def __getitem__(self, index):
# Load acoustic feature and pad
x_batch = [
torch.FloatTensor(np.load(os.path.join(self.root, x_file)))
for x_file in self.X[index]
]
x_pad_batch = pad_sequence(x_batch, batch_first=True)
if self.run_mockingjay:
x_pad_batch = process_train_MAM_data(spec=(x_pad_batch, ),
config=self.mock_config)
return x_pad_batch
def __getitem__(self, index):
# Load acoustic feature and pad
x_batch = [
torch.FloatTensor(np.load(os.path.join(self.root, x_file)))
for x_file in self.X[index]
]
x_pad_batch = pad_sequence(x_batch, batch_first=True)
# Return (x_spec, t_spec)
t_batch = [
torch.FloatTensor(np.load(os.path.join(self.t_root, t_file)))
for t_file in self.T[index]
]
t_pad_batch = pad_sequence(t_batch, batch_first=True)
batch = process_train_MAM_data(spec=(x_pad_batch, t_pad_batch),
config=self.mock_config)
return batch