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[CI] Added CircleCI pipeline to test compatibility across supported gym versions (#645)
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‎.circleci/config.yml

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- store_test_results:
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path: test-results
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unittest_linux_gym_gpu:
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<<: *binary_common
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machine:
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image: ubuntu-2004-cuda-11.4:202110-01
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resource_class: gpu.nvidia.medium
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environment:
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image_name: "pytorch/manylinux-cuda113"
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TAR_OPTIONS: --no-same-owner
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PYTHON_VERSION: << parameters.python_version >>
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CU_VERSION: << parameters.cu_version >>
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steps:
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- checkout
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- designate_upload_channel
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- run:
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name: Generate cache key
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# This will refresh cache on Sundays, nightly build should generate new cache.
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command: echo "$(date +"%Y-%U")" > .circleci-weekly
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- restore_cache:
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keys:
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- env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux_libs/scripts_gym/environment.yml" }}-{{ checksum ".circleci-weekly" }}
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- run:
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name: Setup
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command: docker run -e PYTHON_VERSION -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux_libs/scripts_gym/setup_env.sh
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- save_cache:
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key: env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux_libs/scripts_gym/environment.yml" }}-{{ checksum ".circleci-weekly" }}
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paths:
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- conda
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- env
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- run:
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name: Install torchrl, run tests
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command: |
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docker run -t --env=CUDA_VISIBLE_DEVICES="" --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux_libs/scripts_gym/batch_scripts.sh
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- run:
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name: Codecov upload
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command: |
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bash <(curl -s https://codecov.io/bash) -Z -F linux-gpu
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- run:
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name: Post process
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command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux_libs/scripts_gym/post_process.sh
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- store_test_results:
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path: test-results
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unittest_linux_optdeps_gpu:
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<<: *binary_common
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machine:
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cu_version: cu113
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name: unittest_linux_habitat_gpu_py3.8
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python_version: '3.8'
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- unittest_linux_gym_gpu:
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cu_version: cu113
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name: unittest_linux_gym_gpu_py3.8
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python_version: '3.8'
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- unittest_macos_cpu:
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cu_version: cpu

‎.circleci/unittest/linux_libs/scripts_gym/batch_scripts.sh

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#!/usr/bin/env bash
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# Runs a batch of scripts in a row to allow docker run to keep installed libraries
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# and env variables across runs.
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DIR="$(cd "$(dirname "$0")" && pwd)"
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set -e
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eval "$(./conda/bin/conda shell.bash hook)"
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conda activate ./env
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# Install PyTorch and TorchRL.
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$DIR/install.sh
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# Extracted from run_test.sh to run once.
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yum makecache && yum install libglvnd-devel mesa-libGL mesa-libGL-devel mesa-libEGL mesa-libEGL-devel glfw mesa-libOSMesa-devel glew glew-devel egl-utils freeglut xorg-x11-server-Xvfb -y
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# This version is installed initially (see environment.yml)
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for GYM_VERSION in '0.13'
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do
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echo "Testing gym version: ${GYM_VERSION}"
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pip3 install 'gym[atari]'==$GYM_VERSION
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$DIR/run_test.sh
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done
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# gym[atari]==0.19 is broken, so we install only gym without dependencies.
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for GYM_VERSION in '0.19'
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do
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echo "Testing gym version: ${GYM_VERSION}"
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pip3 install gym==$GYM_VERSION
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$DIR/run_test.sh
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done
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# gym[atari]==0.20 installs ale-py==0.8, but this version is not compatible with gym<0.26, so we downgrade it.
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for GYM_VERSION in '0.20'
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do
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echo "Testing gym version: ${GYM_VERSION}"
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pip3 install 'gym[atari]'==$GYM_VERSION
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pip3 install ale-py==0.7
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$DIR/run_test.sh
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done
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for GYM_VERSION in '0.25'
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do
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echo "Testing gym version: ${GYM_VERSION}"
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pip3 install 'gym[atari]'==$GYM_VERSION
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$DIR/run_test.sh
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done
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# For this version "gym[accept-rom-license]" is required.
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for GYM_VERSION in '0.26'
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do
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echo "Testing gym version: ${GYM_VERSION}"
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pip3 install 'gym[accept-rom-license]'==$GYM_VERSION
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pip3 install 'gym[atari]'==$GYM_VERSION
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$DIR/run_test.sh
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done

‎.circleci/unittest/linux_libs/scripts_gym/environment.yml

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channels:
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- pytorch
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- defaults
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dependencies:
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- pip
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- protobuf
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- pip:
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# Initial version is required to install Atari ROMS in setup_env.sh
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- gym[atari]==0.13
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- hypothesis
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- future
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- cloudpickle
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- pygame
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- moviepy
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- tqdm
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- pytest
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- pytest-cov
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- pytest-mock
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- pytest-instafail
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- expecttest
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- pyyaml
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- scipy
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- hydra-core
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- dm_control -e git+https://github.com/deepmind/dm_control.git@c053360edea6170acfd9c8f65446703307d9d352#egg={dm_control}
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- patchelf
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- pyopengl==3.1.4

‎.circleci/unittest/linux_libs/scripts_gym/install.sh

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#!/usr/bin/env bash
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unset PYTORCH_VERSION
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# For unittest, nightly PyTorch is used as the following section,
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# so no need to set PYTORCH_VERSION.
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# In fact, keeping PYTORCH_VERSION forces us to hardcode PyTorch version in config.
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set -e
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eval "$(./conda/bin/conda shell.bash hook)"
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conda activate ./env
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#apt-get update -y && apt-get install git wget gcc g++ -y
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if [ "${CU_VERSION:-}" == cpu ] ; then
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cudatoolkit="cpuonly"
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version="cpu"
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else
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if [[ ${#CU_VERSION} -eq 4 ]]; then
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CUDA_VERSION="${CU_VERSION:2:1}.${CU_VERSION:3:1}"
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elif [[ ${#CU_VERSION} -eq 5 ]]; then
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CUDA_VERSION="${CU_VERSION:2:2}.${CU_VERSION:4:1}"
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fi
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echo "Using CUDA $CUDA_VERSION as determined by CU_VERSION ($CU_VERSION)"
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version="$(python -c "print('.'.join(\"${CUDA_VERSION}\".split('.')[:2]))")"
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cudatoolkit="cudatoolkit=${version}"
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fi
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case "$(uname -s)" in
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Darwin*) os=MacOSX;;
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*) os=Linux
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esac
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# submodules
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git submodule sync && git submodule update --init --recursive
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printf "Installing PyTorch with %s\n" "${CU_VERSION}"
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if [ "${CU_VERSION:-}" == cpu ] ; then
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conda install pytorch==1.10.0 torchvision==0.11.0 torchaudio==0.10.0 cpuonly -c pytorch -y
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else
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conda install pytorch==1.10.0 torchvision==0.11.0 torchaudio==0.10.0 cudatoolkit=11.3 -c pytorch -c conda-forge -y
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fi
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# install tensordict
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pip install git+https://github.com/pytorch-labs/tensordict
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printf "* Installing torchrl\n"
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python setup.py develop

‎.circleci/unittest/linux_libs/scripts_gym/post_process.sh

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#!/usr/bin/env bash
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set -e
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eval "$(./conda/bin/conda shell.bash hook)"
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conda activate ./env

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