From 06b1192768220b77d8f5a22031ed081e79df1616 Mon Sep 17 00:00:00 2001 From: Sai-Suraj-27 Date: Mon, 15 Apr 2024 14:06:06 +0530 Subject: [PATCH] fix: Replace deprecated `assertEquals` with `assertEqual` (#30241) Replace deprecated assertEquals with assertEqual. --- ...xtraction_audio_spectrogram_transformer.py | 2 +- .../test_feature_extraction_encodec.py | 20 +++++++++---------- tests/models/git/test_modeling_git.py | 6 +++--- .../test_image_processing_mask2former.py | 12 +++++------ .../test_image_processing_maskformer.py | 12 +++++------ .../rembert/test_tokenization_rembert.py | 4 ++-- .../test_feature_extraction_speech_to_text.py | 2 +- .../test_feature_extraction_speecht5.py | 4 ++-- .../tvlt/test_feature_extraction_tvlt.py | 2 +- tests/models/udop/test_modeling_udop.py | 2 +- tests/test_modeling_flax_common.py | 2 +- tests/test_tokenization_common.py | 4 ++-- 12 files changed, 36 insertions(+), 36 deletions(-) diff --git a/tests/models/audio_spectrogram_transformer/test_feature_extraction_audio_spectrogram_transformer.py b/tests/models/audio_spectrogram_transformer/test_feature_extraction_audio_spectrogram_transformer.py index ac6cd5eb1f..fbe2509086 100644 --- a/tests/models/audio_spectrogram_transformer/test_feature_extraction_audio_spectrogram_transformer.py +++ b/tests/models/audio_spectrogram_transformer/test_feature_extraction_audio_spectrogram_transformer.py @@ -173,7 +173,7 @@ class ASTFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Test input_speech = self._load_datasamples(1) feature_extractor = ASTFeatureExtractor() input_values = feature_extractor(input_speech, return_tensors="pt").input_values - self.assertEquals(input_values.shape, (1, 1024, 128)) + self.assertEqual(input_values.shape, (1, 1024, 128)) self.assertTrue(torch.allclose(input_values[0, 0, :30], EXPECTED_INPUT_VALUES, atol=1e-4)) def test_feat_extract_from_and_save_pretrained(self): diff --git a/tests/models/encodec/test_feature_extraction_encodec.py b/tests/models/encodec/test_feature_extraction_encodec.py index 5a8010d247..e56517ac41 100644 --- a/tests/models/encodec/test_feature_extraction_encodec.py +++ b/tests/models/encodec/test_feature_extraction_encodec.py @@ -158,7 +158,7 @@ class EnCodecFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest. input_audio = self._load_datasamples(1) feature_extractor = EncodecFeatureExtractor() input_values = feature_extractor(input_audio, return_tensors="pt").input_values - self.assertEquals(input_values.shape, (1, 1, 93680)) + self.assertEqual(input_values.shape, (1, 1, 93680)) self.assertTrue(torch.allclose(input_values[0, 0, :30], EXPECTED_INPUT_VALUES, atol=1e-6)) def test_integration_stereo(self): @@ -177,7 +177,7 @@ class EnCodecFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest. input_audio[0][1] *= 0.5 feature_extractor = EncodecFeatureExtractor(feature_size=2) input_values = feature_extractor(input_audio, return_tensors="pt").input_values - self.assertEquals(input_values.shape, (1, 2, 93680)) + self.assertEqual(input_values.shape, (1, 2, 93680)) self.assertTrue(torch.allclose(input_values[0, 0, :30], EXPECTED_INPUT_VALUES, atol=1e-6)) self.assertTrue(torch.allclose(input_values[0, 1, :30], EXPECTED_INPUT_VALUES * 0.5, atol=1e-6)) @@ -197,27 +197,27 @@ class EnCodecFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest. # truncate to chunk truncated_outputs = feature_extractor(input_audio, truncation=True, return_tensors="pt").input_values - self.assertEquals(truncated_outputs.shape, (2, 1, 71520)) # 2 chunks + self.assertEqual(truncated_outputs.shape, (2, 1, 71520)) # 2 chunks # force truncate to max_length truncated_outputs = feature_extractor( input_audio, truncation=True, max_length=48000, return_tensors="pt" ).input_values - self.assertEquals(truncated_outputs.shape, (2, 1, 48000)) + self.assertEqual(truncated_outputs.shape, (2, 1, 48000)) # pad to chunk padded_outputs = feature_extractor(input_audio, padding=True, return_tensors="pt").input_values - self.assertEquals(padded_outputs.shape, (2, 1, 95280)) + self.assertEqual(padded_outputs.shape, (2, 1, 95280)) # pad to chunk truncated_outputs = feature_extractor(input_audio, return_tensors="pt").input_values - self.assertEquals(truncated_outputs.shape, (2, 1, 95280)) + self.assertEqual(truncated_outputs.shape, (2, 1, 95280)) # force pad to max length truncated_outputs = feature_extractor( input_audio, padding="max_length", max_length=100000, return_tensors="pt" ).input_values - self.assertEquals(truncated_outputs.shape, (2, 1, 100000)) + self.assertEqual(truncated_outputs.shape, (2, 1, 100000)) # force no pad with self.assertRaisesRegex( @@ -227,7 +227,7 @@ class EnCodecFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest. truncated_outputs = feature_extractor(input_audio, padding=False, return_tensors="pt").input_values truncated_outputs = feature_extractor(input_audio[0], padding=False, return_tensors="pt").input_values - self.assertEquals(truncated_outputs.shape, (1, 1, 93680)) + self.assertEqual(truncated_outputs.shape, (1, 1, 93680)) # no pad if no chunk_length_s feature_extractor.chunk_length_s = None @@ -238,7 +238,7 @@ class EnCodecFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest. truncated_outputs = feature_extractor(input_audio, padding=False, return_tensors="pt").input_values truncated_outputs = feature_extractor(input_audio[0], padding=False, return_tensors="pt").input_values - self.assertEquals(truncated_outputs.shape, (1, 1, 93680)) + self.assertEqual(truncated_outputs.shape, (1, 1, 93680)) # no pad if no overlap feature_extractor.chunk_length_s = 2 @@ -250,4 +250,4 @@ class EnCodecFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest. truncated_outputs = feature_extractor(input_audio, padding=False, return_tensors="pt").input_values truncated_outputs = feature_extractor(input_audio[0], padding=False, return_tensors="pt").input_values - self.assertEquals(truncated_outputs.shape, (1, 1, 93680)) + self.assertEqual(truncated_outputs.shape, (1, 1, 93680)) diff --git a/tests/models/git/test_modeling_git.py b/tests/models/git/test_modeling_git.py index 6a891f17b0..0ef74d8184 100644 --- a/tests/models/git/test_modeling_git.py +++ b/tests/models/git/test_modeling_git.py @@ -510,7 +510,7 @@ class GitModelIntegrationTest(unittest.TestCase): expected_shape = torch.Size((1, 9)) self.assertEqual(outputs.sequences.shape, expected_shape) - self.assertEquals(generated_caption, "two cats laying on a pink blanket") + self.assertEqual(generated_caption, "two cats laying on a pink blanket") self.assertTrue(outputs.scores[-1].shape, expected_shape) expected_slice = torch.tensor([[-0.8805, -0.8803, -0.8799]], device=torch_device) self.assertTrue(torch.allclose(outputs.scores[-1][0, :3], expected_slice, atol=1e-4)) @@ -537,7 +537,7 @@ class GitModelIntegrationTest(unittest.TestCase): expected_shape = torch.Size((1, 15)) self.assertEqual(generated_ids.shape, expected_shape) - self.assertEquals(generated_caption, "what does the front of the bus say at the top? special") + self.assertEqual(generated_caption, "what does the front of the bus say at the top? special") def test_batched_generation(self): processor = GitProcessor.from_pretrained("microsoft/git-base-coco") @@ -555,4 +555,4 @@ class GitModelIntegrationTest(unittest.TestCase): generated_ids = model.generate(pixel_values=pixel_values, input_ids=input_ids, max_length=50) generated_captions = processor.batch_decode(generated_ids, skip_special_tokens=True) - self.assertEquals(generated_captions, ["two cats sleeping on a pink blanket next to remotes."] * 2) + self.assertEqual(generated_captions, ["two cats sleeping on a pink blanket next to remotes."] * 2) diff --git a/tests/models/mask2former/test_image_processing_mask2former.py b/tests/models/mask2former/test_image_processing_mask2former.py index 24d5b8cf89..9b9e46907b 100644 --- a/tests/models/mask2former/test_image_processing_mask2former.py +++ b/tests/models/mask2former/test_image_processing_mask2former.py @@ -297,8 +297,8 @@ class Mask2FormerImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase self.assertEqual(len(inputs["mask_labels"]), 2) self.assertEqual(inputs["mask_labels"][0].shape, (2, 512, 512)) self.assertEqual(inputs["mask_labels"][1].shape, (4, 512, 512)) - self.assertEquals(inputs["mask_labels"][0].sum().item(), 41527.0) - self.assertEquals(inputs["mask_labels"][1].sum().item(), 26259.0) + self.assertEqual(inputs["mask_labels"][0].sum().item(), 41527.0) + self.assertEqual(inputs["mask_labels"][1].sum().item(), 26259.0) def test_integration_semantic_segmentation(self): # load 2 images and corresponding semantic annotations from the hub @@ -339,8 +339,8 @@ class Mask2FormerImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase self.assertEqual(len(inputs["mask_labels"]), 2) self.assertEqual(inputs["mask_labels"][0].shape, (3, 512, 512)) self.assertEqual(inputs["mask_labels"][1].shape, (8, 512, 512)) - self.assertEquals(inputs["mask_labels"][0].sum().item(), 170200.0) - self.assertEquals(inputs["mask_labels"][1].sum().item(), 257036.0) + self.assertEqual(inputs["mask_labels"][0].sum().item(), 170200.0) + self.assertEqual(inputs["mask_labels"][1].sum().item(), 257036.0) def test_integration_panoptic_segmentation(self): # load 2 images and corresponding panoptic annotations from the hub @@ -400,8 +400,8 @@ class Mask2FormerImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase self.assertEqual(len(inputs["mask_labels"]), 2) self.assertEqual(inputs["mask_labels"][0].shape, (79, 512, 711)) self.assertEqual(inputs["mask_labels"][1].shape, (61, 512, 711)) - self.assertEquals(inputs["mask_labels"][0].sum().item(), 315193.0) - self.assertEquals(inputs["mask_labels"][1].sum().item(), 350747.0) + self.assertEqual(inputs["mask_labels"][0].sum().item(), 315193.0) + self.assertEqual(inputs["mask_labels"][1].sum().item(), 350747.0) def test_binary_mask_to_rle(self): fake_binary_mask = np.zeros((20, 50)) diff --git a/tests/models/maskformer/test_image_processing_maskformer.py b/tests/models/maskformer/test_image_processing_maskformer.py index e4779f896a..dcb0a04f57 100644 --- a/tests/models/maskformer/test_image_processing_maskformer.py +++ b/tests/models/maskformer/test_image_processing_maskformer.py @@ -297,8 +297,8 @@ class MaskFormerImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase) self.assertEqual(len(inputs["mask_labels"]), 2) self.assertEqual(inputs["mask_labels"][0].shape, (2, 512, 512)) self.assertEqual(inputs["mask_labels"][1].shape, (4, 512, 512)) - self.assertEquals(inputs["mask_labels"][0].sum().item(), 41527.0) - self.assertEquals(inputs["mask_labels"][1].sum().item(), 26259.0) + self.assertEqual(inputs["mask_labels"][0].sum().item(), 41527.0) + self.assertEqual(inputs["mask_labels"][1].sum().item(), 26259.0) def test_integration_semantic_segmentation(self): # load 2 images and corresponding semantic annotations from the hub @@ -339,8 +339,8 @@ class MaskFormerImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase) self.assertEqual(len(inputs["mask_labels"]), 