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Fix test typos - audio feature extractors (#23310)

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This commit is contained in:
LWprogramming
2023-05-15 09:22:10 -07:00
committed by GitHub
parent 8f76dc8e5a
commit ee3be05310
3 changed files with 5 additions and 5 deletions
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4
tests/models/mctct/test_feature_extraction_mctct.py
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@@ -114,8 +114,8 @@ class MCTCTFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Te
def test_call(self): def test_call(self):
# Tests that all call wrap to encode_plus and batch_encode_plus # Tests that all call wrap to encode_plus and batch_encode_plus
feature_extractor = self.feature_extraction_class(**self.feat_extract_tester.prepare_feat_extract_dict()) feature_extractor = self.feature_extraction_class(**self.feat_extract_tester.prepare_feat_extract_dict())
# create three inputs of length 800, 1000, and 12000 # create three inputs of length 800, 1000, and 1200
speech_inputs = [floats_list((1, x))[0] for x in range(8000, 14000, 2000)] speech_inputs = [floats_list((1, x))[0] for x in range(800, 1400, 200)]
np_speech_inputs = [np.asarray(speech_input) for speech_input in speech_inputs] np_speech_inputs = [np.asarray(speech_input) for speech_input in speech_inputs]
# Test feature size # Test feature size

4
tests/models/speecht5/test_feature_extraction_speecht5.py
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@@ -255,8 +255,8 @@ class SpeechT5FeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest
def test_call_target(self): def test_call_target(self):
# Tests that all call wrap to encode_plus and batch_encode_plus # Tests that all call wrap to encode_plus and batch_encode_plus
feature_extractor = self.feature_extraction_class(**self.feat_extract_tester.prepare_feat_extract_dict()) feature_extractor = self.feature_extraction_class(**self.feat_extract_tester.prepare_feat_extract_dict())
# create three inputs of length 8000, 14000, and 2000 # create three inputs of length 800, 1000, and 1200
speech_inputs = [floats_list((1, x))[0] for x in range(8000, 14000, 2000)] speech_inputs = [floats_list((1, x))[0] for x in range(800, 1400, 200)]
np_speech_inputs = [np.asarray(speech_input) for speech_input in speech_inputs] np_speech_inputs = [np.asarray(speech_input) for speech_input in speech_inputs]
# Test feature size # Test feature size

2
tests/models/tvlt/test_feature_extraction_tvlt.py
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@@ -160,7 +160,7 @@ class TvltFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Tes
feature_extractor = self.feature_extraction_class(**self.feat_extract_dict) feature_extractor = self.feature_extraction_class(**self.feat_extract_dict)
# create three inputs of length 800, 1000, and 1200 # create three inputs of length 800, 1000, and 1200
speech_inputs = [floats_list((1, x))[0] for x in range(8000, 14000, 20000)] speech_inputs = [floats_list((1, x))[0] for x in range(800, 1400, 200)]
np_speech_inputs = [np.asarray(speech_input) for speech_input in speech_inputs] np_speech_inputs = [np.asarray(speech_input) for speech_input in speech_inputs]
# Test not batched input # Test not batched input