code: def accuracy_score(
      y_true, y_pred, *, normalize=True, sample_weight=None
  ):
      # TODO: implement sample_weight
      y_type = type_of_target(y_true)
      if y_type.startswith("multilabel"):
          diff_labels = ivy.count_nonzero(y_true - y_pred, axis=1)
          ret = ivy.equal(diff_labels, 0).astype("int64")
      else:
          ret = ivy.equal(y_true, y_pred).astype("int64")
      ret = ret.sum().astype("int64")
      if normalize:
          ret = ret / y_true.shape[0]
          ret = ret.astype("float64")
      return ret
  
label_desc: Use image node_id 1 for calling a global function with example usage: accuracy_score(y_true, y_pred) and returns: ret