forked from mrq/DL-Art-School
Oh yeah
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@ -7,7 +7,7 @@ from munch import munchify
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from utils.util import opt_get
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def create_dataloader(dataset, dataset_opt, opt=None, sampler=None, collate_fn=None):
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def create_dataloader(dataset, dataset_opt, opt=None, sampler=None, collate_fn=None, shuffle=True):
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phase = dataset_opt['phase']
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if phase == 'train':
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if opt_get(opt, ['dist'], False):
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@ -15,11 +15,9 @@ def create_dataloader(dataset, dataset_opt, opt=None, sampler=None, collate_fn=N
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num_workers = dataset_opt['n_workers']
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assert dataset_opt['batch_size'] % world_size == 0
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batch_size = dataset_opt['batch_size'] // world_size
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shuffle = False
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else:
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num_workers = dataset_opt['n_workers']
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batch_size = dataset_opt['batch_size']
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shuffle = True
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return torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=shuffle,
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num_workers=num_workers, sampler=sampler, drop_last=True,
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pin_memory=True, collate_fn=collate_fn)
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@ -77,6 +75,12 @@ def create_dataset(dataset_opt, return_collate=False):
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collate = C(dataset_opt)
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elif mode == 'wavfile_clips':
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from data.audio.wavfile_dataset import WavfileDataset as D
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elif mode == 'stop_prediction':
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from models.tacotron2.hparams import create_hparams
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default_params = create_hparams()
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default_params.update(dataset_opt)
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dataset_opt = munchify(default_params)
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from data.audio.stop_prediction_dataset import StopPredictionDataset as D
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else:
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raise NotImplementedError('Dataset [{:s}] is not recognized.'.format(mode))
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dataset = D(dataset_opt)
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