Install on Mila Cluster / Compute Canada

envs_CC.txt

absl_py==2.1.0+computecanada
asttokens==2.4.1+computecanada
astunparse==1.6.3+computecanada
black==24.4.2
causal-conv1d==1.4.0
certifi==2024.7.4
cffi==1.16.0+computecanada
charset-normalizer==3.3.2
chex==0.1.86+computecanada
click==8.1.7+computecanada
cloudpickle==3.0.0+computecanada
comm==0.2.2+computecanada
contextlib2==21.6.0+computecanada
contourpy==1.2.1+computecanada
cycler==0.12.1+computecanada
Cython==0.29.37
D4RL @ git+https://github.com/Farama-Foundation/d4rl@71a9549f2091accff93eeff68f1f3ab2c0e0a288
debugpy==1.8.1+computecanada
decorator==5.1.1+computecanada
dm_control==1.0.20
dm_env==1.6+computecanada
dm_tree==0.1.8+computecanada
docker-pycreds==0.4.0+computecanada
einops==0.8.0+computecanada
etils==1.7.0+computecanada
exceptiongroup==1.2.1+computecanada
executing==2.0.1+computecanada
Farama_Notifications==0.0.4+computecanada
fasteners==0.19+computecanada
filelock==3.15.4
flatbuffers==20190709135844+computecanada
fonttools==4.53.0+computecanada
fsspec==2024.6.1+computecanada
gast==0.6.0
gitdb==4.0.11+computecanada
GitPython==3.1.43
glfw==1.12.0+computecanada
google-pasta==0.2.0+computecanada
GPUtil==1.4.0+computecanada
grpcio==1.62.1+computecanada
gym==0.23.1
gym_notices==0.0.8+computecanada
gymnasium==0.29.1+computecanada
h5py==3.11.0+computecanada
huggingface_hub==0.23.4+computecanada
idna==3.7
imageio==2.34.2
importlib_resources==6.4.0
ipdb==0.13.13
ipykernel==6.29.4+computecanada
ipython==8.25.0+computecanada
jax==0.4.30
jaxlib==0.4.28+cuda12.cudnn89.computecanada
jedi==0.19.1+computecanada
jinja2==3.1.4+computecanada
joblib==1.4.2+computecanada
jupyter_client==8.6.2+computecanada
jupyter_core==5.7.2+computecanada
keras==3.4.1
kiwisolver==1.4.5+computecanada
labmaze==1.0.6+computecanada
libclang==14.0.1+computecanada
lxml==5.2.2+computecanada
mamba-ssm==2.2.2
Markdown==3.6
markdown_it_py==3.0.0+computecanada
MarkupSafe==2.1.5+computecanada
matplotlib==3.9.0+computecanada
matplotlib_inline==0.1.7+computecanada
mdurl==0.1.2+computecanada
mjrl @ git+https://github.com/aravindr93/mjrl@3871d93763d3b49c4741e6daeaebbc605fe140dc
ml-collections @ git+https://github.com/google/ml_collections.git@cea60d600434c9d040d4cb3b261d500f08fb828a
ml-dtypes==0.3.2
mpmath==1.3.0+computecanada
mujoco @ file:///tmp/ebuser/avx2/MuJoCo/3.1.6/GCCcore-12.3-gentoo/mujoco/mujoco-3.1.6
mujoco-py==2.1.2.14
mypy_extensions==1.0.0+computecanada
namex==0.0.8+computecanada
nest_asyncio==1.6.0+computecanada
networkx==3.3+computecanada
ninja==1.11.1+computecanada
nose==1.3.7+computecanada
numpy==1.26.4+computecanada
nvidia-pyindex==1.0.9
opt_einsum==3.3.0+computecanada
optax==0.1.8+computecanada
optree==0.10.0+computecanada
packaging==24.1+computecanada
pandas==2.2.1+computecanada
parso==0.8.4+computecanada
pathspec==0.12.1+computecanada
pexpect==4.9.0+computecanada
pillow==10.3.0+computecanada
platformdirs==4.2.2+computecanada
prompt_toolkit==3.0.47+computecanada
protobuf==4.25.3
psutil==5.9.8
ptyprocess==0.7.0+computecanada
pure_eval==0.2.2+computecanada
pybullet==3.2.6
pycparser==2.22
pygments==2.18.0+computecanada
PyOpenGL==3.1.7+computecanada
pyparsing==3.1.2+computecanada
python_dateutil==2.9.0.post0+computecanada
pytz==2024.1+computecanada
PyYAML==6.0.1+computecanada
pyzmq==26.0.3+computecanada
regex==2023.8.8+computecanada
requests==2.32.3
rich==13.7.1+computecanada
safetensors==0.4.3+computecanada
scikit_learn==1.5.0+computecanada
scipy==1.13.1+computecanada
seaborn==0.13.2+computecanada
sentry-sdk==2.9.0
setproctitle==1.3.2+computecanada
six==1.16.0+computecanada
smmap==5.0.1+computecanada
stack_data==0.6.3+computecanada
sympy==1.13.0+computecanada
tensorboard==2.16.2+computecanada
tensorboard-data-server==0.7.2
tensorflow==2.16.1+computecanada
tensorflow_io_gcs_filesystem==0.32.0+computecanada
termcolor==2.4.0+computecanada
threadpoolctl==3.5.0+computecanada
tokenizers==0.19.1+computecanada
tomli==2.0.1+computecanada
toolz==0.12.1+computecanada
torch==2.2.1+computecanada
tornado==6.3.3+computecanada
tqdm==4.66.4+computecanada
traitlets==5.14.3+computecanada
transformers==4.42.3
triton==2.3.0+computecanada
typing_extensions==4.12.2+computecanada
tzdata==2024.1+computecanada
urllib3==2.2.2
wandb==0.17.4
wcwidth==0.2.13+computecanada
Werkzeug==3.0.3
wrapt==1.16.0+computecanada
zipp==3.19.2

