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kwargs for Whisper methods #108

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kwargs for Whisper methods #108

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f611479
feat: accept kwargs for whisper mixin
iyaja Mar 6, 2024
11f77d0
feat: skip special tokens
iyaja Mar 6, 2024
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13 changes: 7 additions & 6 deletions audiotools/core/whisper.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ def setup_whisper(
).to(self.whisper_device)
self.is_initialized = True

def get_whisper_features(self) -> torch.Tensor:
def get_whisper_features(self, **kwargs) -> torch.Tensor:
"""Preprocess audio signal as per the whisper model's training config.

Returns
Expand Down Expand Up @@ -49,11 +49,12 @@ def get_whisper_features(self) -> torch.Tensor:
raw_speech,
sampling_rate=self.whisper_processor.feature_extractor.sampling_rate,
return_tensors="pt",
**kwargs
).input_features

return input_features

def get_whisper_transcript(self) -> str:
def get_whisper_transcript(self, **kwargs) -> str:
"""Get the transcript of the audio signal using the whisper model.

Returns
Expand All @@ -69,12 +70,12 @@ def get_whisper_transcript(self) -> str:

with torch.inference_mode():
input_features = input_features.to(self.whisper_device)
generated_ids = self.whisper_model.generate(inputs=input_features)
generated_ids = self.whisper_model.generate(input_features=input_features, **kwargs)

transcription = self.whisper_processor.batch_decode(generated_ids)
transcription = self.whisper_processor.batch_decode(generated_ids, skip_special_tokens=True)
return transcription[0]

def get_whisper_embeddings(self) -> torch.Tensor:
def get_whisper_embeddings(self, **kwargs) -> torch.Tensor:
"""Get the last hidden state embeddings of the audio signal using the whisper model.

Returns
Expand All @@ -92,6 +93,6 @@ def get_whisper_embeddings(self) -> torch.Tensor:

with torch.inference_mode():
input_features = input_features.to(self.whisper_device)
embeddings = encoder(input_features)
embeddings = encoder(input_features, **kwargs)

return embeddings.last_hidden_state