class_docstr: BERT encoder with QA head training.
class_docstr_tok: ["BERT","encoder","with","QA","head","training","."]
code: def on_test_epoch_end(self):
      return self.on_validation_epoch_end()
  
imports: import json
  from typing import Optional
  import torch
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from torch.cuda.amp import autocast
  from nemo.collections.common.losses import SpanningLoss
  from nemo.collections.nlp.data import SquadDataset
  from nemo.collections.nlp.data.question_answering_squad.qa_squad_processing import EVALUATION_MODE, INFERENCE_MODE, TRAINING_MODE
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.collections.nlp.modules.common import TokenClassifier
  from nemo.collections.nlp.parts.utils_funcs import tensor2list
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.utils import logging
label_desc: Use image node_id 7 for calling the QAModel obj's underlying member method code with example usage: obj.on_test_epoch_end() and returns: self