envs_mila.txt

name: rl2024
channels:
  - menpo
  - conda-forge
  - defaults
dependencies:
  - _libgcc_mutex=0.1
  - _openmp_mutex=5.1
  - asttokens=2.4.1
  - backcall=0.2.0
  - bzip2=1.0.8
  - ca-certificates=2024.6.2
  - decorator=5.1.1
  - entrypoints=0.4
  - executing=2.0.1
  - glew=2.1.0
  - glfw3=3.2.1
  - jedi=0.19.1
  - jupyter_client=7.3.4
  - jupyter_core=5.7.2
  - ld_impl_linux-64=2.38
  - libffi=3.3
  - libgcc-ng=11.2.0
  - libglu=9.0.0
  - libgomp=11.2.0
  - libsodium=1.0.18
  - libstdcxx-ng=11.2.0
  - libuuid=1.41.5
  - libxcb=1.15
  - matplotlib-inline=0.1.7
  - ncurses=6.4
  - nest-asyncio=1.6.0
  - openssl=1.1.1w
  - packaging=24.0
  - parso=0.8.4
  - pexpect=4.9.0
  - pickleshare=0.7.5
  - platformdirs=4.2.1
  - prompt-toolkit=3.0.42
  - ptyprocess=0.7.0
  - pure_eval=0.2.2
  - pygments=2.17.2
  - python=3.10.0
  - python-dateutil=2.9.0
  - python_abi=3.10
  - readline=8.2
  - six=1.16.0
  - sqlite=3.45.3
  - stack_data=0.6.2
  - tk=8.6.12
  - traitlets=5.14.3
  - wcwidth=0.2.13
  - xorg-kbproto=1.0.7
  - xorg-libx11=1.6.12
  - xorg-libxext=1.3.4
  - xorg-xextproto=7.3.0
  - xorg-xproto=7.0.31
  - xz=5.4.6
  - zeromq=4.3.5
  - zlib=1.2.13
  - pip:
    - absl-py==2.1.0
    - astunparse==1.6.3
    - black==24.4.2
    - certifi==2024.2.2
    - cffi==1.16.0
    - charset-normalizer==3.3.2
    - chex==0.1.86
    - click==8.1.7
    - cloudpickle==3.0.0
    - contextlib2==21.6.0
    - contourpy==1.2.1
    - cycler==0.12.1
    - cython==0.29.37
    - d4rl==1.1
    - debugpy==1.6.7
    - dm-control==1.0.20
    - dm-env==1.6
    - dm-tree==0.1.8
    - docker-pycreds==0.4.0
    - etils==1.7.0
    - farama-notifications==0.0.4
    - fasteners==0.19
    - filelock==3.14.0
    - flatbuffers==24.3.25
    - fonttools==4.51.0
    - fsspec==2024.3.1
    - gast==0.5.4
    - gitdb==4.0.11
    - gitpython==3.1.43
    - glfw==2.7.0
    - google-pasta==0.2.0
    - grpcio==1.63.0
    - gym==0.23.1
    - gym-notices==0.0.8
    - gymnasium==0.29.1
    - h5py==3.11.0
    - huggingface-hub==0.23.0
    - idna==3.7
    - imageio==2.34.1
    - importlib-resources==6.4.0
    - ipdb==0.13.13
    - ipykernel==6.14.0
    - ipython==8.4.0
    - jax==0.4.28
    - jax-cuda12-pjrt==0.4.28
    - jax-cuda12-plugin==0.4.28
    - jaxlib==0.4.28
    - jinja2==3.1.3
    - joblib==1.4.0
    - jupyter-core==5.7.2
    - keras==3.3.3
    - kiwisolver==1.4.5
    - labmaze==1.0.6
    - libclang==18.1.1
    - lxml==5.2.2
    - markdown==3.6
    - markdown-it-py==3.0.0
    - markupsafe==2.1.5
    - matplotlib==3.8.4
    - mdurl==0.1.2
    - mjrl==1.0.0
    - ml-collections==0.1.1
    - ml-dtypes==0.3.2
    - mpmath==1.3.0
    - mujoco==3.1.6
    - mujoco-py==2.1.2.14
    - mypy-extensions==1.0.0
    - namex==0.0.8
    - networkx==3.3
    - numpy==1.26.4
    - nvidia-cublas-cu12==12.1.3.1
    - nvidia-cuda-cupti-cu12==12.1.105
