Installing PYG with conda is very buggy

😵 Describe the installation problem

This is a report concerning an environment built from scratch from an environment.yml file. First thing I tried was installing a PyTorch 1.11 environment, which caused the following bug with CUDA: https://github.com/rusty1s/pytorch_scatter/issues/248. Second try was with a PyTorch 1.10 environment which resulted in the following error: https://github.com/pyg-team/pytorch_geometric/issues/3593. I was able to temporarily fix this by uninstalling torch_spline_conv but this was just a temporary fix. The very next moment I tried installing a package with CUDA, pyg==2.0.4 reported a conflict, which couldn’t be resolved by anything I tried. The conda resolver tried in vain to fix this issue, reporting countless of versioning issues related to PYG, including again the GLIBC version problem (which apparently IPython also has a problem with, albeit being silent before the full conda check is performed). Worth mentioning that this is a remote server so I cannot change the GLIBC version anyway.

This is now getting frustrating and I’d hate to have to resort to installing from scratch the environment every time I need a new package. Something is clearly broken with the PYG versioning on conda, since uninstalling pyg fixed everything… Below is the environment.yml in question:

name: graph
channels:
  - pytorch
  - pyg
  - conda-forge
  - defaults
dependencies:
  - python=3.9
  - conda
  - pytorch=1.10.1
  - torchvision==0.11.2
  - cudatoolkit=11.3
  - pyg
  - networkx
  - numpy
  - matplotlib
  - plotly
  - pandas
  - tqdm
  - dill
  - scikit-learn
  - jupyterlab
  - torchvision
  - pytorch-lightning
  - neptune-client

Environment

• PyG version: 2.0.4
• PyTorch version: 1.10
• OS: Red Hat Enterprise Linux 7"
• Python version: 3.9.12
• CUDA/cuDNN version: 11.3
• How you installed PyTorch and PyG (conda, pip, source): conda
• Any other relevant information (e.g., version of torch-scatter):

[rusty1s]

Can you try to run

pip uninstall torch-spline-conv

[andrei-rusu]

I see, thank you! Unfortunately I do not have sudo there, so I think I’ll stick to using the “dirty” pip installs for now. But I’ll keep this issue opened as it would be nice to have conda behave nicely on remote servers (a lot of which utilize outdated GLIBC unfortunately).