class_docstr: Cell for Sequential User Matrix
class_docstr_tok: ["Cell","for","Sequential","User","Matrix"]
code: def get_config(self):
      config = {
          "num_units": self._num_units,
          "kernel_initializer": initializers.serialize(
              self._kernel_initializer
          ),
          "bias_initializer": initializers.serialize(
              self._bias_initializer
          ),
          "activation": activations.serialize(self._activation),
          "reuse": self._reuse,
      }
      base_config = super(SUMCell, self).get_config()
      return dict(list(base_config.items()) + list(config.items()))
  
imports: import numpy
  import tensorflow
  from keras.layers.legacy_rnn.rnn_cell_impl import LayerRNNCell
  from tensorflow.python.eager import context
  from tensorflow.python.keras import activations
  from tensorflow.python.keras import initializers
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.ops import init_ops
  from tensorflow.python.framework import dtypes
  from tensorflow.python.util import nest
label_desc: Use image node_id 7 for calling the SUMCell obj's underlying member method code with example usage: obj.get_config() and returns: dict