size_on_polaris)}" if [[ -n "${NO_FLASH_ATTN-}" ]]; then echo "Not using flash-attn!!" else @@ -257,7 +293,7 @@ function setParams() { } -function setArgs() { +setArgs() { # ---- Set DeepSpeed arguments -------------------------------- ds_args=" " ds_args=" --deepspeed ${ds_args}" @@ -288,7 +324,7 @@ function setArgs() { } -function make_ds_hostfile() { +make_ds_hostfile() { export GPUS_PER_NODE="${GPUS_PER_NODE:-${NGPU_PER_HOST:-${SLURM_GPUS_ON_NODE:-$(nvidia-smi -L | wc -l)}}}" # ---- Make MPICH hostfile ---------------- hf="${HOSTFILE:-${PBS_NODEFILE}}" @@ -304,33 +340,45 @@ function make_ds_hostfile() { # | 1. Git clone ezpz (if not found) | # | 2. Install ezpz (if not installed) | # +---------------------------------------+ -function ezpz() { +ezpz() { if [[ ! -d "${WORKING_DIR}/deps/ezpz" ]]; then mkdir -p "${WORKING_DIR}/deps" git clone https://github.com/saforem2/ezpz "${WORKING_DIR}/deps/ezpz" else echo "Found ezpz!" fi - echo "Done with clone. Now, checking if ezpz is installed..." - # if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then - if python3 -c "import sys; any(['ezpz' in s for s in sys.path])" 2> '/dev/null'; then - echo "Has ezpz installed. Nothing to do." + ezloc=$(python3 -m pip list | grep ezpz | awk '{print $NF}') + if [[ -n "${ezloc}" ]]; then + echo "ezpz detected. Sourcing ${ezloc}/bin/savejobenv" + source "${ezloc}/src/ezpz/bin/savejobenv" > /dev/null 2>&1 + source "${ezloc}/src/ezpz/bin/getjobenv" || exit + make_ds_hostfile || exit else - echo "Does not have ezpz installed. Installing..." - echo "Using $(which python3) to install ezpz:" - python3 -m pip install -e "${WORKING_DIR}/deps/ezpz" # > ezpz-install.log 2>&1 + echo "No ezpz detected. Attempting to install with $(which python3)" + python3 -m pip install -e "${WORKING_DIR}/deps/ezpz" --require-virtualenv fi echo "Done with ezpz." - source ${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv > /dev/null 2>&1 #> /tmp/savejobenv.log 2>&1 || exit - source ${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv || exit - make_ds_hostfile || exit + # echo "Done with clone. Now, checking if ezpz is installed..." + # if python3 -c 'import ezpz; print(ezpz.__file__)' 2> '/dev/null'; then + # if [[ $(python3 -c "import sys; any(['ezpz' in s for s in sys.path])") 2> '/dev/null' ]]; then + # echo "Has ezpz installed. Nothing to do." + # else + # echo "Does not have ezpz installed. Installing..." + # echo "Using $(which python3) to install ezpz:" + # python3 -m pip install -e "${WORKING_DIR}/deps/ezpz" --verbose --require-virtualenv # > ezpz-install.log 2>&1 + # fi + # python3 -m pip install -e "${WORKING_DIR}/deps/ezpz" --verbose --require-virtualenv + # # echo "Done with ezpz." + # source ${WORKING_DIR}/deps/ezpz/src/ezpz/bin/savejobenv > /dev/null 2>&1 #> /tmp/savejobenv.log 2>&1 || exit + # source ${WORKING_DIR}/deps/ezpz/src/ezpz/bin/getjobenv || exit + # make_ds_hostfile || exit } # +------------------------------------------------------------------------+ # | Save important environment variables to .deepspeed_env, which will be | # | forwarded to ALL ranks with DeepSpeed | # +------------------------------------------------------------------------+ -function saveDSenv() { +saveDSenv() { echo "Saving {PATH, LD_LIBRARY_PATH, htt{p,ps}_proxy, CFLAGS, PYTHONUSERBASE} to .deepspeed_env" { echo "PATH=${PATH}" ; @@ -342,7 +390,7 @@ function saveDSenv() { } > .deepspeed_env } -function setOutput() { +setOutput() { # ---- Specify output location -------------------------------- OUTPUT_PREFIX="ws${WORLD_SIZE}_ds_stage${ZERO_STAGE}_nl${NLAYERS}" OUTPUT_PREFIX="${OUTPUT_PREFIX}_hs${HIDDEN}_mb${MICRO_BATCH}" @@ -367,7 +415,7 @@ function setOutput() { printf "Checkpoints will be saved to: %s\n" $(printYellow "${CKPT_DIR}") } -function buildDSconfig() { +buildDSconfig() { # ---- Build DeepSpeed Config --------------------------------- export CPU_OPTIMIZER="${CPU_OPTIMIZER:-0}" export DS_CONFIG="${WORKING_DIR}/ds-configs/ds_stage${ZERO_STAGE}_mb${MICRO_BATCH}_gb${GLOBAL_BATCH}_pp${PP}_${DTYPE}.json" @@ -381,13 +429,13 @@ function buildDSconfig() { } -function sumWeights() { +sumWeights() { local file_list=$1 weights=$(cat "${file_list}" | awk '{print $1}' | tr '\n' '\ ,\ ' | sed 's/^/[/g' | sed 's/$/]/g' | tr '\ ' "\,\ ") python3 -c "import numpy as np; print(np.sum(${weights}))" } -function sumFiles() { +sumFiles() { local rd=$1 for f in $("${rd}/*.txt"); do ws=$(sumWeights "${rd}/${f}") @@ -397,46 +445,23 @@ function sumFiles() { ######################################################## # Setup / activate conda environment, +# NOTE: +# +# Jerome's `frameworks_2024_5_v2` seems broken ?? +# - seems to be missing `python3 -c 'from mpi4py import MPI'` ??? +# - consequently, we leave the setup below commented out (for the time +# being): +# if [[ -z "${CONDA_PREFIX-}" ]]; then +# module use -a /home/jmitche1/anl_release/2024/q2 ; module load frameworks_2024_5_v2 +# else +# echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" +# fi ######################################################## setup_conda_sunspot() { ###### check if CONDA_PREFIX non-empty ################ if [[ -z "${CONDA_PREFIX:-}" ]]; then - # eval "$(~/miniconda3/bin/conda shell.zsh hook)" - # conda activate anl_24_q2_release module use /soft/preview-modulefiles/24.086.0 ; module load frameworks/2024.04.15.002.lua fi - # XXX: ------------------------------------------------------------------- - # Jerome's `frameworks_2024_5_v2` seems broken ?? - # - seems to be missing `python3 -c 'from mpi4py import MPI'` ??? - # - consequently, we leave the setup below commented out (for the time - # being): - # if [[ -z "${CONDA_PREFIX-}" ]]; then - # module use -a /home/jmitche1/anl_release/2024/q2 ; module load frameworks_2024_5_v2 - # else - # echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" - # fi - # ------------------------------------------------------------------------ - - ###### check if VIRTUAL_ENV non-empty #################################### - # venvs/anl_24_q2_release/bin/activate - # if [[ -d "${DEFAULT_VENV_PATH}" ]]; then - if [[ -z "${VIRTUAL_ENV:-}" ]]; then - if [[ -n "${CONDA_PREFIX}" ]]; then - VENV_DIR="${WORKING_DIR}/venvs/$(echo ${CONDA_PREFIX} | tr '\/' '\t' | awk '{print $NF}')" - else - VENV_DIR="${WORKING_DIR}/venvs/anl_24_q2_release" - fi - echo "Caught virtual env at ${VENV_DIR}!" - # source "${VENV_DIR}/bin/activate" || - if [[ ! -f "${VENV_DIR}/bin/activate" ]]; then - printf "[!! %s]: Unable to locate %s\n" "$(printRed "ERROR")" "$(printMagenta "${VENV_DIR}/bin/activate")" - # echo "[!ERROR]: Unable to locate ${VENV_DIR}/bin/activate !!" - else - source "${VENV_DIR}/bin/activate" - fi - else - echo "Found existing python at: $(which python3)" - fi } ######################## @@ -453,6 +478,21 @@ setup_conda_sirius() { fi } +######################## +# Setup conda on Polaris +######################## +setup_conda_polaris() { + # unset MPICH_GPU_SUPPORT_ENABLED + ###### check if CONDA_PREFIX non-empty ################ + if [[ -z "${CONDA_PREFIX-}" ]]; then + # if so, load the default conda/2024-04-29 + # module and activate base environment + module use /soft/modulefiles ; module load conda ; conda activate base + else + echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" + fi +} + setup_venv_from_conda() { if [[ -z "${CONDA_PREFIX}" ]]; then echo "No ${CONDA_PREFIX} found." # Exiting." @@ -488,32 +528,6 @@ setup_venv_from_conda() { } -######################## -# Setup conda on Polaris -######################## -setup_conda_polaris() { - # unset MPICH_GPU_SUPPORT_ENABLED - ###### check if CONDA_PREFIX non-empty ################ - if [[ -z "${CONDA_PREFIX-}" ]]; then - # if so, load the default conda/2024-04-29 - # module and activate base environment - module use /soft/modulefiles - module load conda/2024-04-29 ; conda activate base - else - echo "Caught CONDA_PREFIX=${CONDA_PREFIX}" - fi - ###### check if VIRTUAL_ENV non-empty ################# - if [[ -z "${VIRTUAL_ENV:-}" ]]; then - DEFAULT_VENV_PATH=${WORKING_DIR}/venvs/polaris/2024-04-29 - if [[ -d "${DEFAULT_VENV_PATH}" ]]; then - echo "Caught virtual env at ${DEFAULT_VENV_PATH}!" - source "${WORKING_DIR}/venvs/polaris/2024-04-29/bin/activate" - fi - else - echo "Found existing python at: $(which python3)" - fi -} - ########################################################## # Check that we can find the `.py` file we wish to launch ########################################################## @@ -532,12 +546,14 @@ check_executable() { -function setEnv() { - local virtual_env="${VIRTUAL_ENV-}" - local conda_prefix="${CONDA_PREFIX-}" +setEnv() { + local virtual_env="${VIRTUAL_ENV:-}" + local conda_prefix="${CONDA_PREFIX:-}" if [[ -n "${conda_prefix}" && -z "${virtual_env}" ]]; then echo "No virtual environment found." echo "Using conda from: ${conda_prefix}" + echo "Setting up venv from ${CONDA_PROMPT_MODIFIER:-}" + setup_venv_from_conda elif [[ -n "${virtual_env}" && -z "${conda_prefix}" ]]; then echo "No conda found." echo "Using virtual_env from: ${virtual_env}" @@ -589,6 +605,9 @@ function setEnv() { echo "Unable to setup python environment. Exiting" exit 1 fi + if [[ -z "${virtual_env}" ]]; then + setup_venv_from_conda + fi ##################################################################### pystr="Using: $(which python3)" printf "[python] %s" "$(printMagenta ${pystr})" @@ -603,7 +622,7 @@ function setEnv() { # - If so, use this. # - Otherwise, make default HOSTFILEs from "${PBS_NODEFILE}" ###################################################################### -function makeHostfiles() { +makeHostfiles() { if [[ -n "${HOSTFILE}" ]]; then printf "!! USING CUSTOM HOSTFILE FROM: %s" "${HOSTFILE}" else @@ -615,31 +634,12 @@ function makeHostfiles() { # Setup tokenizer as either Llama2 or GPT2 style ################################################## setup_tokenizer_and_data() { - # if [[ ${tok} == Llama* || ${tok} == llama* || ${tok} == LLAMA* ]]; then - # tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model - # export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" # USE TOKENIZER_MODEL from env, else fallback from ^ - # export TOKENIZER_TYPE="Llama2" - # setData - # elif [[ ${tok} == gpt* || ${tok} == GPT* ]]; then - # export DATA_PARENT="${DATA_PARENT:-/gila/Aurora_deployment/foremans/anl_24_q2_release/Megatron-DeepSpeed/dataset}" - # export VOCAB_FILE="${DATA_PARENT}/gpt2-vocab.json" - # export MERGE_FILE="${DATA_PARENT}/gpt2-merges.txt" - # export DATA_PATH="${DATA_PARENT}/BookCorpusDataset_text_document" - # export TOKENIZER_FLAGS="--data-path $DATA_PATH--vocab-file $VOCAB_FILE --merge-file $MERGE_FILE" - # # export TOKENIZER_TYPE="${TOKENIZER_TYPE:-GPT2}" - # export TOKENIZER_TYPE="GPT2" - # else - # echo "Unknown tokenizer ${tok} passed" - # fi if [[ "$#" == 1 ]]; then tok="$1" dfl="${DATA_FILE_LIST:-}" - # echo "Setting up tokenizer with ${tok}" - # elif [[ "$#" -ne 2 ]]; then elif [[ "$#" == 2 ]]; then tok="$1" dfl="$2" - # tok="${TOKENIZER_TYPE:-Llama2}" else echo "Incorrect number of arguments passed. Received: $#, expected 2" fi @@ -648,14 +648,18 @@ setup_tokenizer_and_data() { if [[ ${tok} == gpt* || ${tok} == GPT* ]]; then export TOKENIZER_TYPE="GPT2" export TOKENIZER_FLAGS="--tokenizer-type GPT2BPETokenizer" - export DATA_PARENT="${DATA_PARENT:-/gila/Aurora_deployment/foremans/anl_24_q2_release/Megatron-DeepSpeed/dataset}" + local machine=$(where_am_i) + if [[ ${machine} == "polaris" ]]; then + export DATA_PARENT="${DATA_PARENT:-/eagle/argonne_tpc/foremans/projects/argonne-lcf/Megatron-DeepSpeed/dataset}" + elif [[ ${machine} == "sunspot" ]]; then + export DATA_PARENT="${DATA_PARENT:-/gila/Aurora_deployment/foremans/anl_24_q2_release/Megatron-DeepSpeed/dataset}" + else + export DATA_PARENT="${DATA_PARENT:-${WORKING_DIR}/dataset}" + fi export VOCAB_FILE="${DATA_PARENT}/gpt2-vocab.json" export MERGE_FILE="${DATA_PARENT}/gpt2-merges.txt" export DATA_PATH="${DATA_PARENT}/BookCorpusDataset_text_document" - # TOKENIZER_FLAGS="--data-path $DATA_PATH--vocab-file $VOCAB_FILE --merge-file ${MERGE_FILE}" export DATA_FLAGS="--data-path ${DATA_PATH} --vocab-file ${VOCAB_FILE} --merge-file ${MERGE_FILE}" - # export TOKENIZER_TYPE="${TOKENIZER_TYPE:-GPT2}" - # else [[ ${tok} == Llama* || ${tok} == llama* || ${tok} == LLAMA* ]]; then else export DATA_FLAGS="" export TOKENIZER_TYPE="Llama2" @@ -665,19 +669,10 @@ setup_tokenizer_and_data() { if [[ "${TOKENIZER_TYPE}" != "GPT2" ]]; then echo "Using tokenizer: ${TOKENIZER_TYPE}. Setting up data with ${DATA_FILE_LIST-}" setData "${dfl}" || exit - # setData "${DATA_FILE_LIST-}" || exit # 09. Specify `DATA_FILE_LIST` for dolma dataset fi - # --tokenizer-model ${TOKENIZER_MODEL} \ fi - # export DATA_FLAGS="${DATA_FLAGS}" - # export TOKENIZER_TYPE="${TOKENIZER_TYPE}" - # export TOKENIZER_FLAGS="${TOKENIZER_FLAGS}" printf "[setData] DATA_FLAGS: %s\n" "$(printGreen ${DATA_FLAGS})" printf "[setData] TOKENIZER_FLAGS: %s\n" "$(printMagenta ${TOKENIZER_FLAGS})" - # if [[ "${TOKENIZER_TYPE}" != "GPT2" ]]; then - # echo "Using tokenizer: ${TOKENIZER_TYPE}. Setting up data with ${DATA_FILE_LIST-}" - # setData "${DATA_FILE_LIST-}" || exit # 09. Specify `DATA_FILE_LIST` for dolma dataset - # fi } @@ -686,7 +681,7 @@ setup_tokenizer_and_data() { # Ensure `DATA_FILE_LIST` is set, # fallback to default values if necessary. ############################################### -function setData() { # ------------------------[dfl: abbrv. for DATA_FILE_LIST] +setData() { # ------------------------[dfl: abbrv. for DATA_FILE_LIST] # if [[ "$#" -ne 1 ]]; then # tok="${TOKENIZER_TYPE:-Llama2}" # else @@ -764,7 +759,7 @@ function setData() { # ------------------------[dfl: abbrv. for DATA_FILE_LIST] # printf "[setData] TOKENIZER_FLAGS: %s\n" "$(printMagenta ${TOKENIZER_FLAGS})" } -function generateDSconfig() { +generateDSconfig() { for v in "$GLOBAL_BATCH" "$MICRO_BATCH" "$GRAD_ACC_STEPS" "$ZERO_STAGE" \ "$PP" "$DTYPE" do @@ -926,35 +921,35 @@ $flops_profiler EOT } -function printBlack() { +printBlack() { printf "\e[1;30m%s\e[0m\n" "$@" } -function printRed() { +printRed() { printf "\e[1;31m%s\e[0m\n" "$@" } -function printGreen() { +printGreen() { printf "\e[1;32m%s\e[0m\n" "$@" } -function printYellow() { +printYellow() { printf "\e[1;33m%s\e[0m\n" "$@" } -function printBlue() { +printBlue() { printf "\e[1;34m%s\e[0m\n" "$@" } -function printMagenta() { +printMagenta() { printf "\e[1;35m%s\e[0m\n" "$@" } -function printCyan() { +printCyan() { printf "\e[1;36m%s\e[0m\n" "$@" } -function printWhite() { +printWhite() { printf "\e[1;37m%s\e[0m\n" "$@" } From 3cd3f1a9a695341643dd29c87a47969de90a4812 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 24 May 2024 08:22:48 -0500 Subject: [PATCH 264/268] Update `train_aGPT_7B.sh` --- train_aGPT_7B.sh | 21 ++------------------- 1 file changed, 2 insertions(+), 19 deletions(-) diff --git a/train_aGPT_7B.sh b/train_aGPT_7B.sh index e5035ae27b..72322d655c 100644 --- a/train_aGPT_7B.sh +++ b/train_aGPT_7B.sh @@ -1,5 +1,5 @@ #!/bin/bash --login -# + NOW="$(date "+%Y-%m-%d-%H%M%S")" cd "${PBS_O_WORKDIR}" || exit @@ -7,30 +7,13 @@ cd "${PBS_O_WORKDIR}" || exit HOSTNAME=$(hostname) if [[ "${HOSTNAME}" == x3* ]]; then MACHINE="polaris" - # XXX: - # - On Polaris, we see that: - # - on 1 or 2 nodes, only MICRO_BATCH=1 will fit in memory - # - on 8 nodes, MICRO_BATCH=2 will fit in memory - # - on 48 nodes, MICRO_BATCH=4 will fit in memory - nhosts=$(wc -l < "${PBS_NODEFILE}") - if [[ "${nhosts}" == 1 ]]; then - export MBS=1 - elif [[ "${nhosts}" == 2 ]]; then - export MBS=1 - elif [[ "${nhosts}" -ge 3 ]]; then - export MBS=2 - elif [[ "${nhosts}" -ge 8 ]]; then - export MBS=4 - fi elif [[ "${HOSTNAME}" == x1* ]]; then MACHINE="sunspot" elif [[ "${HOSTNAME}" == x4* ]]; then MACHINE="aurora" fi -export nhosts -OUTDIR="${PBS_O_WORKDIR}/pbslogs" -mkdir -p "${OUTDIR}" +OUTDIR="${PBS_O_WORKDIR}/pbslogs" && mkdir -p "${OUTDIR}" OUTFILE="${OUTDIR}/${PBS_JOBID}-${NOW}.log" echo "+---------------------------------------------------------+" From bc1dbfdd7943b4513c9a167d934ae0e5e1d5e171 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Fri, 24 May 2024 13:59:39 -0500 Subject: [PATCH 265/268] Fix `--data-cache-path` in `ALCF/helpers.sh, train_llama_alcf.sh` --- ALCF/helpers.sh | 37 +++++++++++++++++++++++-------------- train_llama_alcf.sh | 5 +++-- 2 files changed, 26 insertions(+), 16 deletions(-) diff --git a/ALCF/helpers.sh b/ALCF/helpers.sh index a9af22416d..c0927766f2 100644 --- a/ALCF/helpers.sh +++ b/ALCF/helpers.sh @@ -135,12 +135,13 @@ loadCondaEnv() { setupLauncher() { # outdir=$1 - if [[ -n "${DIST_LAUNCH}" && ${LAUNCH_CMD:-"MPICH"} != "deepspeed" ]]; then - export LAUNCHER="${DIST_LAUNCH} --genvall --cpu-bind depth -d 16 $(which python3) -Wignore ${EXEC}" - else + if [[ "${LAUNCH_CMD:-"MPICH"}" == "deepspeed" ]]; then # Assert `./hostfile_deepspeed` exists export hfds="${WORKING_DIR}/hostfile_deepspeed" && [ -f "${hfds}" ] || exit export LAUNCHER="deepspeed --hostfile $hfds --launcher MPICH ${EXEC}" + # if [[ -n "${DIST_LAUNCH}" && ${LAUNCH_CMD:-"MPICH"} != "deepspeed" ]]; then + else + export LAUNCHER="${DIST_LAUNCH} --genvall --cpu-bind depth -d 16 $(which python3) -Wignore ${EXEC}" fi printf "Launching with: %s\n" "$(printRed "${LAUNCH_CMD}")" printf " %s" "$(printMagenta ${LAUNCHER})" @@ -390,21 +391,27 @@ saveDSenv() { } > .deepspeed_env } -setOutput() { + +get_output_prefix() { # ---- Specify output location -------------------------------- - OUTPUT_PREFIX="ws${WORLD_SIZE}_ds_stage${ZERO_STAGE}_nl${NLAYERS}" - OUTPUT_PREFIX="${OUTPUT_PREFIX}_hs${HIDDEN}_mb${MICRO_BATCH}" - OUTPUT_PREFIX="${OUTPUT_PREFIX}_seq${SEQ}_gb${GLOBAL_BATCH}" - OUTPUT_PREFIX="${OUTPUT_PREFIX}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" - OUTPUT_PREFIX="${OUTPUT_PREFIX}_lr${LR}_lwf${LR_WARMUP_FRAC}" + pre="ws${WORLD_SIZE}_ds_stage${ZERO_STAGE}_nl${NLAYERS}" + pre="${pre}_hs${HIDDEN}_mb${MICRO_BATCH}" + pre="${pre}_seq${SEQ}_gb${GLOBAL_BATCH}" + pre="${pre}_pp${PP}_tp${TP}_${DTYPE}_opt${OPT}" + pre="${pre}_lr${LR}_lwf${LR_WARMUP_FRAC}" if [[ -n "${LR_DECAY_ITERS}" ]]; then - OUTPUT_PREFIX="${OUTPUT_PREFIX}_ldi${LR_DECAY_ITERS}" + pre="${pre}_ldi${LR_DECAY_ITERS}" fi if [[ -z "${NO_FLASH_ATTN:-}" ]]; then - OUTPUT_PREFIX="${OUTPUT_PREFIX}_flash" + pre="${pre}_flash" fi - export OUTPUT_PREFIX="${OUTPUT_PREFIX}" + export OUTPUT_PREFIX="${pre}" + echo "${pre}" +} + +setOutput() { # OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%m%d%H%M%S)_${HOSTNAME}" + OUTPUT_PREFIX=$(get_output_prefix) OUTPUT_DIR="logs/${OUTPUT_PREFIX}/$(date +%Y%m%d-%H%M%S)_${WORLD_SIZE}_${HOSTNAME}" export OUTPUT_DIR="${OUTPUT_DIR}" export OUTPUT_LOG="${OUTPUT_DIR}/output.log" @@ -665,7 +672,7 @@ setup_tokenizer_and_data() { export TOKENIZER_TYPE="Llama2" tm="${WORKING_DIR}/ALCF/tokenizer.model" # fallback: Megatron-DeepSpeed/ALCF/tokenizer.model export TOKENIZER_MODEL="${TOKENIZER_MODEL:-${tm}}" # USE TOKENIZER_MODEL from env, else fallback from ^ - export TOKENIZER_FLAGS="${TOKENIZER_FLAGS} --tokenizer-type Llama2Tokenizer --tokenizer-model ${TOKENIZER_MODEL}" + export TOKENIZER_FLAGS="--tokenizer-type Llama2Tokenizer --tokenizer-model ${TOKENIZER_MODEL}" if [[ "${TOKENIZER_TYPE}" != "GPT2" ]]; then echo "Using tokenizer: ${TOKENIZER_TYPE}. Setting up data with ${DATA_FILE_LIST-}" setData "${dfl}" || exit @@ -737,13 +744,14 @@ setData() { # ------------------------[dfl: abbrv. for DATA_FILE_LIST] ndocs=$(wc -l < "${dfl}") ws=$(sumWeights "${dfl}") dfl_stem=$(echo "${dfl}" | tr "\/" "\t" | awk '{print $NF}' | sed "s/\.txt//g") + # dcp="${OUTPUT_PREFIX:-$(get_output_prefix)}/.cache/${dfl_stem}/index-cache" dcp=".cache/${dfl_stem}/index-cache" export DATA_FILE_LIST="${dfl}" export NUM_DOCS="${ndocs}" export WEIGHT_SUM="${ws}" export DFL_STEM="${dfl_stem}" export DATA_CACHE_PATH="${dcp}" - export DATA_FLAGS="${DATA_FLAGS} --data-file-list ${DATA_FILE_LIST} --data-cache-path ${DATA_CACHE_PATH}" + export DATA_FLAGS="${DATA_FLAGS} --data-file-list ${DATA_FILE_LIST}" # --data-cache-path ${DATA_CACHE_PATH}" echo "--------------------" echo "Updated environment:" printf "DATA_FILE_LIST: %s\n" "${DATA_FILE_LIST}" @@ -751,6 +759,7 @@ setData() { # ------------------------[dfl: abbrv. for DATA_FILE_LIST] printf "WEIGHT_SUM: %s\n" "${WEIGHT_SUM}" printf "DFL_STEM: %s\n" "${DFL_STEM}" printf "DATA_CACHE_PATH: %s\n" "${DATA_CACHE_PATH}" + printf "DATA_FLAGS: %s\n" "${DATA_FLAGS}" echo "--------------------" # fi # export DATA_FLAGS="${DATA_FLAGS}" diff --git a/train_llama_alcf.sh b/train_llama_alcf.sh index 9a6d39923c..bf346e2144 100644 --- a/train_llama_alcf.sh +++ b/train_llama_alcf.sh @@ -95,6 +95,7 @@ TBDIR="${CKPT_DIR}/tensorboard" mkdir -p "${TBDIR}" data_cache_path="${CKPT_DIR}/${DATA_CACHE_PATH}" && mkdir -p "${data_cache_path}" +echo "Using data_cache_path: ${data_cache_path}" export DEFAULTS="\ @@ -116,7 +117,6 @@ custom_args=" $@" # --log-memory-to-tensorboard \ # --data-file-list ${DATA_FILE_LIST} \ # --data-file-list ${DATA_FILE_LIST} \ - # --data-cache-path ${data_cache_path} \ # --tokenizer-type Llama2Tokenizer \ # --tokenizer-model ${TOKENIZER_MODEL} \ run_cmd=" @@ -143,10 +143,11 @@ run_cmd=" --pipeline-model-parallel-size ${PP} \ --num-key-value-heads ${NUM_KV_HEAD} \ --ffn-hidden-size ${FFN_HIDDEN_SIZE} \ + --data-cache-path ${data_cache_path} \ + ${DATA_FLAGS} \ ${LR_ARGS} \ ${LLAMA_ARGS} \ ${TIMING_STR} \ - ${DATA_FLAGS} \ ${TOKENIZER_FLAGS} \ $ds_args \ ${gpt_args[*]} \ From c3a4451f646b3ef17a1a8f2d371ae159974c4ca3 Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 25 May 2024 11:21:00 -0500 Subject: [PATCH 266/268] Add `ALCF/sunspot-env-2024-04-15-002.sh` --- ALCF/sunspot-env-2024-04-15-002.sh | 4 ++++ 1 file changed, 4 insertions(+) create mode 100644 ALCF/sunspot-env-2024-04-15-002.sh diff --git a/ALCF/sunspot-env-2024-04-15-002.sh b/ALCF/sunspot-env-2024-04-15-002.sh new file mode 100644 index 0000000000..3b7155675d --- /dev/null +++ b/ALCF/sunspot-env-2024-04-15-002.sh @@ -0,0 +1,4 @@ +#!