def _build(self, inputs, prev_state):
    """Connects the KernelDeepLSTM module into the graph.

    Args:
      inputs: 4D `Tensor` (convolutional filter).
      prev_state: `DeepRNN` state.

    Returns:
      `Tensor` shaped as `inputs`.
    """
    input_shape = inputs.get_shape().as_list()
    reshaped_inputs = self._reshape_inputs(inputs)

    build_fn = super(KernelDeepLSTM, self)._build
    output, next_state = build_fn(reshaped_inputs, prev_state)
    transposed_output = tf.transpose(output, [1, 0])

    # Recover original shape.
    return tf.reshape(transposed_output, input_shape), next_state
Connects the KernelDeepLSTM module into the graph.

    Args:
      inputs: 4D `Tensor` (convolutional filter).
      prev_state: `DeepRNN` state.

    Returns:
      `Tensor` shaped as `inputs`.
    
networks.py