a0b36a485bfe99ebf258c23057e1d8a602e9e7b2,train.py,,collate_fn,#Any#,126

Before Change

        frame_positions = np.array(
            [_pad(np.arange(1, len(x[1]) // r + 1), max_target_len // r)
             for x in batch], dtype=np.int)
        frame_positions = torch.LongTensor(frame_positions)
    else:
        s, e = 1, max_target_len // r + 1
        if b_pad > 0:
            s, e = s - 1, e - 1

After Change

    // done flags
    done = np.array([_pad(np.zeros(len(x[1]) // r - 1), max_target_len // r, constant_values=1)
                     for x in batch])
    done = torch.FloatTensor(done)

    return x_batch, input_lengths, mel_batch, y_batch, (text_positions, frame_positions), done

Instances