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pytorchcondanvidia-jetsonmini-forge

Miniforge Conda "PackagesNotFoundError" on ARM processor for PyTorch


I am unable to install any packages with miniforge 3 (conda 4.11.0).

I am attempting this on a Jetson Nano Developer Kit running Jetpack. Initially it had conda installed but it seems to have gone missing, so I decided to reinstall conda. It looks like the base version of anaconda/miniconda is having issues running on ARM processors, and so I downloaded miniforge which apparently is working.

I have set up an environment successfully, but attempting to download pytorch gives the following error:

Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.

PackagesNotFoundError: The following packages are not available from current channels:

  - pytorch

Current channels:

  - https://conda.anaconda.org/pytorch/linux-aarch64
  - https://conda.anaconda.org/pytorch/noarch
  - https://conda.anaconda.org/abinit/linux-aarch64
  - https://conda.anaconda.org/abinit/noarch
  - https://conda.anaconda.org/matsci/linux-aarch64
  - https://conda.anaconda.org/matsci/noarch
  - https://conda.anaconda.org/conda-forge/linux-aarch64
  - https://conda.anaconda.org/conda-forge/noarch

To search for alternate channels that may provide the conda package you're
looking for, navigate to

    https://anaconda.org

and use the search bar at the top of the page.

This is for Python 3.7.12. It seems this issue persists no matter what version of pytorch I try to install.

I am however able to install some other packages, as I was able to install beautifulsoup4.



Solution

  • There is no linux-aarch64 version of pytorch on the default conda channel, see here

    This is of course package specific. E.g. there is a linux-aarch64 version of beautifulsoup4 which is why you wre able to install it without an issue.

    You can try to install from a different channel that claims to provide a pytorch for aarch64, e.g.

    conda install -c kumatea pytorch