Upload wav2vec_aligen.py

wav2vec_aligen.py

@@ -3,19 +3,19 @@ import librosa
 import os
 from model import Wav2Vec2BertForSequenceClassification
 from transformers import AutoFeatureExtractor
-from optimum.bettertransformer import BetterTransformer
+# from optimum.bettertransformer import BetterTransformer
 
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
-os.environ['PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION'] = 'python'
-os.environ['TRANSFORMERS_NO_ADVISORY_WARNINGS'] = '1'
-os.environ['TRANSFORMERS_VERBOSITY'] = 'error'
+# os.environ['PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION'] = 'python'
+# os.environ['TRANSFORMERS_NO_ADVISORY_WARNINGS'] = '1'
+# os.environ['TRANSFORMERS_VERBOSITY'] = 'error'
 torch.random.manual_seed(0); 
 # protobuf==3.20.0
 
 model_name = "arslanarjumand/wav2vec-reptiles"
 processor = AutoFeatureExtractor.from_pretrained(model_name)
 model = Wav2Vec2BertForSequenceClassification.from_pretrained(model_name).to(device)
-model = BetterTransformer.transform(model)
+# model = BetterTransformer.transform(model)
 
 def load_audio(audio_path, processor):
     audio, sr = librosa.load(audio_path, sr=16000)