class_docstr: Raw XLNet module for encoding sequences. Please see
  :class:`~texar.tf.modules.PretrainedXLNetMixin` for a brief description
  of XLNet.
  
  Args:
      pretrained_model_name (optional): a `str`, the name
          of pre-trained model (e.g., ``xlnet-based-cased``). Please refer to
          :class:`~texar.tf.modules.PretrainedXLNetMixin` for
          all supported models.
          If `None`, the model name in :attr:`hparams` is used.
      cache_dir (optional): the path to a folder in which the
          pre-trained models will be cached. If `None` (default),
          a default directory (``texar_data`` folder under user's home
          directory) will be used.
      hparams (dict or HParams, optional): Hyperparameters. Missing
          hyperparameter will be set to default values. See
          :meth:`default_hparams` for the hyperparameter structure
          and default values.
  
  .. document private functions
  .. automethod:: _build
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docstr: Cache hidden states into memory.
docstr_tok: ["Cache","hidden","states","into","memory","."]
code: def _cache_mem(curr_out, prev_mem, mem_len, reuse_len=None):
      r"""Cache hidden states into memory."""
      assert mem_len > 0
  
      if reuse_len is not None and reuse_len > 0:
          curr_out = curr_out[:reuse_len]
  
      if prev_mem is None:
          new_mem = curr_out[-mem_len:]
      else:
          new_mem = tf.concat([prev_mem, curr_out], 0)[-mem_len:]
  
      return tf.stop_gradient(new_mem)
  
imports: import tensorflow
  from texar.tf.utils.mode import is_train_mode
  from texar.tf.core.layers import get_initializer, get_layer
  from texar.tf.modules.embedders.embedders import WordEmbedder
  from texar.tf.modules.encoders.encoder_base import EncoderBase
  from texar.tf.modules.pretrained.xlnet import PretrainedXLNetMixin
  from texar.tf.modules.pretrained.xlnet_utils import PositionWiseFF, RelativePositionalEncoding, RelativeMutiheadAttention
  from texar.tf.utils.utils import dict_fetch
label_desc: Use image node_id 6 for calling the XLNetEncoder obj's underlying member method code with example usage: obj._cache_mem(curr_out, prev_mem, mem_len, reuse_len) and returns: tf