/bin/bash --login + +module use /soft/preview-modulefiles/24.086.0 +module load frameworks/2024.04.15.002.lua From 0fc3919d1587adc3b13b4afe2f9e1b90cbd6874f Mon Sep 17 00:00:00 2001 From: Sam Foreman Date: Sat, 25 May 2024 11:22:03 -0500 Subject: [PATCH 267/268] Update `train_aGPT_7B.sh` --- train_aGPT_7B.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/train_aGPT_7B.sh b/train_aGPT_7B.sh index 72322d655c..9dc0f1d946 100644 --- a/train_aGPT_7B.sh +++ b/train_aGPT_7B.sh @@ -25,6 +25,6 @@ echo "+---------------------------------------------------------+" export TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC=6000 echo "${OUTFILE}" >> "${OUTDIR}/latest" # export DEBUG=1 -export MICRO_BATCH="${MICRO_BATCH:-${MBS}}" +# export MICRO_BATCH="${MICRO_BATCH:-${MBS}}" export DATA_FILE_LIST="${DATA_FILE_LIST:-${PBS_O_WORKDIR}/ALCF/data-lists/${MACHINE}/dolma_v1_7_file_list.txt}" bash "${PBS_O_WORKDIR}/train_llama_alcf.sh" |& tee "${OUTFILE}" From 2b5b41f7acb8bb685e7e7f794af12ef6af317674 Mon Sep 17 00:00:00 2001 From: Varuni Sastry <88804132+vksastry@users.noreply.github.com> Date: Thu, 30 May 2024 22:29:53 -0500 Subject: [PATCH 268/268] convert MDS checkpoint to Hf Llama model --- ALCF/mds_to_hf.py | 91 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 91 insertions(+) create mode 100644 ALCF/mds_to_hf.py diff --git a/ALCF/mds_to_hf.py b/ALCF/mds_to_hf.py new file mode 100644 index 0000000000..a336788274 --- /dev/null +++ b/ALCF/mds_to_hf.py @@ -0,0 +1,91 @@ +# Usage : python mds_to_hf.py --mds_checkpoint --output_dir +# Tips : Do not run on login node. +# This script currently only takes care of tp=1. Takes a AuroraGPT Llama model trained with Megatron-DeepSpeed and converts to LLamaCausalForLM architecture from HuggingFace. + +import argparse +import torch +import pdb +import os +from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer + +def repeat_kv_wt(x,np): + return torch.repeat_interleave(x, dim=0, repeats=np) + +def Update_llama_config(Llama_config, mds_args): + if mds_args['swiglu']: + Llama_config.hidden_act = "silu" + Llama_config.hidden_size = mds_args['hidden_size'] + Llama_config.intermediate_size = mds_args['ffn_hidden_size'] + Llama_config.max_position_embeddings = mds_args['max_position_embeddings'] + Llama_config.num_attention_heads = mds_args['num_attention_heads'] + Llama_config.num_hidden_layers = mds_args['num_layers'] + Llama_config.num_key_value_heads = mds_args['num_key_value_heads'] + Llama_config.rms_norm_eps = mds_args['layernorm_epsilon'] + Llama_config.rope_theta = mds_args['rope_theta'] + Llama_config.vocab_size = mds_args['padded_vocab_size'] + return Llama_config + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument('--mds_checkpoint', required=True) + parser.add_argument('--output_dir', required=True) + args = parser.parse_args() + + # make output_dir if it does not exits. + if not os.path.exists(args.output_dir): + os.makedirs(args.output_dir) + + filename = str(args.mds_checkpoint) + if not filename.split("/")[-1].startswith('mp_rank') and not filename.split("/")[-1].endswith('.pt'): + assert ("Provide the right file path, The file should be of format mp_rank_*.pt") + print(f"loading mds checkpoint {filename}") + + mds_model = torch.load(args.mds_checkpoint,map_location=torch.device('cpu')) + Llama_model = LlamaForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf",cache_dir='/eagle/datascience/vsastry/huggingface') + + Llama_config = Llama_model.config + Updated_Llama_config = Update_llama_config(Llama_config, mds_model['args'].