code: def default_memnet_embed_fn_hparams():
      """Returns a dictionary of hyperparameters with default hparams for
      :func:`~texar.tf.modules.memory.default_embed_fn`
  
      .. code-block:: python
  
          {
              "embedding": {
                  "dim": 100
              },
              "temporal_embedding": {
                  "dim": 100
              },
              "combine_mode": "add"
          }
  
      Here:
  
      "embedding": dict, optional
          Hyperparameters for embedding operations. See
          :meth:`~texar.tf.modules.WordEmbedder.default_hparams` of
          :class:`~texar.tf.modules.WordEmbedder` for details. If `None`, the
          default hyperparameters are used.
  
      "temporal_embedding": dict, optional
          Hyperparameters for temporal embedding operations. See
          :meth:`~texar.tf.modules.PositionEmbedder.default_hparams` of
          :class:`~texar.tf.modules.PositionEmbedder` for details. If `None`, the
          default hyperparameters are used.
  
      "combine_mode": str
          Either **'add'** or **'concat'**. If 'add', memory
          embedding and temporal embedding are added up. In this case the two
          embedders must have the same dimension. If 'concat', the two
          embeddings are concated.
      """
      return {
          "embedding": {"dim": 100},
          "temporal_embedding": {"dim": 100},
          "combine_mode": "add",
      }
  
label_desc: Use image node_id 1 for calling a global function with example usage: default_memnet_embed_fn_hparams() and returns: dict