code: def parse_activation_layer(
      operation,
      layer_name,
      input_names,
      input_shapes,
      node,
      class_object,
      data_reader,
      config,
  ):
      layer = {}
  
      layer["class_name"] = operation
      layer["activation"] = layer["class_name"]
      layer["name"] = layer_name
      layer["inputs"] = input_names
  
      # if layer['class_name'] != 'Activation':
      #    layer['activation'] = layer['class_name']
      if node.op == "call_module":
          if (
              layer["class_name"] == "ReLU"
              or layer["class_name"] == "Sigmoid"
          ):
              layer["class_name"] = "Activation"
          if layer["class_name"] == "LeakyReLU":
              layer["activ_param"] = class_object.negative_slope
          if layer["class_name"] == "ELU":
              layer["activ_param"] = class_object.alpha
          if layer["class_name"] == "PReLU":
              layer["alpha_data"] = class_object.weight.data.numpy()
          if layer["class_name"] == "Threshold":
              layer["activ_param"] = class_object.threshold
              layer["class_name"] = "ThresholdedReLU"
              layer["activation"] = "ThresholdedReLU"
              if layer["activ_param"] < 0:
                  raise Exception(
                      "negative threshold values not supported"
                  )
  
          if hasattr(node, "dim"):
              layer["axis"] = class_object.dim
      else:
          if (
              layer["class_name"] == "ReLU"
              or layer["class_name"] == "Sigmoid"
          ):
              layer["class_name"] = "Activation"
          if layer["class_name"] == "LeakyReLU":
              layer["activ_param"] = node.kwargs["negative_slope"]
          if layer["class_name"] == "ELU":
              layer["activ_param"] = node.kwargs["alpha"]
          if layer["class_name"] == "Threshold":
              layer["activ_param"] = node.args[1]
              if layer["activ_param"] < 0:
                  raise Exception(
                      "negative threshold values not supported"
                  )
              layer["class_name"] = "ThresholdedReLU"
              layer["activation"] = "ThresholdedReLU"
          if "dim" in node.kwargs:
              layer["axis"] = node.kwargs["dim"]
  
      output_shape = input_shapes[0]
      return layer, output_shape
  
label_desc: Use image node_id 2 for calling a global function with example usage: parse_activation_layer(operation, layer_name, input_names, input_shapes, node, class_object, data_reader, config) and returns: layer,  output_shape