class_docstr: Base class inherited by all memory network classes.
  
  Args:
      raw_memory_dim (int): Dimension size of raw memory entries
          (before embedding). For example,
          if a raw memory entry is a word, this is the **vocabulary size**
          (imagine a one-hot representation of word). If a raw memory entry
          is a dense vector, this is the dimension size of the vector.
      input_embed_fn (optional): A callable that embeds raw memory entries
          as inputs.
          This corresponds to the `A` embedding operation in
          (Sukhbaatar et al.)
          If not provided, a default embedding operation is created as
          specified in :attr:`hparams`. See
          :meth:`~texar.tf.modules.MemNetBase.get_default_embed_fn`
          for details.
      output_embed_fn (optional): A callable that embeds raw memory entries
          as outputs.
          This corresponds to the `C` embedding operation in
          (Sukhbaatar et al.)
          If not provided, a default embedding operation is created as
          specified in :attr:`hparams`. See
          :meth:`~texar.tf.modules.MemNetBase.get_default_embed_fn`
          for details.
      query_embed_fn (optional): A callable that embeds query.
          This corresponds to the `B` embedding operation in
          (Sukhbaatar et al.). If not provided and "use_B" is True
          in :attr:`hparams`, a default embedding operation is created as
          specified in :attr:`hparams`. See
          :meth:`~texar.tf.modules.MemNetBase.get_default_embed_fn`
          for details.
          Notice: If you'd like to customize this callable, please follow
          the same number and style of dimensions as in `input_embed_fn` or
          `output_embed_fn`, and assume that the 2nd dimension of its
          input and output (which corresponds to `memory_size`) is 1.
      hparams (dict or HParams, optional): Hyperparameters. Missing
          hyperparamerter will be set to default values. See
          :meth:`default_hparams` for the hyperparameter sturcture and
          default values.
docstr: The dimension of embedded memory and all vectors in hops.
          
docstr_tok: ["The","dimension","of","embedded","memory","and","all","vectors","in","hops","."]
code: def memory_dim(self):
      """The dimension of embedded memory and all vectors in hops."""
      return self._memory_dim
  
imports: import tensorflow
  from texar.tf.module_base import ModuleBase
  from texar.tf.modules.embedders import WordEmbedder, PositionEmbedder
  from texar.tf.utils.mode import switch_dropout
  from texar.tf.modules.memory.embed_fns import default_memnet_embed_fn_hparams
label_desc: Use image node_id 8 for calling the MemNetBase obj's underlying member method code with example usage: obj.memory_dim() and returns: self