class_docstr: Transforms inputs to have specified structure.
  
  Args:
      output_size: Size of output **excluding** the batch dimension. For
          example, set `output_size` to `dim` to generate output of
          shape `[batch_size, dim]`.
          Can be an `int`, a tuple of `int`, a Tensorshape, or a tuple of
          TensorShapes.
          For example, to transform inputs to have decoder state size, set
          `output_size=decoder.state_size`.
      hparams (dict, optional): Hyperparameters. Missing
          hyperparamerter will be set to default values. See
          :meth:`default_hparams` for the hyperparameter sturcture and
          default values.
  
  This connector does not have trainable parameters.
  See :meth:`_build` for the inputs and outputs of the connector.
  
  The input to the connector must have the same structure with
  :attr:`output_size`, or must have the same number of elements and be
  re-packable into the structure of :attr:`output_size`. Note that if input
  is or contains a `dict` instance, the keys will be sorted to pack in
  deterministic order (See
  :tf_main:`pack_sequence_as <contrib/framework/nest/pack_sequence_as>`
  for more details).
  
  Example:
  
      .. code-block:: python
  
          cell = LSTMCell(num_units=256)
          # cell.state_size == LSTMStateTuple(c=256, h=256)
  
          connector = ForwardConnector(cell.state_size)
          output = connector([tensor_1, tensor_2])
          # output == LSTMStateTuple(c=tensor_1, h=tensor_2)
  
  .. document private functions
  .. automethod:: _build
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docstr: Returns a dictionary of hyperparameters with default values.
  
  .. code-block:: python
  
      {
          "name": "forward_connector"
      }
  
  Here:
  
  "name": str
      Name of the connector.
docstr_tok: ["Returns","a","dictionary","of","hyperparameters","with","default","values",".","..","code-block",":",":","python","{","``","name","''",":","``","forward_connector","''","}","Here",":","''","name","''",":","str","Name","of","the","connector","."]
code: def default_hparams():
      """Returns a dictionary of hyperparameters with default values.
  
      .. code-block:: python
  
          {
              "name": "forward_connector"
          }
  
      Here:
  
      "name": str
          Name of the connector.
      """
      return {"name": "forward_connector"}
  
imports: import numpy
  import tensorflow
  from tensorflow import distributions
  from tensorflow.python.util import nest
  from texar.tf.modules.connectors.connector_base import ConnectorBase
  from texar.tf.core import layers
  from texar.tf.utils.utils import get_function, check_or_get_instance
label_desc: Use image node_id 2 for calling the ForwardConnector obj's underlying member method code with example usage: obj.default_hparams() and returns: dict