(self, inputs, initial_state=None, **kwargs)
Called before any decoding iterations.

    This methods must compute initial input values and initial state.

    Args:
      inputs: (structure of) tensors that contains the input for the decoder. In
        the normal case, its a tensor with shape [batch, timestep, embedding].
      initial_state: (structure of) tensors that contains the initial state for
        the RNNCell.
      **kwargs: Other arguments that are passed in from layer.call() method. It
        could contains item like input sequence_length, or masking for input.

    Returns:
      `(finished, initial_inputs, initial_state)`: initial values of
      'finished' flags, inputs and state.
Called before any decoding iterations.
Called before any decoding iterations .
def initialize(self, inputs, initial_state=None, **kwargs):
    """Called before any decoding iterations.

    This methods must compute initial input values and initial state.

    Args:
      inputs: (structure of) tensors that contains the input for the decoder. In
        the normal case, its a tensor with shape [batch, timestep, embedding].
      initial_state: (structure of) tensors that contains the initial state for
        the RNNCell.
      **kwargs: Other arguments that are passed in from layer.call() method. It
        could contains item like input sequence_length, or masking for input.

    Returns:
      `(finished, initial_inputs, initial_state)`: initial values of
      'finished' flags, inputs and state.
    """
    raise NotImplementedError
def initialize ( self , inputs , initial_state = None , * * kwargs ) : raise NotImplementedError