code: def merge_lists(a_features: List, b_features: List):
      for idx in range(max(len(a_features), len(b_features))):
          if idx >= len(a_features):
              a_features.append(b_features[idx])
          elif idx < len(b_features):
              a_features[idx] = merge_dict(
                  a_features[idx], b_features[idx]
              )
  
imports: import os
  import tempfile
  from typing import List, Set
  from unittest import mock
  import numpy
  import pandas
  import pytest
  from ludwig.api import LudwigModel
  from ludwig.constants import COLUMN, ENCODER, INPUT_FEATURES, NAME, OUTPUT_FEATURES, PREPROCESSING, SPLIT, TYPE
  from ludwig.schema.model_types.base import ModelConfig
  from ludwig.types import FeatureConfigDict, ModelConfigDict
  from ludwig.utils.misc_utils import merge_dict
  from tests.integration_tests.utils import binary_feature, category_feature, generate_data, image_feature, minio_test_creds, number_feature, private_param, remote_tmpdir, text_feature
  import dask.dataframe
  from ray.tune.experiment.trial import Trial
  from ludwig.automl import auto_train, create_auto_config, train_with_config
  from ludwig.automl.automl import OUTPUT_DIR
  from ludwig.hyperopt.execution import RayTuneExecutor
label_desc: Use image node_id 2 for calling a global function with example usage: merge_lists(a_features, b_features) without return types