base_image: {{ env["RAY_IMAGE_ML_NIGHTLY_GPU"] }}
env_vars: {"LD_LIBRARY_PATH": "$LD_LIBRARY_PATH:/home/ray/.mujoco/mujoco210/bin", "RLLIB_TEST_NO_JAX_IMPORT": "1"}
debian_packages:
  - unzip
  - zip

  # Needed to run MuJoCo with gymnasium.
  - libosmesa6-dev
  - libgl1-mesa-glx
  - libglfw3
  - patchelf
  # End: MuJoCo.

python:
  pip_packages:
  # AutoROM downloads ROMs via torrent when they are built. The torrent is unreliable,
  # so we built it for py3 and use that instead. This wheel was tested for python 3.7, 3.8,
  # and 3.9.
  - https://ray-ci-deps-wheels.s3.us-west-2.amazonaws.com/AutoROM.accept_rom_license-0.5.4-py3-none-any.whl
  - pytest
  conda_packages: []

post_build_cmds:
  - pip3 uninstall -y ray || true && pip3 install -U {{ env["RAY_WHEELS"] | default("ray") }}
  - {{ env["RAY_WHEELS_SANITY_CHECK"] | default("echo No Ray wheels sanity check") }}
  # Clone the rl-experiments repo for offline-RL files.
  - git clone https://github.com/ray-project/rl-experiments.git
  - unzip rl-experiments/halfcheetah-sac/2022-12-17/halfcheetah_1500_mean_reward_sac.zip -d ~/.

  # Uninstall minigrid (it imports matplotlib, which sometimes causes a filelock error).
  # We don't need minigrid for the release tests.
  - pip3 uninstall -y minigrid

  # Install torch.
  - pip3 install torch==2.0.0+cu118 torchvision==0.15.1+cu118 --index-url https://download.pytorch.org/whl/cu118

  # TODO(sven): remove once nightly image gets gymnasium and the other new dependencies.
  - wget https://mujoco.org/download/mujoco210-linux-x86_64.tar.gz
  - mkdir ~/.mujoco
  - mv mujoco210-linux-x86_64.tar.gz ~/.mujoco/.
  - cd ~/.mujoco
  - tar -xf ~/.mujoco/mujoco210-linux-x86_64.tar.gz

  # not strictly necessary, but makes debugging easier
  - git clone https://github.com/ray-project/ray.git