class_docstr: Mixin for :class:`jiant.tasks.core.Task`s in the `SuperGLUE<https://super.gluebenchmark.com/>`_
  benchmark.
class_docstr_tok: ["Mixin","for",":","class",":","`","jiant.tasks.core.Task","`","s","in","the","`","SuperGLUE","<","https",":","\/\/super.gluebenchmark.com\/",">","`","_","benchmark","."]
docstr: Tasks in the SuperGLUE benchmark must implement this method to return
  predictions in the expected SuperGLUE format. This function is expect to
  return a List[Dict] with each Dict value in the format expected by the
  SuperGLUE benchmark submission grader.
  
  Args:
      pred_dict (Dict): Dictionary mapping "preds" to List of label ids
      and
      "guids" to List of example ids
  
  Raises:
      NotImplementedError
code: def super_glue_format_preds(cls, pred_dict: Dict):
      """Tasks in the SuperGLUE benchmark must implement this method to return
      predictions in the expected SuperGLUE format. This function is expect to
      return a List[Dict] with each Dict value in the format expected by the
      SuperGLUE benchmark submission grader.
  
      Args:
          pred_dict (Dict): Dictionary mapping "preds" to List of label ids
          and
          "guids" to List of example ids
  
      Raises:
          NotImplementedError
      """
      raise NotImplementedError()
  
imports: import numpy
  from typing import NamedTuple, Mapping, Dict
  from enum import Enum
  from dataclasses import dataclass
  import torch
  import torch.utils.data.dataloader
  from jiant.utils.python.datastructures import ExtendedDataClassMixin, combine_dicts
label_desc: Use image node_id 1 for calling the SuperGlueMixin obj's underlying member method code with example usage: obj.super_glue_format_preds(cls, pred_dict) without return types