2) self.assertEqual(inputs["mask_labels"][0].shape, (3, 512, 512)) self.assertEqual(inputs["mask_labels"][1].shape, (8, 512, 512)) - self.assertEquals(inputs["mask_labels"][0].sum().item(), 170200.0) - self.assertEquals(inputs["mask_labels"][1].sum().item(), 257036.0) + self.assertEqual(inputs["mask_labels"][0].sum().item(), 170200.0) + self.assertEqual(inputs["mask_labels"][1].sum().item(), 257036.0) def test_integration_panoptic_segmentation(self): # load 2 images and corresponding panoptic annotations from the hub @@ -400,8 +400,8 @@ class MaskFormerImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase) self.assertEqual(len(inputs["mask_labels"]), 2) self.assertEqual(inputs["mask_labels"][0].shape, (79, 512, 711)) self.assertEqual(inputs["mask_labels"][1].shape, (61, 512, 711)) - self.assertEquals(inputs["mask_labels"][0].sum().item(), 315193.0) - self.assertEquals(inputs["mask_labels"][1].sum().item(), 350747.0) + self.assertEqual(inputs["mask_labels"][0].sum().item(), 315193.0) + self.assertEqual(inputs["mask_labels"][1].sum().item(), 350747.0) def test_binary_mask_to_rle(self): fake_binary_mask = np.zeros((20, 50)) diff --git a/tests/models/rembert/test_tokenization_rembert.py b/tests/models/rembert/test_tokenization_rembert.py index 5f65629213..096106a2fc 100644 --- a/tests/models/rembert/test_tokenization_rembert.py +++ b/tests/models/rembert/test_tokenization_rembert.py @@ -88,13 +88,13 @@ class RemBertTokenizationTest(TokenizerTesterMixin, unittest.TestCase): encoded_string = tokenizer.encode(text) self.assertListEqual(encoded_string, [1000, 7, 0, 1001]) decode_text = tokenizer.convert_tokens_to_string(tokens) - self.assertEquals(decode_text, text) + self.assertEqual(decode_text, text) text = "That's awesome! 🀩 #HuggingFace, 🌟 Have a great day! 🌈" tokens = tokenizer.tokenize(text) self.assertListEqual( tokens, ['▁That', "'", 's', '▁a', 'w', 'es', 'ome', '!', '▁', '🀩', '▁', '#', 'H', 'u', 'g', 'g', 'ing', 'F', 'a', 'ce', ',', '▁', '🌟', '▁H', 'a', 've', '▁a', '▁great', '▁day', '!', '▁', '🌈']) # fmt: skip decode_text = tokenizer.convert_tokens_to_string(tokens) - self.assertEquals(decode_text, "That's awesome! 🀩 #HuggingFace, 🌟 Have a great day! 🌈") + self.assertEqual(decode_text, "That's awesome! 🀩 #HuggingFace, 🌟 Have a great day! 🌈") text = "In the sky up above" tokens = tokenizer._tokenize(text) diff --git a/tests/models/speech_to_text/test_feature_extraction_speech_to_text.py b/tests/models/speech_to_text/test_feature_extraction_speech_to_text.py index f652d09ffc..9023e8467f 100644 --- a/tests/models/speech_to_text/test_feature_extraction_speech_to_text.py +++ b/tests/models/speech_to_text/test_feature_extraction_speech_to_text.py @@ -277,7 +277,7 @@ class Speech2TextFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unitt input_speech = self._load_datasamples(1) feature_extractor = self.feature_extraction_class(**self.feat_extract_tester.prepare_feat_extract_dict()) input_features = feature_extractor(input_speech, return_tensors="pt").input_features - self.assertEquals(input_features.shape, (1, 584, 24)) + self.assertEqual(input_features.shape, (1, 584, 24)) self.assertTrue(np.allclose(input_features[0, 0, :30], expected, atol=1e-4)) def test_feat_extract_from_and_save_pretrained(self): diff --git a/tests/models/speecht5/test_feature_extraction_speecht5.py b/tests/models/speecht5/test_feature_extraction_speecht5.py index 22d99a8180..5ec632e7e7 100644 --- a/tests/models/speecht5/test_feature_extraction_speecht5.py +++ b/tests/models/speecht5/test_feature_extraction_speecht5.py @@ -401,7 +401,7 @@ class