class_docstr: This is a classification model that selects the best heteronym option out of possible dictionary entries.
  Supports only heteronyms, no OOV.
code: def on_train_epoch_end(self):
      return super().on_train_epoch_end()
  
imports: import json
  import os
  from typing import List, Optional
  import torch
  from hydra.utils import instantiate
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from nemo.collections.common.losses import CrossEntropyLoss
  from nemo.collections.nlp.metrics.classification_report import ClassificationReport
  from nemo.collections.nlp.modules.common import TokenClassifier
  from nemo.collections.nlp.parts.utils_funcs import tensor2list
  from nemo.collections.tts.g2p.data.heteronym_classification import HeteronymClassificationDataset
  from nemo.collections.tts.g2p.utils import get_heteronym_spans, get_wordid_to_phonemes, read_wordids
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.utils import logging
label_desc: Use image node_id 5 for calling the HeteronymClassificationModel obj's underlying member method code with example usage: obj.on_train_epoch_end() and returns: super