DeepLearningExamples/PyTorch/SpeechSynthesis/Tacotron2/data_functions.py

69 lines
3.1 KiB
Python

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import torch
from tacotron2.data_function import TextMelCollate
from tacotron2.data_function import TextMelLoader
from waveglow.data_function import MelAudioLoader
from tacotron2.data_function import batch_to_gpu as batch_to_gpu_tacotron2
from waveglow.data_function import batch_to_gpu as batch_to_gpu_waveglow
def get_collate_function(model_name, n_frames_per_step):
if model_name == 'Tacotron2':
collate_fn = TextMelCollate(n_frames_per_step)
elif model_name == 'WaveGlow':
collate_fn = torch.utils.data.dataloader.default_collate
else:
raise NotImplementedError(
"unknown collate function requested: {}".format(model_name))
return collate_fn
def get_data_loader(model_name, dataset_path, audiopaths_and_text, args):
if model_name == 'Tacotron2':
data_loader = TextMelLoader(dataset_path, audiopaths_and_text, args)
elif model_name == 'WaveGlow':
data_loader = MelAudioLoader(dataset_path, audiopaths_and_text, args)
else:
raise NotImplementedError(
"unknown data loader requested: {}".format(model_name))
return data_loader
def get_batch_to_gpu(model_name):
if model_name == 'Tacotron2':
batch_to_gpu = batch_to_gpu_tacotron2
elif model_name == 'WaveGlow':
batch_to_gpu = batch_to_gpu_waveglow
else:
raise NotImplementedError(
"unknown batch_to_gpu requested: {}".format(model_name))
return batch_to_gpu