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fixup dependencies #22

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294f3a6
fixup dependencies
Mar 4, 2024
d4f2ca1
MNT: Re-rendered with conda-build 24.1.2, conda-smithy 3.31.1, and co…
Mar 4, 2024
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8 changes: 3 additions & 5 deletions .azure-pipelines/azure-pipelines-linux.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,8 @@ requirements:
- pillow
- pretrainedmodels ==0.7.4
- python >=3.6
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Suggested change
- python >=3.6
- python >=3.7

Upstream says that this should be 3.7.
https://github.com/qubvel/segmentation_models.pytorch/blob/v0.3.3/setup.py#L20

though it may be entirely true that 3.6 is compatible.

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Minimum version for python is 3.9 now according to https://github.com/qubvel-org/segmentation_models.pytorch/blame/v0.3.4/setup.py#L20

- timm ==0.9.2
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Smp 0.3.3 has a hard pin on the version of timm, see error at https://dev.azure.com/conda-forge/feedstock-builds/_build/results?buildId=888834&view=logs&j=656edd35-690f-5c53-9ba3-09c10d0bea97&t=986b1512-c876-5f92-0d81-ba851554a0a3&l=1048:

segmentation-models-pytorch 0.3.3 has requirement timm==0.9.2, but you have timm 0.9.16

Will need to update upstream at https://github.com/qubvel/segmentation_models.pytorch/blob/6db76a1106426ac5b55f39fba68168f3bccae7f8/requirements.txt#L4, and get them to make a new release before it can be changed here.

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Maintainer of https://github.com/conda-forge/pytorch-cpu-feedstock/ here.
Thank you for pinging me @jefromson .

Sometimes it is appropriate to patch the source code.

We do this a bit with conda-forge because often we are more at the bleeding edge of releases compared to what people are working with upstream.

It may be that we should:

  1. Set the pin to >=0.9.2,<0.10a.0a instead of ==0.9.2 with conda build's infrastructure, this translates to any "version 0.9".
  2. Patch the file you pointed to with a conda-forge patch. Preferably, we leave a comment pointing to a tracking issue upstream, or even more preferred, a PR showing that the proposed patch was merged and is slated for the next release.

This is sometimes quite risky without tests. I can help try to run the small test suite in the recipe if you want.

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#23 <-- leaving this here as an example of what I have in mind. but I haven't run any analysis code, so it might be fully broken.

I did leave a reference to the open issue asking for a new release with expanded timm compatibility.

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Keeping an eye on qubvel-org/segmentation_models.pytorch#885 for smp to support timm 1.x

- six
- timm
- torchvision >=0.5.0
- tqdm

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