SpeechT5FeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest input_speech = self._load_datasamples(1) feature_extractor = SpeechT5FeatureExtractor() input_values = feature_extractor(input_speech, return_tensors="pt").input_values - self.assertEquals(input_values.shape, (1, 93680)) + self.assertEqual(input_values.shape, (1, 93680)) self.assertTrue(torch.allclose(input_values[0, :30], EXPECTED_INPUT_VALUES, atol=1e-6)) def test_integration_target(self): @@ -417,5 +417,5 @@ class SpeechT5FeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest input_speech = self._load_datasamples(1) feature_extractor = SpeechT5FeatureExtractor() input_values = feature_extractor(audio_target=input_speech, return_tensors="pt").input_values - self.assertEquals(input_values.shape, (1, 366, 80)) + self.assertEqual(input_values.shape, (1, 366, 80)) self.assertTrue(torch.allclose(input_values[0, 0, :30], EXPECTED_INPUT_VALUES, atol=1e-4)) diff --git a/tests/models/tvlt/test_feature_extraction_tvlt.py b/tests/models/tvlt/test_feature_extraction_tvlt.py index e2d8c624b0..cd737d5a8f 100644 --- a/tests/models/tvlt/test_feature_extraction_tvlt.py +++ b/tests/models/tvlt/test_feature_extraction_tvlt.py @@ -176,7 +176,7 @@ class TvltFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Tes feature_extractor = TvltFeatureExtractor() audio_values = feature_extractor(input_speech, return_tensors="pt").audio_values - self.assertEquals(audio_values.shape, (1, 1, 192, 128)) + self.assertEqual(audio_values.shape, (1, 1, 192, 128)) expected_slice = torch.tensor([[-0.3032, -0.2708], [-0.4434, -0.4007]]) self.assertTrue(torch.allclose(audio_values[0, 0, :2, :2], expected_slice, atol=1e-4)) diff --git a/tests/models/udop/test_modeling_udop.py b/tests/models/udop/test_modeling_udop.py index 257f6245ee..63e7a2fa78 100644 --- a/tests/models/udop/test_modeling_udop.py +++ b/tests/models/udop/test_modeling_udop.py @@ -574,4 +574,4 @@ class UdopModelIntegrationTests(unittest.TestCase): predicted_ids = model.generate(**encoding) predicted_text = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0] - self.assertEquals(predicted_text, "2013") + self.assertEqual(predicted_text, "2013") diff --git a/tests/test_modeling_flax_common.py b/tests/test_modeling_flax_common.py index ef99786fdf..22d6b241f0 100644 --- a/tests/test_modeling_flax_common.py +++ b/tests/test_modeling_flax_common.py @@ -792,7 +792,7 @@ class FlaxModelTesterMixin: types = flatten_dict(types) for name, type_ in types.items(): - self.assertEquals(type_, jnp.float32, msg=f"param {name} is not initialized in fp32.") + self.assertEqual(type_, jnp.float32, msg=f"param {name} is not initialized in fp32.") def test_to_bf16(self): config, _ = self.model_tester.prepare_config_and_inputs_for_common() diff --git a/tests/test_tokenization_common.py b/tests/test_tokenization_common.py index e98f09d431..76402cd092 100644 --- a/tests/test_tokenization_common.py +++ b/tests/test_tokenization_common.py @@ -1608,7 +1608,7 @@ class TokenizerTesterMixin: with self.subTest(f"{(chunk/len(input_full_vocab_string))*100}%"): slow_encode = slow_tokenizer.encode(string_to_check) fast_encode = rust_tokenizer.encode(string_to_check) - self.assertEquals( + self.assertEqual( slow_encode, fast_encode, "Hint: the following tokenization diff were obtained for slow vs fast:\n " @@ -1620,7 +1620,7 @@ class TokenizerTesterMixin: for chunk in range(0, len(input_full_vocab_ids) - 100, 100): ids_to_decode = input_full_vocab_ids[chunk : chunk + 100] with self.subTest(f"{(chunk/len(input_full_vocab_string))*100}%"): - self.assertEquals( + self.assertEqual( slow_tokenizer.decode( ids_to_decode, space_between_special_tokens=False,