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fix: Replace deprecated assertEquals with assertEqual (#30241)

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Replace deprecated assertEquals with assertEqual.
This commit is contained in:
Sai-Suraj-27
2024-04-15 14:06:06 +05:30
committed by GitHub
parent 8fd2de933c
commit 06b1192768
12 changed files with 36 additions and 36 deletions
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20
tests/models/encodec/test_feature_extraction_encodec.py
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@@ -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))