code: def _get_elementwise_name_from_keras_layer(keras_layer):
      """
      Get the keras layer name from the activation name.
      """
      if isinstance(keras_layer, _keras.layers.Add):
          return "ADD"
      elif isinstance(keras_layer, _keras.layers.Multiply):
          return "MULTIPLY"
      elif isinstance(keras_layer, _keras.layers.Concatenate):
          if len(keras_layer.input_shape[0]) == 3 and (
              keras_layer.axis == 1 or keras_layer.axis == -2
          ):
              return "SEQUENCE_CONCAT"
          if len(keras_layer.input_shape[0]) == 3 and (
              keras_layer.axis == 2 or keras_layer.axis == -1
          ):
              return "CONCAT"
          elif len(keras_layer.input_shape[0]) == 4 and (
              keras_layer.axis == 3 or keras_layer.axis == -1
          ):
              return "CONCAT"
          elif len(keras_layer.input_shape[0]) == 2 and (
              keras_layer.axis == 1 or keras_layer.axis == -1
          ):
              return "CONCAT"
          else:
              raise ValueError(
                  "Only channel and sequence concatenation are supported."
              )
      elif isinstance(keras_layer, _keras.layers.Dot):
          if len(keras_layer.input_shape[0]) == 2:
              if (
                  type(keras_layer.axes) is list
                  or type(keras_layer.axes) is tuple
              ):
                  if len(keras_layer.axes) > 1:
                      raise ValueError(
                          "Only vector dot-product is supported."
                      )
                  else:
                      axis = keras_layer.axes[0]
              else:
                  axis = keras_layer.axes
              if axis != -1 and axis != 1:
                  raise ValueError(
                      "Only vector dot-product is supported."
                  )
  
              if keras_layer.normalize:
                  return "COS"
              else:
                  return "DOT"
          else:
              raise ValueError("Only vector dot-product is supported.")
      elif isinstance(keras_layer, _keras.layers.Maximum):
          return "MAX"
      elif isinstance(keras_layer, _keras.layers.Average):
          return "AVE"
      else:
          _utils.raise_error_unsupported_option(
              str(type(keras_layer)), "merge", keras_layer.name
          )
  
imports: from .None import _utils
  import logging
  import keras
  import numpy
  from ...proto import NeuralNetwork_pb2
  from distutils.version import StrictVersion
label_desc: Use image node_id 3 for calling a global function with example usage: _get_elementwise_name_from_keras_layer(keras_layer) and returns: str, str, str, str, str, str, str, str, str, str