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Added torchao nightly workflow #10

Added torchao nightly workflow

Added torchao nightly workflow #10

Workflow file for this run

name: Torchao nightly workflow (A100)
on:
workflow_dispatch:
# TODO: REMOVE THIS BEFORE THE PR IS MERGED!
pull_request:
jobs:
run-benchmark:
environment: docker-s3-upload
env:
BASE_CONDA_ENV: "torchbench"
CONDA_ENV: "torchao-nightly"
PLATFORM_NAME: "gcp_a100"
SETUP_SCRIPT: "/workspace/setup_instance.sh"
TORCHBENCH_USERBENCHMARK_SCRIBE_GRAPHQL_ACCESS_TOKEN: ${{ secrets.TORCHBENCH_USERBENCHMARK_SCRIBE_GRAPHQL_ACCESS_TOKEN }}
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
IS_GHA: 1
BUILD_ENVIRONMENT: benchmark-nightly
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: [a100-runner]
steps:
- name: Checkout TorchBench
uses: actions/checkout@v3
with:
path: benchmark
- name: Tune Nvidia GPU
run: |
sudo nvidia-smi -pm 1
sudo nvidia-smi -ac 1215,1410
nvidia-smi
- name: Clone and setup conda env
run: |
CONDA_ENV=${BASE_CONDA_ENV} . "${SETUP_SCRIPT}"
conda create --name "${CONDA_ENV}" --clone "${BASE_CONDA_ENV}"
- name: Run the torchao userbenchmark
run: |
. "${SETUP_SCRIPT}"
# remove old results if exists
if [ -d benchmark-output ]; then rm -Rf benchmark-output; fi
pushd benchmark
if [ -d .userbenchmark ]; then rm -Rf .userbenchmark; fi
# Install torchao
python install.py torchao
python run_benchmark.py torchao --ci
cp -r ./.userbenchmark/torchao ../benchmark-output
- name: Upload result to GH Actions Artifact
uses: actions/upload-artifact@v3
with:
name: Torchao nightly result
path: benchmark-output/
- name: Clean up Conda env
if: always()
run: |
. "${SETUP_SCRIPT}"
conda deactivate && conda deactivate
conda remove -n "${CONDA_ENV}" --all