Rotation sampling grid is undesireably low-res

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Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
78/100
Issue type
Bug
Clarity
Clearly specified
Activity status
Active
Tech stack
python
Domain
computer-vision

Research direction

Start in torchvision/transforms/_functional_tensor.py around line 594, where the resampling grid is created with linspace. Reproduce the rotation behavior using bfloat16 or float16 on an image larger than 250x250 pixels, then verify the grid avoids the reported quantization and the output is no longer visibly subsampled.

Written by the indexing model from the issue text.

Description

🐛 Describe the bug

https://github.com/pytorch/vision/blob/f799a5348d990de02f9189d9496f369bacfe5cf3/torchvision/transforms/_functional_tensor.py#L594

This function that creates the resampling grid will use the default tensor dtype. If this is bfloat16/float16 and the image is sufficiently large (over 250x250 px), this results in significant quantizing that seems undesirable. The output will look extremely subsampled from the original. This would not occur if the dtype was higher precision.

My suggestion would be to update these linspace to either be dtype=theta.dtype or explicitly dtype=torch.float32 to prevent this from happening.

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