code: def summarize_attributions(attributions):
      """Summarises the attribution across multiple runs
      Args:
          attributions ([list): attributions from the Layer Integrated Gradients
      Returns:
          list : Returns the attributions after normalizing them.
      """
      attributions = attributions.sum(dim=-1).squeeze(0)
      attributions = attributions / torch.norm(attributions)
      return attributions
  
imports: import ast
  import json
  import logging
  import os
  from abc import ABC
  import torch
  import transformers
  from captum.attr import LayerIntegratedGradients
  from transformers import AutoModelForCausalLM, AutoModelForQuestionAnswering, AutoModelForSequenceClassification, AutoModelForTokenClassification, AutoTokenizer, GPT2TokenizerFast
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 3 for calling a global function with example usage: summarize_attributions(attributions) and returns: attributions