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Add AutoFeatureExtractor support to Wav2Vec2ProcessorWithLM (#28706)

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* Add AutoFeatureExtractor support to Wav2Vec2ProcessorWithLM

* update with a type filter

* add raises error test

* fix added test
This commit is contained in:
Yoach Lacombe
2024-05-20 13:40:42 +02:00
committed by GitHub
parent c11ac7857b
commit e6708709cb
2 changed files with 43 additions and 9 deletions
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31
tests/models/wav2vec2_with_lm/test_processor_wav2vec2_with_lm.py
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@@ -25,7 +25,7 @@ import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from transformers import AutoFeatureExtractor, AutoProcessor
from transformers.models.wav2vec2 import Wav2Vec2CTCTokenizer, Wav2Vec2FeatureExtractor
from transformers.models.wav2vec2.tokenization_wav2vec2 import VOCAB_FILES_NAMES
from transformers.testing_utils import require_pyctcdecode, require_torch, require_torchaudio, slow
@@ -157,6 +157,35 @@ class Wav2Vec2ProcessorWithLMTest(unittest.TestCase):
for key in input_feat_extract.keys():
self.assertAlmostEqual(input_feat_extract[key].sum(), input_processor[key].sum(), delta=1e-2)
def test_another_feature_extractor(self):
feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/w2v-bert-2.0")
tokenizer = self.get_tokenizer()
decoder = self.get_decoder()
processor = Wav2Vec2ProcessorWithLM(tokenizer=tokenizer, feature_extractor=feature_extractor, decoder=decoder)
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)
self.assertListEqual(
processor.model_input_names,
feature_extractor.model_input_names,
msg="`processor` and `feature_extractor` model input names do not match",
)
def test_wrong_feature_extractor_raises_error(self):
feature_extractor = AutoFeatureExtractor.from_pretrained("openai/whisper-large-v3")
tokenizer = self.get_tokenizer()
decoder = self.get_decoder()
with self.assertRaises(ValueError):
Wav2Vec2ProcessorWithLM(tokenizer=tokenizer, feature_extractor=feature_extractor, decoder=decoder)
def test_tokenizer(self):
feature_extractor = self.get_feature_extractor()
tokenizer = self.get_tokenizer()