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Merge pull request #31 from YerevaNN/minor_changes_for_run
Minor changes for run
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,133 @@ | ||
| import sys | ||
| from contextlib import contextmanager | ||
| from datetime import datetime | ||
| import submitit | ||
|
|
||
| use_accelerate = False | ||
| rsync_enabled = False | ||
| executor_name = "slurm" # options are ["slurm", "local"] | ||
| root_path = "" | ||
| num_gpus = 1 | ||
| # model_name = "gemma" | ||
| # model_size = "2b" | ||
| model_name = "galactica" | ||
| model_size = "125m" | ||
| train_type = "sft" | ||
| train_name = "_".join([model_name, model_size, train_type]) | ||
| job_name = "HLM_chem_3wu_32bs_15ep_1e4_nef20" | ||
|
|
||
| slurm_params = { | ||
| "slurm_job_name": job_name, | ||
| "timeout_min": 60 * 3, | ||
| "nodes": 1, | ||
| "tasks_per_node": 1, | ||
| "gpus_per_node": num_gpus, | ||
| "cpus_per_task": num_gpus * 8, | ||
| "mem_gb": num_gpus * 40.0 + 20.0, | ||
| "stderr_to_stdout": True, | ||
| } | ||
|
|
||
| accelerate_config = {"num_processes": num_gpus} | ||
|
|
||
| env_variables = { | ||
| "TOKENIZERS_PARALLELISM": "true", | ||
| "CUDA_VISIBLE_DEVICES": "0, 1, 2, 3, 4, 5, 6, 7", | ||
| # "CUDA_VISIBLE_DEVICES": "3", | ||
| } | ||
|
|
||
| cli_arguments = { | ||
| "train_type": train_type, | ||
| # "from_pretrained": "/nfs/dgx/raid/chem/checkpoints/facebook/"\ | ||
| # "galactica-125m/9954e52e400b43d18d3a40f6/checkpoint-20480", | ||
| # "from_pretrained": "/nfs/dgx/raid/chem/checkpoints/facebook/"\ | ||
| # "galactica-125m/1f289ff103034364bd27e1c3/checkpoint-18000/", | ||
| # "from_pretrained": "/nfs/dgx/raid/chem/checkpoints/google/"\ | ||
| # "gemma-2b/d6e6a76e91814ad68d5fa264/checkpoint-11000", | ||
| # "from_pretrained": "/nfs/dgx/raid/chem/checkpoints/h100/"\ | ||
| # "google/gemma-2b/0717d445bcf44e31b2887892/checkpoint-12000", | ||
| "from_pretrained": "/nfs/dgx/raid/chem/checkpoints/h100/" | ||
| "google/gemma-2b/0717d445bcf44e31b2887892/checkpoint-18000", | ||
| "model_config": train_name, | ||
| "dir_data_types": "computed", | ||
| "training_data_dirs": "/auto/home/menuab/code/sft_data/ADME_HLM", | ||
| "valid_data_dir": "", | ||
| # "max_steps":120000, | ||
| "num_train_epochs": 15, | ||
| "learning_rate": 0.0001, | ||
| "warmup": 180, | ||
| "eval_steps": 60, | ||
| "save_steps": 2440, | ||
| "train_batch_size": 32, | ||
| "valid_batch_size": 32, | ||
| "dataloader_num_workers": 1, | ||
| "experiment_name": job_name, | ||
| "checkpoints_root_dir": "/nfs/dgx/raid/chem/checkpoints/", | ||
| "flash_attn": False, | ||
| "track": True, | ||
| "track_dir": "/nfs/dgx/raid/chem/aim/", | ||
| # "profile":, | ||
| # "profile_dir":, | ||
| # "gradient_accumulation_steps":, | ||
| # "gradient_checkpointing":, | ||
| # "evaluate_only":, | ||
| # "check_reproducability":, | ||
| } | ||
|
|
||
|
|
||
| def get_command(use_accelerate): | ||
| python_executable = sys.executable | ||
| command = [python_executable] | ||
| if use_accelerate: | ||
| accelerate_path = "chemlactica/config/accelerate_config.yaml" | ||
| command.extend( | ||
| f"-m accelerate.commands.launch --config_file {accelerate_path}".split(" ") | ||
| ) | ||
| for k, v in accelerate_config.items(): | ||
| command.append(f"--{k}={v}") | ||
| command.append("chemlactica/train.py") | ||
| for x, y in cli_arguments.items(): | ||
| if isinstance(y, bool): | ||
| if y: | ||
| command.append(f"--{x}") | ||
| else: | ||
| command.append(f"--{x}={y}") | ||
|
|
||
| print(f'command being executed: {" ".join(command)}') | ||
| return command | ||
|
|
||
|
|
||
| @contextmanager | ||
| def conditional_context_manager(rsync_enabled, repo_path): | ||
| if rsync_enabled: | ||
| with submitit.helpers.RsyncSnapshot(repo_path) as cm: | ||
| yield cm | ||
| else: | ||
| yield None | ||
|
|
||
|
|
||
| def get_executor(executor_name, logs_path): | ||
| if executor_name == "slurm": | ||
| executor = submitit.AutoExecutor(folder=logs_path) | ||
| elif executor_name == "local": | ||
| executor = submitit.local.local.LocalExecutor(folder=logs_path) | ||
| return executor | ||
|
|
||
|
|
||
| if __name__ == "__main__": | ||
| logs_path = "submitit_logs/%j" | ||
| logs_path = "/nfs/dgx/raid/chem/" + logs_path if rsync_enabled else logs_path | ||
| repo_path = ( | ||
| "/nfs/dgx/raid/chem/rsyncsnapshots/" | ||
| f"{train_name}-{datetime.now().strftime('%Y-%m-%d-%H:%M')}" | ||
| ) | ||
|
|
||
| with conditional_context_manager(rsync_enabled, repo_path): | ||
| command = get_command(use_accelerate) | ||
| executor = get_executor(executor_name, logs_path) | ||
| executor.update_parameters(**slurm_params) | ||
| print("train_name: ", train_name) | ||
| print("logs_path: ", logs_path) | ||
| print("repo path: ", repo_path) | ||
| function = submitit.helpers.CommandFunction(command, env=env_variables) | ||
| job = executor.submit(function) | ||
| # print(job.result()) |
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