fixup dependencies #22
Conversation
jefromson
requested review from
mxr-conda,
ndmaxar,
oblute,
ocefpaf,
rluria14 and
weiji14
as code owners
|
Hi! This is the friendly automated conda-forge-linting service. I just wanted to let you know that I linted all conda-recipes in your PR ( |
|
@conda-forge-admin, please rerender |
…nda-forge-pinning 2024.03.04.16.05.00
| @@ -23,7 +23,8 @@ requirements: | |||
| - pillow | |||
| - pretrainedmodels ==0.7.4 | |||
| - python >=3.6 | |||
| - timm ==0.9.2 | |||
There was a problem hiding this comment.
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.
There was a problem hiding this comment.
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:
- Set the pin to
>=0.9.2,<0.10a.0ainstead of==0.9.2with conda build's infrastructure, this translates to any "version 0.9". - 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.
There was a problem hiding this comment.
#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.
There was a problem hiding this comment.
Keeping an eye on qubvel-org/segmentation_models.pytorch#885 for smp to support timm 1.x
| @@ -23,7 +23,8 @@ requirements: | |||
| - pillow | |||
| - pretrainedmodels ==0.7.4 | |||
| - python >=3.6 | |||
There was a problem hiding this comment.
| - 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.
There was a problem hiding this comment.
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
Since segmentation-models-pytorch=0.3.3 requires timm=0.9.2. Xref conda-forge/segmentation-models-pytorch-feedstock#22 (comment)
* Remove explicit pin on timm Since segmentation-models-pytorch=0.3.3 requires timm=0.9.2. Xref conda-forge/segmentation-models-pytorch-feedstock#22 (comment) * Add back osx-64 and osx-arm64 platforms * Remove explicit pin on pyarrow Use whatever is set by lancedb and pylance. Currently pylance=0.14.1 pulls in pyarrow=14.0.2.
|
Exact |
Edit: I should have given more context here. I am attempting to install this package with the conda-forge release version of pytorch and it seems to have unmet dependencies requiring me to downgrade smp to 0.2.1. I am hoping to get the recipe here updated to be compatible with pytorch.
@hmaarrfk
Checklist
0(if the version changed)conda-smithy(Use the phrase@conda-forge-admin, please rerenderin a comment in this PR for automated rerendering)