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[BugFix] Make sure ParallelEnv does not overflow mem when policy requires grad #614

[BugFix] Make sure ParallelEnv does not overflow mem when policy requires grad

[BugFix] Make sure ParallelEnv does not overflow mem when policy requires grad #614

Workflow file for this run

name: Unit-tests on Linux
on:
pull_request:
push:
branches:
- nightly
- main
- release/*
workflow_dispatch:
env:
CHANNEL: "nightly"
concurrency:
# Documentation suggests ${{ github.head_ref }}, but that's only available on pull_request/pull_request_target triggers, so using ${{ github.ref }}.
# On master, we want all builds to complete even if merging happens faster to make it easier to discover at which point something broke.
group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && format('ci-master-{0}', github.sha) || format('ci-{0}', github.ref) }}
cancel-in-progress: true
jobs:
tests-cpu:
strategy:
matrix:
python_version: ["3.8", "3.9", "3.10", "3.11"]
fail-fast: false
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
with:
runner: linux.12xlarge
repository: pytorch/rl
docker-image: "nvidia/cuda:12.2.0-devel-ubuntu22.04"
timeout: 90
script: |
# Set env vars from matrix
export PYTHON_VERSION=${{ matrix.python_version }}
export CU_VERSION="cpu"
export TORCH_VERSION=nightly
echo "PYTHON_VERSION: $PYTHON_VERSION"
echo "CU_VERSION: $CU_VERSION"
## setup_env.sh
bash .github/unittest/linux/scripts/run_all.sh
tests-gpu:
strategy:
matrix:
python_version: ["3.8"]
cuda_arch_version: ["12.1"]
fail-fast: false
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
with:
runner: linux.g5.4xlarge.nvidia.gpu
repository: pytorch/rl
docker-image: "nvidia/cuda:12.1.0-devel-ubuntu22.04"
gpu-arch-type: cuda
gpu-arch-version: ${{ matrix.cuda_arch_version }}
timeout: 90
script: |
# Set env vars from matrix
export PYTHON_VERSION=${{ matrix.python_version }}
# Commenting these out for now because the GPU test are not working inside docker
export CUDA_ARCH_VERSION=${{ matrix.cuda_arch_version }}
export CU_VERSION="cu${CUDA_ARCH_VERSION:0:2}${CUDA_ARCH_VERSION:3:1}"
export TORCH_VERSION=nightly
# Remove the following line when the GPU tests are working inside docker, and uncomment the above lines
#export CU_VERSION="cpu"
echo "PYTHON_VERSION: $PYTHON_VERSION"
echo "CU_VERSION: $CU_VERSION"
## setup_env.sh
bash .github/unittest/linux/scripts/run_all.sh
tests-olddeps:
strategy:
matrix:
python_version: ["3.8"]
cuda_arch_version: ["11.6"]
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"
timeout: 120
script: |
set -euo pipefail
export PYTHON_VERSION="3.9"
export CU_VERSION="cu116"
export TAR_OPTIONS="--no-same-owner"
export UPLOAD_CHANNEL="nightly"
export TF_CPP_MIN_LOG_LEVEL=0
bash .github/unittest/linux_olddeps/scripts_gym_0_13/setup_env.sh
bash .github/unittest/linux_olddeps/scripts_gym_0_13/batch_scripts.sh
bash .github/unittest/linux_olddeps/scripts_gym_0_13/post_process.sh
tests-optdeps:
strategy:
matrix:
python_version: ["3.9"] # "3.8", "3.9", "3.10", "3.11"
cuda_arch_version: ["12.1"] # "11.6", "11.7"
fail-fast: false
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
with:
runner: linux.g5.4xlarge.nvidia.gpu
repository: pytorch/rl
docker-image: "nvidia/cuda:12.1.0-devel-ubuntu22.04"
gpu-arch-type: cuda
gpu-arch-version: ${{ matrix.cuda_arch_version }}
timeout: 90
script: |
# Set env vars from matrix
export PYTHON_VERSION=${{ matrix.python_version }}
# Commenting these out for now because the GPU test are not working inside docker
export CUDA_ARCH_VERSION=${{ matrix.cuda_arch_version }}
export CU_VERSION="cu${CUDA_ARCH_VERSION:0:2}${CUDA_ARCH_VERSION:3:1}"
# Remove the following line when the GPU tests are working inside docker, and uncomment the above lines
#export CU_VERSION="cpu"
echo "PYTHON_VERSION: $PYTHON_VERSION"
echo "CU_VERSION: $CU_VERSION"
## setup_env.sh
bash .github/unittest/linux_optdeps/scripts/run_all.sh
tests-stable-gpu:
strategy:
matrix:
python_version: ["3.8"] # "3.8", "3.9", "3.10", "3.11"
cuda_arch_version: ["11.8"] # "11.6", "11.7"
fail-fast: false
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
with:
runner: linux.g5.4xlarge.nvidia.gpu
repository: pytorch/rl
docker-image: "nvidia/cuda:12.1.0-devel-ubuntu22.04"
gpu-arch-type: cuda
gpu-arch-version: ${{ matrix.cuda_arch_version }}
timeout: 90
script: |
# Set env vars from matrix
export PYTHON_VERSION=${{ matrix.python_version }}
# Commenting these out for now because the GPU test are not working inside docker
export CUDA_ARCH_VERSION=${{ matrix.cuda_arch_version }}
export CU_VERSION="cu${CUDA_ARCH_VERSION:0:2}${CUDA_ARCH_VERSION:3:1}"
export TORCH_VERSION=stable
# Remove the following line when the GPU tests are working inside docker, and uncomment the above lines
#export CU_VERSION="cpu"
echo "PYTHON_VERSION: $PYTHON_VERSION"
echo "CU_VERSION: $CU_VERSION"
## setup_env.sh
bash .github/unittest/linux/scripts/run_all.sh