__dict__) + # save the updated config.json file + Updated_Llama_config.to_json_file(os.path.join(args.output_dir,'config.json')) + + state_dict = {} + dim = mds_model['args'].__dict__['kv_channels'] + inv_freq = 1.0 / (mds_model['args'].__dict__['rope_theta'] ** (torch.arange(0,dim, 2).float() / dim)) + hidden_size = mds_model['args'].__dict__['hidden_size'] + kv_dim = mds_model['args'].__dict__['kv_channels'] * mds_model['args'].__dict__['num_key_value_heads'] + kv_groups = mds_model['args'].__dict__['num_attention_heads'] // mds_model['args'].__dict__['num_key_value_heads'] + for layer_i in range(Updated_Llama_config.__dict__['num_hidden_layers']): + # SELF ATTENTION layers. + # get the q, k, v weights separately. Keeping k and v at the GQA head dim, since the transformers/models/llama/modelling_utils will take care of it. + fused_qkv = mds_model['module']['language_model']['encoder'][f"layers.{layer_i}.self_attention.query_key_value.weight"] + state_dict[f"model.layers.{layer_i}.self_attn.q_proj.weight"] = fused_qkv[0:hidden_size] + state_dict[f"model.layers.{layer_i}.self_attn.k_proj.weight"] = fused_qkv[hidden_size:hidden_size+kv_dim] + #state_dict[f"model.layers.{layer_i}.self_attn.k_proj.weight"] = repeat_kv_wt(fused_qkv[hidden_size:hidden_size+kv_dim], kv_groups) + state_dict[f"model.layers.{layer_i}.self_attn.v_proj.weight"] = fused_qkv[hidden_size+kv_dim:hidden_size+2*kv_dim] + #state_dict[f"model.layers.{layer_i}.self_attn.v_proj.weight"] = repeat_kv_wt(fused_qkv[hidden_size+kv_dim:hidden_size+2*kv_dim],kv_groups) + state_dict[f"model.layers.{layer_i}.self_attn.o_proj.weight"] = mds_model['module']['language_model']['encoder'][f"layers.{layer_i}.self_attention.dense.weight"] + + # MLP Layers + fused_mlp = mds_model['module']['language_model']['encoder'][f"layers.{layer_i}.mlp.dense_h_to_4h.weight"] + chunked_mlp = torch.chunk(fused_mlp,2,dim=0) + state_dict[f"model.layers.{layer_i}.mlp.gate_proj.weight"] = chunked_mlp[0] + state_dict[f"model.layers.{layer_i}.mlp.up_proj.weight"] = chunked_mlp[1] + state_dict[f"model.layers.{layer_i}.mlp.down_proj.weight"] = mds_model['module']['language_model']['encoder'][f"layers.{layer_i}.mlp.dense_4h_to_h.weight"] + + #LayerNorm weights and RoPe + state_dict[f"model.layers.{layer_i}.input_layernorm.weight"] = mds_model['module']['language_model']['encoder'][f"layers.{layer_i}.input_layernorm.weight"] + state_dict[f"model.layers.{layer_i}.post_attention_layernorm.weight"] = mds_model['module']['language_model']['encoder'][f"layers.{layer_i}.post_attention_layernorm.weight"] + + state_dict[f"model.layers.{layer_i}.self_attn.rotary_emb.inv_freq"] = inv_freq + + # Get the non-encoder layer weights. + state_dict["model.embed_tokens.weight"] = mds_model['module']['language_model']['embedding']['word_embeddings']['weight'] + state_dict["model.norm.weight"] = mds_model['module']['language_model']['encoder']['final_layernorm.weight'] + state_dict["lm_head.weight"] = mds_model['module']['language_model']['output_layer']['weight'] + + # Save the model in the hf output path. + torch.save(state_dict, os.path.join(args.output_dir,"pytorch_model.bin")) + + +