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Create top-level torchchat.py CLI binary #545

Create top-level torchchat.py CLI binary

Create top-level torchchat.py CLI binary #545

Workflow file for this run

name: Run compile tests
on:
pull_request:
push:
branches:
- main
workflow_dispatch:
jobs:
test-cuda:
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
with:
runner: linux.g5.4xlarge.nvidia.gpu
gpu-arch-type: cuda
gpu-arch-version: "12.1"
script: |
echo "::group::Print machine info"
uname -a
if [ $(uname -s) == Darwin ]; then
sysctl machdep.cpu.brand_string
sysctl machdep.cpu.core_count
fi
echo "::endgroup::"
echo "::group::Download checkpoints"
# Install requirements
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu121
pip install -r requirements.txt
echo "::endgroup::"
echo "::group::Download checkpoints"
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
echo "::endgroup::"
echo "::group::Run inference"
export MODEL_PATH=checkpoints/stories15M/stories15M.pt
export MODEL_NAME=stories15M
export MODEL_DIR=/tmp
python generate.py --device cuda --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_eager
cat ./output_eager
python generate.py --device cuda --compile --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_compiled
cat ./output_compiled
python export.py --device cuda --checkpoint-path ${MODEL_PATH} --output-dso-path ${MODEL_DIR}/${MODEL_NAME}.so
python generate.py --device cuda --checkpoint-path ${MODEL_PATH} --temperature 0 --dso-path ${MODEL_DIR}/${MODEL_NAME}.so > ./output_aoti
cat ./output_aoti
echo "******************************************"
echo "******* Emb: channel-wise quantized ******"
echo "******************************************"
python generate.py --device cuda --quant '{"embedding" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_eager
cat ./output_eager
python generate.py --device cuda --compile --quant '{"embedding" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_compiled
cat ./output_compiled
python export.py --device cuda --quant '{"embedding" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --output-dso-path ${MODEL_DIR}/${MODEL_NAME}.so
python generate.py --device cuda --checkpoint-path ${MODEL_PATH} --temperature 0 --dso-path ${MODEL_DIR}/${MODEL_NAME}.so > ./output_aoti
cat ./output_aoti
echo "******************************************"
echo "******** Emb: group-wise quantized *******"
echo "******************************************"
python generate.py --device cuda --quant '{"embedding" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_eager
cat ./output_eager
python generate.py --device cuda --compile --quant '{"embedding" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_compiled
cat ./output_compiled
python export.py --device cuda --quant '{"embedding" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --output-dso-path ${MODEL_DIR}/${MODEL_NAME}.so
python generate.py --device cuda --checkpoint-path ${MODEL_PATH} --temperature 0 --dso-path ${MODEL_DIR}/${MODEL_NAME}.so > ./output_aoti
cat ./output_aoti
echo "******************************************"
echo "******* INT8 channel-wise quantized ******"
echo "******************************************"
python generate.py --device cuda --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_eager
cat ./output_eager
python generate.py --device cuda --compile --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_compiled
cat ./output_compiled
python export.py --device cuda --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --output-dso-path ${MODEL_DIR}/${MODEL_NAME}.so
python generate.py --device cuda --checkpoint-path ${MODEL_PATH} --temperature 0 --dso-path ${MODEL_DIR}/${MODEL_NAME}.so > ./output_aoti
cat ./output_aoti
echo "******************************************"
echo "******** INT8 group-wise quantized *******"
echo "******************************************"
python generate.py --device cuda --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_eager
cat ./output_eager
python generate.py --device cuda --compile --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_compiled
cat ./output_compiled
python export.py --device cuda --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --output-dso-path ${MODEL_DIR}/${MODEL_NAME}.so
python generate.py --device cuda --checkpoint-path ${MODEL_PATH} --temperature 0 --dso-path ${MODEL_DIR}/${MODEL_NAME}.so > ./output_aoti
cat ./output_aoti
echo "******************************************"
echo "******** INT4 group-wise quantized *******"
echo "******************************************"
python generate.py --device cuda --quant '{"linear:int4" : {"groupsize": 32}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_eager
cat ./output_eager
python generate.py --device cuda --compile --quant '{"linear:int4" : {"groupsize": 32}}' --checkpoint-path ${MODEL_PATH} --temperature 0 > ./output_compiled
cat ./output_compiled
python export.py --device cuda --quant '{"linear:int4" : {"groupsize": 32}}' --checkpoint-path ${MODEL_PATH} --output-dso-path ${MODEL_DIR}/${MODEL_NAME}.so
python generate.py --device cuda --checkpoint-path ${MODEL_PATH} --temperature 0 --dso-path ${MODEL_DIR}/${MODEL_NAME}.so > ./output_aoti
cat ./output_aoti
echo "tests complete"
echo "******************************************"
echo "::endgroup::"