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Envpool Tests to Nova (pytorch#1283)
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osalpekar authored Jul 15, 2023
1 parent 07f502a commit ef5be1c
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6 changes: 6 additions & 0 deletions .circleci/unittest/linux_libs/scripts_envpool/setup_env.sh
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Expand Up @@ -47,6 +47,8 @@ pip install pip --upgrade

conda env update --file "${this_dir}/environment.yml" --prune

yum install -y mesa-libGL

conda deactivate
conda activate "${env_dir}"

Expand Down Expand Up @@ -80,3 +82,7 @@ else
pip install "gym[atari,accept-rom-license]"
fi
pip install envpool treevalue

# wget https://files.pythonhosted.org/packages/a1/ee/b35ab21e71d34cdcedf05c0d32abca3a3e87d669bdc772660165ee2f55b8/envpool-0.8.2-cp39-cp39-manylinux_2_24_x86_64.whl
# pip install envpool-0.8.2-cp39-cp39-manylinux_2_24_x86_64.whl
# rm envpool-0.8.2-cp39-cp39-manylinux_2_24_x86_64.whl
36 changes: 36 additions & 0 deletions .github/workflows/test-linux-envpool.yml
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@@ -0,0 +1,36 @@
name: Envpool Tests on Linux

on:
pull_request:
push:
branches:
- nightly
- main
- release/*
workflow_dispatch:

jobs:
unittests:
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
with:
repository: pytorch/rl
runner: "linux.g5.4xlarge.nvidia.gpu"
# gpu-arch-type: cuda
# gpu-arch-version: "11.7"
# docker-image: "nvidia/cudagl:11.4.0-base"
docker-image: "pytorch/manylinux-cuda117"
timeout: 120
script: |
set -euo pipefail
export PYTHON_VERSION="3.8"
export CU_VERSION="11.7"
export TAR_OPTIONS="--no-same-owner"
export UPLOAD_CHANNEL="nightly"
export TF_CPP_MIN_LOG_LEVEL=0
nvidia-smi
bash .circleci/unittest/linux_libs/scripts_envpool/setup_env.sh
bash .circleci/unittest/linux_libs/scripts_envpool/install.sh
bash .circleci/unittest/linux_libs/scripts_envpool/run_test.sh
bash .circleci/unittest/linux_libs/scripts_envpool/post_process.sh

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