initial hqq #3
Workflow file for this run
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name: Compile main | |
on: | |
push: | |
branches: | |
- main | |
pull_request: | |
workflow_dispatch: | |
jobs: | |
run-hqq-tinystories: | |
strategy: | |
matrix: | |
runner: [ubuntu-latest] | |
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: | | |
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu | |
pip install -r requirements.txt | |
pip install hqq | |
- 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 | |
popd | |
- name: Run inference | |
run: | | |
export MODEL_PATH=checkpoints/stories15M/stories15M.pt | |
export MODEL_NAME=stories15M | |
export MODEL_DIR=/tmp | |
echo "******************************************" | |
echo "******** HQQ: group-wise quantized *******" | |
echo "******************************************" | |
python generate.py --quant '{"linear:hqq" : {"group_size": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_eager | |
cat ./output_eager | |
python generate.py --compile --quant '{"linear:hqq" : {"group_size": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_compiled | |
cat ./output_compiled | |
python export.py --quant '{"embedding" : {"group_size": 8}}' --checkpoint-path ${MODEL_PATH} --output-dso-path ${MODEL_DIR}/${MODEL_NAME}.so | |
python generate.py --checkpoint-path ${MODEL_PATH} --temperature 0 --dso-path ${MODEL_DIR}/${MODEL_NAME}.so > ./output_aoti | |
cat ./output_aoti | |
echo "tests complete" | |
echo "******************************************" |