bandaid for run-readme-pr-macos.yml incorrectly loading to MPS #2579
Workflow file for this run
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name: Run parallel prefill | |
on: | |
pull_request: | |
push: | |
branches: | |
- main | |
workflow_dispatch: | |
jobs: | |
test-cuda: | |
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main | |
with: | |
runner: linux.g5.4xlarge.nvidia.gpu | |
gpu-arch-type: cuda | |
gpu-arch-version: "12.4" | |
timeout: 60 | |
script: | | |
echo "::group::Print machine info" | |
uname -a | |
echo "::endgroup::" | |
echo "::group::Download checkpoints" | |
# Install requirements | |
./install/install_requirements.sh cuda | |
pip3 list | |
python3 -c 'import torch;print(f"torch: {torch.__version__, torch.version.git_version}")' | |
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 | |
for DTYPE in bfloat16 float16 float32; do | |
################################################################### | |
# group with different temperatures | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 0 | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 0.9 | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 1.0 | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 100 | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 200 | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 500 | |
################################################################### | |
# group with different temperatures and prefill, and compile | |
# and prefill compile | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 0 --compile --compile-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 0.9 --compile --compile-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 1.0 --compile --compile-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 100 --compile --compile-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 200 --compile --compile-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 500 --compile --compile-prefill | |
################################################################### | |
# group with different temperatures and sequential prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 0 --sequential-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 0.9 --sequential-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 1.0 --sequential-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 100 --sequential-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 200 --sequential-prefill | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 500 --sequential-prefill | |
################################################################### | |
# group with different temperatures and prefill, and compile | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 0 --sequential-prefill --compile | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 0.9 --sequential-prefill --compile | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --temperature 1.0 --sequential-prefill --compile | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 100 --sequential-prefill --compile | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 200 --sequential-prefill --compile | |
python torchchat.py generate --checkpoint-path ${MODEL_PATH} --device cpu --dtype ${DTYPE} --top-k 500 --sequential-prefill --compile | |
done | |
echo "tests complete" | |
echo "******************************************" | |
echo "::endgroup::" |