Add Tensor support for some transforms #1104
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Codecov Report
@@ Coverage Diff @@
## master #1104 +/- ##
==========================================
+ Coverage 63.92% 64.89% +0.96%
==========================================
Files 68 68
Lines 5406 5438 +32
Branches 829 843 +14
==========================================
+ Hits 3456 3529 +73
+ Misses 1707 1650 -57
- Partials 243 259 +16
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|
fmassa
changed the title
soumith
approved these changes
Jul 26, 2019
| PIL Image: Resized image. | ||
| """ | ||
| if not _is_pil_image(img): | ||
| if not (_is_pil_image(img) or isinstance(img, torch.Tensor)): |
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the comment above needs to be updated that it takes torch.Tensor (and has to specify what range the Tensor's values have to be)
| PIL Image: Cropped image. | ||
| """ | ||
| if not _is_pil_image(img): | ||
| if not (_is_pil_image(img) or isinstance(img, torch.Tensor)): |
| Image.NEAREST: "nearest", | ||
| Image.BILINEAR: "bilinear" | ||
| } | ||
| should_unsqueeze = False |
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this is actually should_squeeze as you squeeze below in 278
| PIL Image: Horizontall flipped image. | ||
| """ | ||
| if not _is_pil_image(img): | ||
| if not (_is_pil_image(img) or isinstance(img, torch.Tensor)): |
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same documentation comment as above
| raise TypeError('img should be PIL Image. Got {}'.format(type(img))) | ||
|
|
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| return img.transpose(Image.FLIP_LEFT_RIGHT) | ||
| if _is_pil_image(img): |
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it's much cleaner to write explicit if/else, rather than have if shortcut to a return
| PIL Image: Vertically flipped image. | ||
| """ | ||
| if not _is_pil_image(img): | ||
| if not (_is_pil_image(img) or isinstance(img, torch.Tensor)): |
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This is a POC implementation for adding support for tensors in some of the transforms.
It will be specially useful for video, and also as a first step towards enabling (some of) the transforms to be traceable.