parameters: (x, y, input_length, output_length, sentinel=None, name=None)
docstring: Processes inputs for Sequence to Sequence models.
  
    Args:
      x: Input Tensor [batch_size, input_length, embed_dim].
      y: Output Tensor [batch_size, output_length, embed_dim].
      input_length: length of input x.
      output_length: length of output y.
      sentinel: optional first input to decoder and final output expected.
        If sentinel is not provided, zeros are used. Due to fact that y is not
        available in sampling time, shape of sentinel will be inferred from x.
      name: Operation name.
  
    Returns:
      Encoder input from x, and decoder inputs and outputs from y.
docstring_summary: Processes inputs for Sequence to Sequence models.
docstring_tokens: Processes inputs for Sequence to Sequence models .
function: def seq2seq_inputs(x, y, input_length, output_length, sentinel=None, name=None):
    """Processes inputs for Sequence to Sequence models.
  
    Args:
      x: Input Tensor [batch_size, input_length, embed_dim].
      y: Output Tensor [batch_size, output_length, embed_dim].
      input_length: length of input x.
      output_length: length of output y.
      sentinel: optional first input to decoder and final output expected.
        If sentinel is not provided, zeros are used. Due to fact that y is not
        available in sampling time, shape of sentinel will be inferred from x.
      name: Operation name.
  
    Returns:
      Encoder input from x, and decoder inputs and outputs from y.
    """
    with ops.name_scope(name, "seq2seq_inputs", [x, y]):
      in_x = array_ops.unstack(x, axis=1)
      y = array_ops.unstack(y, axis=1)
      if not sentinel:
        # Set to zeros of shape of y[0], using x for batch size.
        sentinel_shape = array_ops.stack(
            [array_ops.shape(x)[0], y[0].get_shape()[1]])
        sentinel = array_ops.zeros(sentinel_shape)
        sentinel.set_shape(y[0].get_shape())
      in_y = [sentinel] + y
      out_y = y + [sentinel]
      return in_x, in_y, out_y
function_tokens: def seq2seq_inputs ( x , y , input_length , output_length , sentinel = None , name = None ) : with ops . name_scope ( name , "seq2seq_inputs" , [ x , y ] ) : in_x = array_ops . unstack ( x , axis = 1 ) y = array_ops . unstack ( y , axis = 1 ) if not sentinel : # Set to zeros of shape of y[0], using x for batch size. sentinel_shape = array_ops . stack ( [ array_ops . shape ( x ) [ 0 ] , y [ 0 ] . get_shape ( ) [ 1 ] ] ) sentinel = array_ops . zeros ( sentinel_shape ) sentinel . set_shape ( y [ 0 ] . get_shape ( ) ) in_y = [ sentinel ] + y out_y = y + [ sentinel ] return in_x , in_y , out_y