parameters: (self, name=None)
return_statement: return (finished, start_inputs, initial_state)
docstring: Initialize the decoder.
  
      Args:
        name: Name scope for any created operations.
  
      Returns:
        `(finished, start_inputs, initial_state)`.
docstring_summary: Initialize the decoder.
docstring_tokens: Initialize the decoder .
function: def initialize(self, name=None):
      """Initialize the decoder.
  
      Args:
        name: Name scope for any created operations.
  
      Returns:
        `(finished, start_inputs, initial_state)`.
      """
      finished, start_inputs = self._finished, self._start_inputs
  
      initial_state = BeamSearchDecoderState(
          cell_state=self._initial_cell_state,
          log_probs=array_ops.zeros(
              [self._batch_size, self._beam_width],
              dtype=nest.flatten(self._initial_cell_state)[0].dtype),
          finished=finished,
          lengths=array_ops.zeros(
              [self._batch_size, self._beam_width], dtype=dtypes.int32))
  
      return (finished, start_inputs, initial_state)
function_tokens: def initialize ( self , name = None ) : finished , start_inputs = self . _finished , self . _start_inputs initial_state = BeamSearchDecoderState ( cell_state = self . _initial_cell_state , log_probs = array_ops . zeros ( [ self . _batch_size , self . _beam_width ] , dtype = nest . flatten ( self . _initial_cell_state ) [ 0 ] . dtype ) , finished = finished , lengths = array_ops . zeros ( [ self . _batch_size , self . _beam_width ] , dtype = dtypes . int32 ) ) return ( finished , start_inputs , initial_state )