DeepLearningExamples/PyTorch/SpeechSynthesis/Tacotron2/data_functions.py

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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=1):
    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