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Clone https://github.com/mlcommons/algorithmic-efficiency.git #52

Clone https://github.com/mlcommons/algorithmic-efficiency.git

Clone https://github.com/mlcommons/algorithmic-efficiency.git #52

name: Release TorchBench Userbenchmark on A100
on:
pull_request:
paths:
- userbenchmark/release-test/*
jobs:
run-userbenchmark:
runs-on: [linux.aws.a100]
timeout-minutes: 1440 # 24 hours
environment: docker-s3-upload
env:
BASE_CONDA_ENV: "torchbench"
CONDA_ENV: "userbenchmark-a100"
PLATFORM_NAME: "gcp_a100"
SETUP_SCRIPT: "/workspace/setup_instance.sh"
steps:
- name: Checkout TorchBench
uses: actions/checkout@v3
with:
path: benchmark
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
- name: Tune Nvidia GPU
run: |
sudo nvidia-smi -pm 1
sudo nvidia-smi -ac 1215,1410
nvidia-smi
- name: Clone and setup conda env
run: |
CONDA_ENV=${BASE_CONDA_ENV} . "${SETUP_SCRIPT}"
conda create --name "${CONDA_ENV}" --clone "${BASE_CONDA_ENV}"
- name: Install TorchBench
run: |
set -x
. "${SETUP_SCRIPT}"
pushd benchmark
python install.py
- name: Run user benchmark
run: |
set -x
. "${SETUP_SCRIPT}"
# remove old results
if [ -d benchmark-output ]; then rm -Rf benchmark-output; fi
pushd benchmark
# Install necessary packages <-- Added these lines
pip3 install -e '.[jax_cpu]'
pip3 install -e '.[pytorch_gpu]' -f 'https://download.pytorch.org/whl/cu121'
pip3 install -e '.[full]'
release_version=$(cat userbenchmark/release-test/version.txt)
if [ -d .userbenchmark ]; then rm -Rf .userbenchmark; fi
python run_benchmark.py release-test -c ${release_version}
cp -r ./.userbenchmark/release-test ../benchmark-output
- name: Upload artifact
uses: actions/upload-artifact@v3
with:
name: TorchBench result
path: benchmark-output/
- name: Clean up Conda env
if: always()
run: |
. "${SETUP_SCRIPT}"
conda deactivate && conda deactivate
conda remove -n "${CONDA_ENV}" --all