code: def map_scale(cls, node):
      # TODO: The gamma parameter has to be set (in node.data?) and this should work.
      # Also, mean should be set to 0, and var to 1, just to be safe.
      if node.data:
          scale_value = float(node.parameters.filler.value)
          if node.parameters.bias_term:
              bias_value = float(node.parameters.bias_filler.value)
              kwargs = {
                  "use_scale": True,
                  "use_bias": node.parameters.bias_term,
                  "gamma": scale_value,
                  "beta": bias_value,
                  "epsilon": 0,
              }
          else:
              kwargs = {
                  "use_scale": True,
                  "use_bias": node.parameters.bias_term,
                  "gamma": scale_value,
                  "epsilon": 0,
              }
  
          cls._convert_output_shape(kwargs, node)
          return Node.create("Affine", **kwargs)
      else:
          return Node.create("Mul")
  
imports: from __future__ import absolute_import
  from __future__ import division
  import numpy
  from mmdnn.conversion.caffe.errors import ConversionError
  from mmdnn.conversion.caffe.common_graph import Node
  from mmdnn.conversion.caffe.network import DEFAULT_PADDING
  from mmdnn.conversion.caffe.utils import get_lower_case
  from mmdnn.conversion.common.IR.graph_pb2 import TensorShape
label_desc: Use image node_id 20 for calling the NodeMapper obj's underlying member method code with example usage: obj.map_scale(cls, node) and returns: Node, Node