class_docstr: TF basic RNN cell with extra customization params. 
class_docstr_tok: ["TF","basic","RNN","cell","with","extra","customization","params","."]
docstr: Most basic RNN: output = new_state = activation(W * input + U * state + B).
code: def __call__(self, inputs, state, scope=None):
      """Most basic RNN: output = new_state = activation(W * input + U * state + B)."""
      with tf.variable_scope(scope or type(self).__name__):
          # "BasicRNNCell"
          output = self._activation(
              _linear(
                  [inputs, state],
                  self._num_units,
                  True,
                  0.0,
                  self.weights_init,
                  self.trainable,
                  self.restore,
                  self.reuse,
              )
          )
          # Retrieve RNN Variables
          with tf.variable_scope("Linear", reuse=True):
              self.W = tf.get_variable("Matrix")
              self.b = tf.get_variable("Bias")
  
      return output, output
  
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 4 for calling the BasicRNNCell obj's underlying member method code with example usage: obj.__call__(inputs, state, scope) and returns: output,  output