class_docstr: A layer which multiplies its input by a scalar variable.
class_docstr_tok: ["A","layer","which","multiplies","its","input","by","a","scalar","variable","."]
code: def get_config(self):
      config = super(MultiplyLayer, self).get_config()
      config["regularizer"] = regularizers.serialize(self._regularizer)
      config["activity_regularizer"] = regularizers.serialize(
          self._activity_regularizer
      )
      config["use_operator"] = self._use_operator
      config["var_name"] = self._var_name
      config["assert_type"] = self._assert_type
      return config
  
imports: from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion
  from tensorflow.python.keras import regularizers
  from tensorflow.python.keras.engine import base_layer
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import math_ops
  from tensorflow.python.util import nest
label_desc: Use image node_id 5 for calling the MultiplyLayer obj's underlying member method code with example usage: obj.get_config() and returns: config