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Ensure preprocessor is in CPU
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@ -29,3 +29,6 @@ class PreprocessorProtocol(Protocol):
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def process_numpy(self, wav: np.ndarray) -> np.ndarray:
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def process_numpy(self, wav: np.ndarray) -> np.ndarray:
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return self(torch.tensor(wav)).numpy()
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return self(torch.tensor(wav)).numpy()
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def cpu(self) -> "PreprocessorProtocol":
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return self
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@ -272,7 +272,7 @@ def build_train_dataset(
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audio_loader=audio_loader,
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audio_loader=audio_loader,
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labeller=labeller,
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labeller=labeller,
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clipper=clipper,
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clipper=clipper,
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preprocessor=preprocessor,
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preprocessor=preprocessor.cpu(),
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audio_augmentation=audio_augmentation,
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audio_augmentation=audio_augmentation,
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spectrogram_augmentation=spectrogram_augmentation,
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spectrogram_augmentation=spectrogram_augmentation,
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)
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)
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@ -305,7 +305,7 @@ def build_val_dataset(
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clip_annotations,
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clip_annotations,
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audio_loader=audio_loader,
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audio_loader=audio_loader,
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labeller=labeller,
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labeller=labeller,
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preprocessor=preprocessor,
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preprocessor=preprocessor.cpu(),
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clipper=clipper,
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clipper=clipper,
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)
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)
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@ -73,8 +73,9 @@ def run_train(
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audio_loader = audio_loader or build_audio_loader(config=audio_config)
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audio_loader = audio_loader or build_audio_loader(config=audio_config)
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# NOTE: Create a new preprocessor instead of using the one from the model
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if model is not None:
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# to avoid issues with device placement.
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preprocessor = preprocessor or model.preprocessor
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preprocessor = preprocessor or build_preprocessor(
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preprocessor = preprocessor or build_preprocessor(
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input_samplerate=audio_loader.samplerate,
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input_samplerate=audio_loader.samplerate,
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config=model_config.preprocess,
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config=model_config.preprocess,
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