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Bump the torch group in /requirements with 2 updates #1050

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Jan 30, 2025
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Bump the torch group in /requirements with 2 updates #1050

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Bump the torch group in /requirements with 2 updates
dependabot[bot] Jan 30, 2025
d3cefdd
Fix dpn exportable flag
qubvel Jan 30, 2025
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4 changes: 2 additions & 2 deletions requirements/required.txt
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Expand Up @@ -5,6 +5,6 @@ pretrainedmodels==0.7.4
safetensors==0.5.2
six==1.17.0
timm==1.0.14
torch==2.5.1
torchvision==0.20.1
torch==2.6.0
torchvision==0.21.0
tqdm==4.67.1
2 changes: 1 addition & 1 deletion segmentation_models_pytorch/encoders/dpn.py
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Expand Up @@ -34,7 +34,7 @@

class DPNEncoder(DPN, EncoderMixin):
_is_torch_scriptable = False
_is_torch_exportable = False
_is_torch_exportable = True # since torch 2.6.0
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@adamjstewart adamjstewart Jan 30, 2025 •
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Should this have an if-statement based on PyTorch version?

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hmm.. this way, we should test other encoders for all the previous torch versions as well. torch.export is still in active development and it's recommended to use the latest torch, so I suppose a comment is enough unless we see an issue

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That's why I designed the tests to run on the newest and oldest version of all of our dependencies.

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@qubvel qubvel Jan 30, 2025 •
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Yes, I understand, but some features are introduced with the latest version of torch, while the main functionality works with the previous versions. I'm not sure we should claim we are only compatible with PyTorch 2.6+ if only a very small subset of features fails. WDYT?

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I think it should be clearly stated in the docs/README that export/scripting/compilation has been tested and is expected to work with the latest versions and one may encounter issues with previous versions.

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We can support a wider range of PyTorch versions by using an if-statement on this one line of code. Alternatively, we can skip the export test for this specific model for certain versions of PyTorch.


def __init__(
self,
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