Refactor image processor testers (#25450)
* Refactor image processor test mixin - Move test_call_numpy, test_call_pytorch, test_call_pil to mixin - Rename mixin to reflect handling of logic more than saving - Add prepare_image_inputs, expected_image_outputs for tests * Fix for oneformer
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@@ -22,7 +22,7 @@ import requests
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from transformers.testing_utils import require_torch, require_vision
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from transformers.utils import is_torch_available, is_vision_available
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from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
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from ...test_image_processing_common import ImageProcessingTestMixin, prepare_image_inputs
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if is_torch_available():
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@@ -73,6 +73,17 @@ class Pix2StructImageProcessingTester(unittest.TestCase):
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raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB")
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return raw_image
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def prepare_image_inputs(self, equal_resolution=False, numpify=False, torchify=False):
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return prepare_image_inputs(
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batch_size=self.batch_size,
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num_channels=self.num_channels,
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min_resolution=self.min_resolution,
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max_resolution=self.max_resolution,
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equal_resolution=equal_resolution,
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numpify=numpify,
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torchify=torchify,
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)
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@unittest.skipIf(
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not is_torch_greater_or_equal_than_1_11,
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@@ -80,7 +91,7 @@ class Pix2StructImageProcessingTester(unittest.TestCase):
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)
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@require_torch
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@require_vision
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class Pix2StructImageProcessingTest(ImageProcessingSavingTestMixin, unittest.TestCase):
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class Pix2StructImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase):
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image_processing_class = Pix2StructImageProcessor if is_vision_available() else None
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def setUp(self):
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@@ -108,7 +119,7 @@ class Pix2StructImageProcessingTest(ImageProcessingSavingTestMixin, unittest.Tes
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# Initialize image_processor
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image_processor = self.image_processing_class(**self.image_processor_dict)
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# create random PIL images
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image_inputs = prepare_image_inputs(self.image_processor_tester, equal_resolution=False)
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image_inputs = self.image_processor_tester.prepare_image_inputs(equal_resolution=False)
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for image in image_inputs:
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self.assertIsInstance(image, Image.Image)
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@@ -141,7 +152,7 @@ class Pix2StructImageProcessingTest(ImageProcessingSavingTestMixin, unittest.Tes
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# Initialize image_processor
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image_processor = self.image_processing_class(**self.image_processor_dict)
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# create random PIL images
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image_inputs = prepare_image_inputs(self.image_processor_tester, equal_resolution=False)
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image_inputs = self.image_processor_tester.prepare_image_inputs(equal_resolution=False)
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for image in image_inputs:
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self.assertIsInstance(image, Image.Image)
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@@ -183,7 +194,7 @@ class Pix2StructImageProcessingTest(ImageProcessingSavingTestMixin, unittest.Tes
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# Initialize image_processor
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image_processor = self.image_processing_class(**self.image_processor_dict)
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# create random numpy tensors
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image_inputs = prepare_image_inputs(self.image_processor_tester, equal_resolution=False, numpify=True)
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image_inputs = self.image_processor_tester.prepare_image_inputs(equal_resolution=False, numpify=True)
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for image in image_inputs:
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self.assertIsInstance(image, np.ndarray)
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@@ -215,7 +226,7 @@ class Pix2StructImageProcessingTest(ImageProcessingSavingTestMixin, unittest.Tes
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# Initialize image_processor
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image_processor = self.image_processing_class(**self.image_processor_dict)
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# create random PyTorch tensors
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image_inputs = prepare_image_inputs(self.image_processor_tester, equal_resolution=False, torchify=True)
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image_inputs = self.image_processor_tester.prepare_image_inputs(equal_resolution=False, torchify=True)
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for image in image_inputs:
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self.assertIsInstance(image, torch.Tensor)
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@@ -251,7 +262,7 @@ class Pix2StructImageProcessingTest(ImageProcessingSavingTestMixin, unittest.Tes
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)
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@require_torch
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@require_vision
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class Pix2StructImageProcessingTestFourChannels(ImageProcessingSavingTestMixin, unittest.TestCase):
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class Pix2StructImageProcessingTestFourChannels(ImageProcessingTestMixin, unittest.TestCase):
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image_processing_class = Pix2StructImageProcessor if is_vision_available() else None
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def setUp(self):
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@@ -267,11 +278,11 @@ class Pix2StructImageProcessingTestFourChannels(ImageProcessingSavingTestMixin,
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self.assertTrue(hasattr(image_processor, "do_normalize"))
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self.assertTrue(hasattr(image_processor, "do_convert_rgb"))
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def test_call_pil_four_channels(self):
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def test_call_pil(self):
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# Initialize image_processor
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image_processor = self.image_processing_class(**self.image_processor_dict)
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# create random PIL images
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image_inputs = prepare_image_inputs(self.image_processor_tester, equal_resolution=False)
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image_inputs = self.image_processor_tester.prepare_image_inputs(equal_resolution=False)
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for image in image_inputs:
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self.assertIsInstance(image, Image.Image)
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@@ -299,3 +310,11 @@ class Pix2StructImageProcessingTestFourChannels(ImageProcessingSavingTestMixin,
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encoded_images.shape,
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(self.image_processor_tester.batch_size, max_patch, expected_hidden_dim),
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)
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@unittest.skip("Pix2StructImageProcessor does not support 4 channels yet") # FIXME Amy
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def test_call_numpy(self):
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return super().test_call_numpy()
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@unittest.skip("Pix2StructImageProcessor does not support 4 channels yet") # FIXME Amy
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def test_call_pytorch(self):
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return super().test_call_torch()
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