def create_datasets(self):
root = self.config.data_params.librispeech_root
print('Initializing train dataset.')
train_dataset = LibriSpeech(root, train=True,
spectral_transforms=self.config.data_params.spectral_transforms,
wavform_transforms=self.config.data_params.wavform_transforms,
train_urls=self.config.data_params.train_urls)
print('Initializing validation dataset.')
val_dataset = LibriSpeech(root, train=False,
spectral_transforms=self.config.data_params.spectral_transforms,
wavform_transforms=self.config.data_params.wavform_transforms,
# use the same split so same speakers
test_url=self.config.data_params.test_url)
return train_dataset, val_dataset
def create_datasets(self):
train_dataset = LibriSpeech(
train=True,
spectral_transforms=False,
wavform_transforms=False,
small=self.config.data_params.small,
input_size=self.config.data_params.input_size,
)
val_dataset = LibriSpeech(
train=False,
spectral_transforms=False,
wavform_transforms=False,
small=self.config.data_params.small,
test_url=self.config.data_params.test_url,
input_size=self.config.data_params.input_size,
)
return train_dataset, val_dataset
def create_datasets(self):
print('Initializing train dataset.')
train_dataset = LibriSpeech(
train=True,
spectral_transforms=self.config.data_params.spectral_transforms,
wavform_transforms=not self.config.data_params.spectral_transforms,
small=self.config.data_params.small,
input_size=self.config.data_params.input_size,
)
print('Initializing validation dataset.')
val_dataset = LibriSpeech(
train=False,
spectral_transforms=False,
wavform_transforms=False,
small=self.config.data_params.small,
test_url=self.config.data_params.test_url,
input_size=self.config.data_params.input_size,
)
return train_dataset, val_dataset