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Update rescale tests - cast to float after rescaling to reflect #25229 (#25259)

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Rescale tests - cast to float after rescaling to reflect #25229
This commit is contained in:
amyeroberts
2023-08-02 11:29:55 +01:00
committed by GitHub
parent 904e7e0f3c
commit 1b35409768
2 changed files with 4 additions and 4 deletions
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4
tests/models/efficientnet/test_image_processing_efficientnet.py
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@@ -201,9 +201,9 @@ class EfficientNetImageProcessorTest(ImageProcessingSavingTestMixin, unittest.Te
image_processor = self.image_processing_class(**self.image_processor_dict) image_processor = self.image_processing_class(**self.image_processor_dict)
rescaled_image = image_processor.rescale(image, scale=1 / 255) rescaled_image = image_processor.rescale(image, scale=1 / 255)
expected_image = image.astype(np.float32) * (2 / 255.0) - 1 expected_image = (image * (2 / 255.0)).astype(np.float32) - 1
self.assertTrue(np.allclose(rescaled_image, expected_image)) self.assertTrue(np.allclose(rescaled_image, expected_image))
rescaled_image = image_processor.rescale(image, scale=1 / 255, offset=False) rescaled_image = image_processor.rescale(image, scale=1 / 255, offset=False)
expected_image = image.astype(np.float32) / 255.0 expected_image = (image / 255.0).astype(np.float32)
self.assertTrue(np.allclose(rescaled_image, expected_image)) self.assertTrue(np.allclose(rescaled_image, expected_image))

4
tests/models/vivit/test_image_processing_vivit.py
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@@ -220,9 +220,9 @@ class VivitImageProcessingTest(ImageProcessingSavingTestMixin, unittest.TestCase
image_processor = self.image_processing_class(**self.image_processor_dict) image_processor = self.image_processing_class(**self.image_processor_dict)
rescaled_image = image_processor.rescale(image, scale=1 / 255) rescaled_image = image_processor.rescale(image, scale=1 / 255)
expected_image = image.astype(np.float32) * (2 / 255.0) - 1 expected_image = (image * (2 / 255.0)).astype(np.float32) - 1
self.assertTrue(np.allclose(rescaled_image, expected_image)) self.assertTrue(np.allclose(rescaled_image, expected_image))
rescaled_image = image_processor.rescale(image, scale=1 / 255, offset=False) rescaled_image = image_processor.rescale(image, scale=1 / 255, offset=False)
expected_image = image.astype(np.float32) / 255.0 expected_image = (image / 255.0).astype(np.float32)
self.assertTrue(np.allclose(rescaled_image, expected_image)) self.assertTrue(np.allclose(rescaled_image, expected_image))