def test_save_load_pretrained_additional_features(self): processor = Wav2Vec2Processor( tokenizer=self.get_tokenizer(), feature_extractor=self.get_feature_extractor()) processor.save_pretrained(self.tmpdirname) tokenizer_add_kwargs = self.get_tokenizer(bos_token="(BOS)", eos_token="(EOS)") feature_extractor_add_kwargs = self.get_feature_extractor( do_normalize=False, padding_value=1.0) processor = Wav2Vec2Processor.from_pretrained(self.tmpdirname, bos_token="(BOS)", eos_token="(EOS)", do_normalize=False, padding_value=1.0) self.assertEqual(processor.tokenizer.get_vocab(), tokenizer_add_kwargs.get_vocab()) self.assertIsInstance(processor.tokenizer, Wav2Vec2CTCTokenizer) self.assertEqual(processor.feature_extractor.to_json_string(), feature_extractor_add_kwargs.to_json_string()) self.assertIsInstance(processor.feature_extractor, Wav2Vec2FeatureExtractor)
def test_save_load_pretrained_default(self): tokenizer = self.get_tokenizer() feature_extractor = self.get_feature_extractor() processor = Wav2Vec2Processor(tokenizer=tokenizer, feature_extractor=feature_extractor) processor.save_pretrained(self.tmpdirname) processor = Wav2Vec2Processor.from_pretrained(self.tmpdirname) self.assertEqual(processor.tokenizer.get_vocab(), tokenizer.get_vocab()) self.assertIsInstance(processor.tokenizer, Wav2Vec2CTCTokenizer) self.assertEqual(processor.feature_extractor.to_json_string(), feature_extractor.to_json_string()) self.assertIsInstance(processor.feature_extractor, Wav2Vec2FeatureExtractor)
def test_tokenizer_decode(self): feature_extractor = self.get_feature_extractor() tokenizer = self.get_tokenizer() processor = Wav2Vec2Processor(tokenizer=tokenizer, feature_extractor=feature_extractor) predicted_ids = [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]] decoded_processor = processor.batch_decode(predicted_ids) decoded_tok = tokenizer.batch_decode(predicted_ids) self.assertListEqual(decoded_tok, decoded_processor)
def test_feature_extractor(self): feature_extractor = self.get_feature_extractor() tokenizer = self.get_tokenizer() processor = Wav2Vec2Processor(tokenizer=tokenizer, feature_extractor=feature_extractor) raw_speech = floats_list((3, 1000)) input_feat_extract = feature_extractor(raw_speech, return_tensors="np") input_processor = processor(raw_speech, return_tensors="np") for key in input_feat_extract.keys(): self.assertAlmostEqual(input_feat_extract[key].sum(), input_processor[key].sum(), delta=1e-2)
def test_tokenizer(self): feature_extractor = self.get_feature_extractor() tokenizer = self.get_tokenizer() processor = Wav2Vec2Processor(tokenizer=tokenizer, feature_extractor=feature_extractor) input_str = "This is a test string" encoded_processor = processor(text=input_str) encoded_tok = tokenizer(input_str) for key in encoded_tok.keys(): self.assertListEqual(encoded_tok[key], encoded_processor[key])