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[Algorithm] RLHF end-to-end, clean #1540

[Algorithm] RLHF end-to-end, clean

[Algorithm] RLHF end-to-end, clean #1540

name: Unit-tests on Windows GPU
on:
pull_request:
push:
branches:
- nightly
- main
- release/*
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && format('ci-master-{0}', github.sha) || format('ci-{0}', github.ref) }}
cancel-in-progress: true
jobs:
unittests:
uses: pytorch/test-infra/.github/workflows/windows_job.yml@main
with:
runner: "windows.g5.4xlarge.nvidia.gpu"
repository: pytorch/rl
timeout: 240
script: |
set -euxo pipefail
export PYTHON_VERSION="3.9"
export CUDA_VERSION="11.6"
export CU_VERSION="cu116"
# TODO: Port this to pytorch/test-infra/.github/workflows/windows_job.yml
export PATH="/c/Jenkins/Miniconda3/Scripts:${PATH}"
echo "PYTHON_VERSION: $PYTHON_VERSION"
## setup_env.sh
./.github/unittest/windows_optdepts/scripts/setup_env.sh
## Install CUDA
packaging/windows/internal/cuda_install.bat
## Update CUDA Driver
packaging/windows/internal/driver_update.bat
## install.sh
./.github/unittest/windows_optdepts/scripts/install.sh
## run_test.sh
./.github/unittest/windows_optdepts/scripts/run_test.sh
## post_process.sh
./.github/unittest/windows_optdepts/scripts/post_process.sh