Use generator args to group arguments to generator #648
Workflow file for this run
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| name: Compile main | |
| on: | |
| push: | |
| branches: | |
| - main | |
| pull_request: | |
| workflow_dispatch: | |
| jobs: | |
| run-tinystories: | |
| strategy: | |
| matrix: | |
| runner: [32-core-ubuntu] | |
| runs-on: ${{matrix.runner}} | |
| steps: | |
| - name: Checkout repo | |
| uses: actions/checkout@v2 | |
| - name: Setup Python | |
| uses: actions/setup-python@v2 | |
| with: | |
| python-version: 3.11 | |
| - name: Print machine info | |
| run: | | |
| uname -a | |
| if [ $(uname -s) == Darwin ]; then | |
| sysctl machdep.cpu.brand_string | |
| sysctl machdep.cpu.core_count | |
| fi | |
| - name: Install requirements | |
| run: | | |
| echo "Intalling pip packages" | |
| pip install wheel | |
| pip install cmake | |
| pip install ninja | |
| pip install zstd | |
| pip install -r requirements.txt | |
| echo "Executorch: cloning" | |
| mkdir etorch | |
| cd etorch | |
| git clone https://github.com/pytorch/executorch.git | |
| cd executorch | |
| echo "Inside: ${PWD}" | |
| echo "Executorch: submodule update" | |
| git submodule sync | |
| git submodule update --init | |
| echo "Executorch: installing python interface" | |
| ./install_requirements.sh --pybind xnnpack | |
| cd ../.. | |
| echo "Inside: ${PWD}" | |
| - name: Download checkpoints | |
| run: | | |
| mkdir -p checkpoints/stories15M | |
| pushd checkpoints/stories15M | |
| wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories15M.pt | |
| wget https://github.com/karpathy/llama2.c/raw/master/tokenizer.model | |
| wget https://github.com/karpathy/llama2.c/raw/master/tokenizer.bin | |
| popd | |
| - name: Run inference | |
| run: | | |
| export MODEL_PATH=${PWD}/checkpoints/stories15M/stories15M.pt | |
| export MODEL_NAME=stories15M | |
| python generate.py --checkpoint-path ${MODEL_PATH} --temperature 0 > ${PWD}/output_eager | |
| cat ${PWD}/output_eager | |
| python export.py --checkpoint-path ${MODEL_PATH} --output-pte-path ${PWD}/${MODEL_NAME}.pte | |
| python generate.py --checkpoint-path ${MODEL_PATH} --temperature 0 --pte-path ${PWD}/${MODEL_NAME}.pte > ${PWD}/output_et | |
| cat ${PWD}/output_et | |
| echo "Tests complete." | |
| - name: Run inference | |
| run: | | |
| export MODEL_PATH=checkpoints/stories15M/stories15M.pt | |
| export MODEL_NAME=stories15M | |
| export MODEL_DIR=/tmp | |
| python export.py --checkpoint-path ${MODEL_PATH} --output-pte-path ${MODEL_DIR}/${MODEL_NAME}.pte | |
| python generate.py --checkpoint-path ${MODEL_PATH} --temperature 0 --pte-path ${MODEL_DIR}/${MODEL_NAME}.pte > ./output_et | |
| cat ./output_et | |
| echo "******************************************" | |
| echo "******* Emb: channel-wise quantized ******" | |
| echo "******************************************" | |
| python export.py --quant '{"embedding" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --output-pte-path ${MODEL_DIR}/${MODEL_NAME}.pte | |
| python generate.py --checkpoint-path ${MODEL_PATH} --temperature 0 --pte-path ${MODEL_DIR}/${MODEL_NAME}.pte > ./output_et | |
| cat ./output_et | |
| echo "******************************************" | |
| echo "******** Emb: group-wise quantized *******" | |
| echo "******************************************" | |
| python export.py --quant '{"embedding" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --output-pte-path ${MODEL_DIR}/${MODEL_NAME}.pte | |
| python generate.py --checkpoint-path ${MODEL_PATH} --temperature 0 --pte-path ${MODEL_DIR}/${MODEL_NAME}.pte > ./output_et | |
| cat ./output_et | |
| echo "******************************************" | |
| echo "******* INT8 channel-wise quantized ******" | |
| echo "******************************************" | |
| python export.py --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --output-pte-path ${MODEL_DIR}/${MODEL_NAME}.pte | |
| python generate.py --checkpoint-path ${MODEL_PATH} --temperature 0 --pte-path ${MODEL_DIR}/${MODEL_NAME}.pte > ./output_et | |
| cat ./output_et | |
| echo "******************************************" | |
| echo "******** INT8 group-wise quantized *******" | |
| echo "******************************************" | |
| python export.py --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --output-pte-path ${MODEL_DIR}/${MODEL_NAME}.pte | |
| python generate.py --checkpoint-path ${MODEL_PATH} --temperature 0 --pte-path ${MODEL_DIR}/${MODEL_NAME}.pte > ./output_et | |
| cat ./output_et | |
| echo "******************************************" | |
| echo "******** INT4 group-wise quantized *******" | |
| echo "******************************************" | |
| python export.py --quant '{"linear:int4" : {"groupsize": 32}}' --checkpoint-path ${MODEL_PATH} --output-pte-path ${MODEL_DIR}/${MODEL_NAME}.pte | |
| python generate.py --checkpoint-path ${MODEL_PATH} --temperature 0 --pte-path ${MODEL_DIR}/${MODEL_NAME}.pte > ./output_et | |
| cat ./output_et | |
| echo "tests complete" | |
| echo "******************************************" | |