code: def _create_dummy_data_handler(self):
      feat = WordFeatConfig(
          vocab_size=4,
          vocab_from_all_data=True,
          vocab_from_train_data=True,
          vocab_from_pretrained_embeddings=False,
          pretrained_embeddings_path=None,
      )
      featurizer = create_featurizer(
          SimpleFeaturizer.Config(), FeatureConfig(word_feat=feat)
      )
      data_handler = DocClassificationDataHandler.from_config(
          DocClassificationDataHandler.Config(),
          ModelInputConfig(word_feat=feat),
          TargetConfig(),
          featurizer=featurizer,
      )
      train_data = data_handler.gen_dataset(
          [{"text": "<pad>"}], include_label_fields=False
      )
      eval_data = data_handler.gen_dataset(
          [{"text": "<pad>"}], include_label_fields=False
      )
      test_data = data_handler.gen_dataset(
          [{"text": "<pad>"}], include_label_fields=False
      )
      data_handler.init_feature_metadata(
          train_data, eval_data, test_data
      )
  
      return data_handler
  
file_path: captum/tests/attr/models/test_pytext.py
imports: from __future__ import print_function
  import os
  import tempfile
  import unittest
  from typing import Dict, List
  import torch
label_desc: Use image node_id 5 for calling the TestWordEmbeddings obj's underlying member method code with example usage: obj._create_dummy_data_handler() and returns: data_handler