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