RosettaCommons / RosettaCommons/RFdiffusion
Channel order causes CPU pytorch to be installed
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- Python
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Description
The channel order in the conda environment file puts conda-forge ahead of pytorch:
https://github.com/RosettaCommons/RFdiffusion/blob/ba8446eae0fb80c121829a67d3464772cc827f01/env/SE3nv.yml#L2-L7
This means that the conda-forge version of packages will be installed in preference to pytorch, at least using micromamba which I tested this with. This means that a GPU will not get utilized.
Can this file be updated to put pytorch at higher priority? Thanks
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Research direction
Open env/SE3nv.yml at lines 2-7 and inspect the channel order. Reproduce the dependency resolution with micromamba, then update the ordering so the PyTorch channel has higher priority. Done means the environment resolves to the GPU-enabled PyTorch packages rather than the conda-forge CPU version.
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Assessment
- Tech stack
- python, pytorch
- Domain
- devops, machine-learning
- Issue type
- Bug
- Difficulty
- 1/5
- Estimated time
- Under an hour
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 55/100