class_docstr: TF Basic LSTM recurrent network cell with extra customization params.
  
  The implementation is based on: http://arxiv.org/abs/1409.2329.
  
  We add forget_bias (default: 1) to the biases of the forget gate in order to
  reduce the scale of forgetting in the beginning of the training.
  
  It does not allow cell clipping, a projection layer, and does not
  use peep-hole connections: it is the basic baseline.
  
  For advanced models, please use the full LSTMCell that follows.
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code: def state_size(self):
      return (
          core_rnn_cell.LSTMStateTuple(self._num_units, self._num_units)
          if self._state_is_tuple
          else 2 * self._num_units
      )
  
imports: from __future__ import division, print_function, absolute_import
  import logging
  import numpy
  import tensorflow.compat.v1
  from tensorflow.python.ops import array_ops
  from tensorflow.python.util.nest import is_sequence
  from ..None import config
  from ..None import utils
  from ..None import activations
  from ..None import initializations
  from ..None import variables
  from .normalization import batch_normalization
label_desc: Use image node_id 2 for calling the BasicLSTMCell obj's underlying member method code with example usage: obj.state_size() and returns: unknown