def load_dataset(args):
train_dataset = KORDataset(args.data_path, True, 0.1)
test_dataset = KORDataset(args.data_path, False, 0.1)
collate_fn1 = lambda batch: collate_fn_tr(batch, args.max_time_steps, args.
hop_length)
collate_fn2 = lambda batch: collate_fn_synth(batch, args.hop_length)
train_loader = DataLoader(train_dataset,
batch_size=args.bsz,
shuffle=True,
collate_fn=collate_fn1,
num_workers=args.num_workers,
pin_memory=True)
test_loader = DataLoader(test_dataset,
batch_size=args.bsz,
collate_fn=collate_fn1,
num_workers=args.num_workers,
pin_memory=True)
synth_loader = DataLoader(test_dataset,
batch_size=1,
collate_fn=collate_fn2,
num_workers=args.num_workers,
pin_memory=True)
print('num of train samples', len(train_loader))
print('num of test samples', len(test_loader))
return train_loader, test_loader, synth_loader
def load_dataset(args):
collate_fn2 = lambda batch: collate_fn_synth(batch, args.hop_length)
test_dataset = KORDataset(args.data_path, False, 0.1)
synth_loader = DataLoader(test_dataset, batch_size=1, collate_fn=collate_fn2,
num_workers=args.num_workers, pin_memory=True)
print('sr', args.sr)
return synth_loader
def load_dataset(args):
train_dataset = KORDataset(args.data_path, True, 0.1)
test_dataset = KORDataset(args.data_path, False, 0.1)
if args.distributed:
train_sampler = torch.utils.data.distributed.DistributedSampler(train_dataset)
else:
train_sampler = None
collate_fn1 = lambda batch: collate_fn_tr(batch, args.max_time_steps, args.hop_length)
collate_fn2 = lambda batch: collate_fn_synth(batch, args.hop_length)
train_loader = DataLoader(train_dataset, batch_size=args.bsz, shuffle=(train_sampler is None), collate_fn=collate_fn1,
num_workers=args.num_workers, pin_memory=True, sampler=train_sampler)
test_loader = DataLoader(test_dataset, batch_size=args.bsz, collate_fn=collate_fn1,
num_workers=args.num_workers, pin_memory=True)
synth_loader = DataLoader(test_dataset, batch_size=1, collate_fn=collate_fn2,
num_workers=args.num_workers, pin_memory=True)
print('num of train samples', len(train_loader))
print('num of test samples', len(test_loader))
return train_loader, test_loader, synth_loader