Enable any resolution for Unet

[qubvel]

What does this PR do?

1. Replace scale_factor with size argument in Unet DecodeBlock to enable forward with any image resolution (not only divisible by 32)
2. Improve Unet docstring, add example
3. Fix type hint for models (was bugged by double inheritance with HubMixin)
4. Use inference_mode instead of no_grad in tests

[codecov]

Codecov Report

Attention: Patch coverage is 97.22222% with 1 line in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
...gmentation_models_pytorch/decoders/unet/decoder.py	96.29%	1 Missing ⚠️

Files with missing lines	Coverage Δ
segmentation_models_pytorch/base/model.py	81.57% <100.00%> (+2.79%)	⬆️
segmentation_models_pytorch/decoders/unet/model.py	100.00% <100.00%> (ø)
...gmentation_models_pytorch/decoders/unet/decoder.py	91.37% <96.29%> (+0.99%)	⬆️

[adamjstewart]

Not sure if I'm familiar enough with the details of the model to properly review this

[adamjstewart]

It's a bit confusing to me to see both "interpolate" and "interpolation", maybe we can make these consistent?

[qubvel]

Thanks for the catch! will fix it

[JulienMaille]

Could this break compatibility with onnx export -> OpenCV inference?

[qubvel]

@JulienMaille thanks for looking into it!

Right, initially, there was an issue with ONNX export, but nowadays ONNX export works with the size argument as well. I will check this out manually, but I plan to add ONNX exportability tests for all models.

[qubvel]

@JulienMaille I just checked this; the minimum opset to export the model with size is 11, while currently, the latest one is 21, so we are good to go