    - nvidia-cuda-nvcc-cu12==12.4.131
    - nvidia-cuda-nvrtc-cu12==12.1.105
    - nvidia-cuda-runtime-cu12==12.1.105
    - nvidia-cudnn-cu12==8.9.2.26
    - nvidia-cufft-cu12==11.0.2.54
    - nvidia-curand-cu12==10.3.2.106
    - nvidia-cusolver-cu12==11.4.5.107
    - nvidia-cusparse-cu12==12.1.0.106
    - nvidia-nccl-cu12==2.20.5
    - nvidia-nvjitlink-cu12==12.4.127
    - nvidia-nvtx-cu12==12.1.105
    - opt-einsum==3.3.0
    - optax==0.2.2
    - optree==0.11.0
    - pandas==2.2.2
    - patchelf==0.17.2.1
    - pathspec==0.12.1
    - pillow==10.3.0
    - pip==23.3.1
    - protobuf==4.25.3
    - psutil==5.9.0
    - pybullet==3.2.6
    - pycparser==2.22
    - pyopengl==3.1.7
    - pyparsing==3.1.2
    - pytz==2024.1
    - pyyaml==6.0.1
    - pyzmq==25.1.2
    - regex==2024.5.15
    - requests==2.31.0
    - rich==13.7.1
    - safetensors==0.4.3
    - scikit-learn==1.4.2
    - scipy==1.13.0
    - seaborn==0.13.2
    - sentry-sdk==2.3.1
    - setproctitle==1.3.3
    - setuptools==68.2.2
    - smmap==5.0.1
    - sympy==1.12
    - tensorboard==2.16.2
    - tensorboard-data-server==0.7.2
    - tensorflow==2.16.1
    - tensorflow-io-gcs-filesystem==0.37.0
    - termcolor==2.4.0
    - threadpoolctl==3.5.0
    - tokenize-rt==5.2.0
    - tokenizers==0.19.1
    - tomli==2.0.1
    - toolz==0.12.1
    - torch==2.3.1
    - torchvision==0.18.1
    - tornado==6.1
    - tqdm==4.66.4
    - transformers==4.41.0
    - triton==2.3.1
    - typing-extensions==4.11.0
    - tzdata==2024.1
    - urllib3==2.2.1
    - wandb==0.17.1
    - werkzeug==3.0.3
    - wheel==0.41.2
    - wrapt==1.16.0
    - zipp==3.19.2
prefix: /home/mila/t/tianwei.ni/.conda/envs/rl2024

test_dm.py

import os
os.environ["MUJOCO_GL"] = "egl" # egl will be faster than osmesa
from dm_control import suite
env = suite.load('cartpole', 'swingup')
pixels = env.physics.render()

test_jax.py

import jax
import jax.numpy as jnp
from jax import jit

print(jax.devices()[0].platform)

rng = jax.random.PRNGKey(1)
rng, key = jax.random.split(rng)

Count the #files recursively in a folder. This is useful for CC that has a limit on #files.

 find . -type f | wc -l

Zhixuan: check I really installed the packages into the virtualenv:

which python
which pip

In narval server, the virtual env may be not automatically loaded in jupyter of vscode. I have to manually add it by searching Python: Select Interpreter in the command palette. Then type ~/.venv/rl/bin/python to add the venv.

Clean Disk (obilaniu)

In Mila cluster, try the following steps:

• Remove pip cache pip cache purge
• Remove deprecated conda envs conda remove -n ENV_NAME --all
• Remove unused packages in conda conda clean -it (do not use conda clean -a which may break conda...)

For short-term projects (90 days), create the env in scratch conda create -p $SCRATCH/newenvname