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Installation failing related to pymc: workaround #30
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This was an issue for about a month, but you should be able to use numpy 1.26 with the latest version of pytensor and pymc: pymc-devs/pytensor#441 (comment). Maybe check to make sure you have the latest version of pytensor? (Although I don't see why you wouldn't get it from pymc...) For reference, these are some of the packages in a python venv I created recently: Package Version jax 0.4.21 One possible difference from what you did was that I did:
before installing other requirements, because it seems like Also, I don't know what the pytensor fix was, so maybe they just avoided the meson build of numpy, which was what caused numpy 1.26 to fail with older versions of pytensor (although I'm not sure if there is an alternative to the meson build for numpy 1.26). |
Not sure if this is related, but I also got an error related to pymc when running
It was resolved by rolling back from python 3.12 to python 3.11 (as described here: https://stackoverflow.com/questions/77364550/attributeerror-module-pkgutil-has-no-attribute-impimporter-did-you-mean) |
I don't think openghg supports python 3.12 yet (I could be wrong). I suppose this should be in the install instructions, if that's the case. |
When running
pip install -e openghg_inversions
I ran into an installation issue related to pymc.My workaround was to install pymc when creating the new environment (note I used conda rather than a virtual environment here), and ensuring that numpy was version 1.25.2 (the latest numpy version causes conflicts, this happens at runtime):
conda create -c conda-forge -n openghg_inv "pymc>5" "numpy=1.25.2"
pip install --upgrade pip setuptools wheel
pip install -e openghg_inversions
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