47c71c0524c7804863f2f4bcffdef5a873d84a55,txtgen/modules/connectors/connectors.py,,_mlp_transform,#Any#Any#Any#,18

Before Change

    // get output dimension
    iter_output_size = output_size if isinstance(output_size, (list, tuple)) else [output_size]
    shape_list = [tf.TensorShape(shape) for shape in iter_output_size]
    size_list = [0] * len(shape_list)
    for (i, shape) in enumerate(shape_list):
        size_list[i] = reduce(lambda x, y: x*y, [dim.value for dim in shape])
    sum_output_size = sum(size_list)

After Change

    flat_output = tf.split(fc_output, size_list, axis=1)

    if isinstance(flat_output_size[0], tf.TensorShape):
        for (i, shape) in enumerate(flat_output_size):
            new_shape = tf.TensorShape(batch_size).concatenate(shape)
            flat_output[i] = tf.reshape(flat_output[i], new_shape)
    output = nest.pack_sequence_as(structure=output_size,
                                   flat_sequence=flat_output)

    return output

Instances