Integrate distributed inference with chat/server #2406
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.yml@main | |
| with: | |
| runner: linux.g5.4xlarge.nvidia.gpu | |
| gpu-arch-type: cuda | |
| gpu-arch-version: "12.1" | |
| timeout: 60 | |
| script: | | |
| echo "::group::Print machine info" | |
| uname -a | |
| echo "::endgroup::" | |
| echo "::group::Install newer objcopy that supports --set-section-alignment" | |
| yum install -y devtoolset-10-binutils | |
| export PATH=/opt/rh/devtoolset-10/root/usr/bin/:$PATH | |
| 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::" |