Sandbox::https://github.com/pytorch/vision/pull/8295

gau-nernst · 2024-03-05T01:43:35Z

Fixes #8281

cc @vfdev-5

pytorch-bot · 2024-03-05T01:43:38Z

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❌ 3 New Failures

As of commit 4260a3b with merge base c7bcfad ():

NEW FAILURES - The following jobs have failed:

Tests / unittests-linux (3.11, linux.12xlarge, cpu) / linux-job (gh)
test/test_internet.py::TestDatasetUtils::test_download_url_dispatch_download_from_google_drive[False]
Tests / unittests-linux (3.9, linux.12xlarge, cpu) / linux-job (gh)
test/test_internet.py::TestDatasetUtils::test_download_url_dispatch_download_from_google_drive[False]
Tests / unittests-macos (3.8, macos-m1-stable) / macos-job (gh)
test/test_transforms_v2.py::TestLinearTransform::test_transform[cpu-dtype1-make_image_tensor]

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gau-nernst · 2024-03-05T08:22:59Z

@NicolasHug I signed the CLA but the status did not change. Not sure what went wrong. Do I need to use the same email as my GitHub account? I signed the CLA with a different email. Then I tried again with my GitHub email. Still no changes here.

vfdev-5 · 2024-03-05T13:36:52Z

+    angle = angle % 360  # shift angle to [0, 360) range
+
+    # fast path: transpose without affine transform
+    if expand or center is None:


why if expand ?

I was reading the NOTE section of v2.RandomRotation, and it says that

setting center has no effect if expand=True

From what I understand, if expand=True, we can ignore center, and thus we can safely use torch.rot90().

I think we can remove expand from the check

facebook-github-bot · 2024-03-05T15:06:17Z

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gau-nernst · 2024-03-06T01:54:28Z

Regarding testing, I think we should test for angles 0, 90, 180, 270. Should I add them here?

vision/test/test_transforms_v2.py

Lines 1496 to 1503 in f3298dc

    
           class TestRotate: 
        
               _EXHAUSTIVE_TYPE_AFFINE_KWARGS = dict( 
        
                   # float, int 
        
                   angle=[-10.9, 18], 
        
                   # None 
        
                   # two-list of float, two-list of int, two-tuple of float, two-tuple of int 
        
                   center=[None, [1.2, 4.9], [-3, 1], (2.5, -4.7), (3, 2)], 
        
               )

My concern is that it will create many more test cases.

The alternative is to write a separate test for angles 0, 90, 180, 270, and we don't use too many values for other parameters (center, expand, fill).

NicolasHug · 2024-03-06T09:46:15Z

Thanks @gau-nernst

The alternative is to write a separate test for angles 0, 90, 180, 270, and we don't use too many values for other parameters (center, expand, fill).

Yes, we can probably create a small separate test to check these specific values, and simply test the output of PIL vs our tensor implementation

NicolasHug

Thanks a lot @gau-nernst for the PR and @vfdev-5 for the reviews. This is good to go on my side, let's just wait for @vfdev-5 's input before merging

vfdev-5

lgtm as well, thanks @gau-nernst !

NicolasHug · 2024-03-13T11:25:49Z

+    angle = angle % 360  # shift angle to [0, 360) range
+
+    # fast path: transpose without affine transform
+    if center is None:


The tests are failing and I think it's because we should set expand to True. When expand is False we're not supposed to be changing the shape of the output (which is what rot90 does!).

Suggested change

if center is None:

if expand and center is None:

Here is what does PIL here:
https://github.com/python-pillow/Pillow/blob/8f63748e50378424628155994efd7e0739a4d1d1/src/PIL/Image.py#L2287-L2296

Yes, I agree that it is incorrect to omit expand for image with h != w, sorry for an incorrect suggestion previously.

Should we also check for square input then? So even if expand is false, rot90 is still valid.

Following their code they: 1) accept angle 0 and 180 whatever provided expand value and 2) for rotations 90 or 270 they do if angle in (90, 270) and (expand or self.width == self.height).
I think this is reasonable and we can do the same

I will update accordingly

I have updated the code. Also updated the test cases to cover everything. I just realized the tests didn't fail on my machine because I was running inside an environment with torchvision installed (big mistake!).

No worries @gau-nernst thanks for the update. I can confirm the tests are passing now (tried locally). let's just wait for the CI to be green before merging

github-actions · 2024-03-13T17:17:43Z

Hey @NicolasHug!

You merged this PR, but no labels were added.
The list of valid labels is available at https://github.com/pytorch/vision/blob/main/.github/process_commit.py

Summary: Co-authored-by: Thien Tran <thien.tran@parallelchain.io> Reviewed By: vmoens Differential Revision: D55062767 fbshipit-source-id: b67a7f7fecab8a33143b95e6233637c336c74cd4

add rotation fast path

3c5b5b2

vfdev-5 reviewed Mar 5, 2024

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Comment thread torchvision/transforms/_functional_pil.py Resolved

gau-nernst added 3 commits March 5, 2024 21:25

Merge branch 'pytorch:main' into main

8652144

remove PIL fast path

cb4f943

return clone() for angle=0

dbb36a8

vfdev-5 reviewed Mar 5, 2024

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gau-nernst added 3 commits March 5, 2024 22:08

fix torchscript (and typing)

f4d9e00

remove expand check for fast path

7cad321

Merge branch 'main' into main

dbde073

facebook-github-bot added the cla signed label Mar 5, 2024

gau-nernst added 3 commits March 6, 2024 21:25

add test

872d4c4

Merge branch 'main' into main

10f51bd

Merge branch 'main' into main

1860a1f

gau-nernst requested a review from vfdev-5 March 12, 2024 11:34

NicolasHug approved these changes Mar 13, 2024

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vfdev-5 approved these changes Mar 13, 2024

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NicolasHug reviewed Mar 13, 2024

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NicolasHug mentioned this pull request Mar 13, 2024

Add Jpeg Compression augmentation #8290

Closed

gau-nernst added 3 commits March 14, 2024 00:06

Merge branch 'main' into main

53f6c92

fix fast path

154d715

Merge branch 'main' into main

4260a3b

gau-nernst requested review from NicolasHug and vfdev-5 March 13, 2024 16:40

NicolasHug merged commit ba64d65 into pytorch:main Mar 13, 2024

NicolasHug added enhancement module: transforms labels Mar 14, 2024

DimitrisMantas mentioned this pull request Feb 6, 2026

RandomRotate(((90, 90)) produces Non-Contiguous Tensors #9378

Closed

davrens101 mentioned this pull request Nov 10, 2026

Use rot90 for right-angle tensor rotations in transforms.functional.rotate #9749

Open

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