docstr: Computes exact match between prediction and ground truth 
docstr_tok: ["Computes","exact","match","between","prediction","and","ground","truth"]
code: def get_one_exact_match(prediction: str, ground_truth: str):
      """Computes exact match between prediction and ground truth"""
  
      return int(
          QAMetrics.normalize_answer(prediction)
          == QAMetrics.normalize_answer(ground_truth)
      )
  
imports: import collections
  import json
  import re
  import string
  import torch
  from tqdm import tqdm
  from nemo.collections.nlp.parts.utils_funcs import tensor2list
  from nemo.utils import logging
label_desc: Use image node_id 7 for calling the QAMetrics obj's underlying member method code with example usage: obj.get_one_exact_match(prediction, ground_truth) and returns: int