Fix TorchVision channel preprocessing #3173
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tgaddair
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Mar 1, 2023
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@jimthompson5802 FYI |
tgaddair
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justinxzhao
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ludwig/features/image_feature.py
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| self, | ||
| metadata: TrainingSetMetadataDict, | ||
| torchvision_transform: Optional[torch.nn.Module] = None, | ||
| transform_metadata: Optional[Dict[str, Any]] = None, |
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nit: Consider breaking up transform_metadata into separate fields: transform_height, transform_width, transform_num_channels`, or used a dataclass for stronger field guarantees and typing:
@dataclass
class ImageTransformMetadata:
height: int
width: int
num_channels: intThere was a problem hiding this comment.
nice suggestion– I wasn't sure that torchscript supported this, but apparently it does! pytorch/pytorch#72901
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This PR introduces automatic channel resizing for torchvision models to ensure that images fed into torchvision encoders always have 3 channels. Closes #3170.