code: def concat(input_layer, concat_dim, other_tensors=None):
    
    if input_layer.is_sequence():
      all_tensors = input_layer.sequence
      all_tensors.extend(other_tensors or [])
    else:
      all_tensors = [input_layer]
      if other_tensors is None:
        raise ValueError('Other Tensors must be supplied.')
      all_tensors.extend(other_tensors)
    # Edge cases really only apply when this is a sequence with 0 or 1 element.
    if not all_tensors:
      return prettytensor.wrap_sequence([])
    else:
      return tf.concat(all_tensors, concat_dim)
docs: Concatenates input PrettyTensor with other_tensors along the specified dim.
  
    This adds the Pretty Tensor passed via input_layer to the front of the list of
    tensors to concat.
  
    Args:
      input_layer: The input layer.
      concat_dim: The dimension along which to concat.
      other_tensors: The tensors to concatenate with as an iterable or None if
        this is called on a sequence.
    Returns:
      A new PrettyTensor.
    Raises:
      ValueError: If other_tensors is None and this is not a sequence.