code: def generate_output_features_with_dependencies(
      main_feature, dependencies
  ):
      # helper function to generate multiple output features specifications
      # with dependencies, support for 'test_experiment_multiple_seq_seq` unit
      # test
      # Parameters:
      # main_feature: feature identifier, valid values 'feat1', 'feat2', 'feat3'
      # dependencies: list of dependencies for 'main_feature', do not li
      # Example:
      #  generate_output_features_with_dependencies('feat2', ['feat1', 'feat3'])
  
      output_features = [
          category_feature(vocab_size=2, reduce_input="sum"),
          sequence_feature(vocab_size=10, max_len=5),
          numerical_feature(),
      ]
  
      # value portion of dictionary is a tuple: (position, feature_name)
      #   position: location of output feature in the above output_features list
      #   feature_name: Ludwig generated feature name
      feature_names = {
          "feat1": (0, output_features[0]["name"]),
          "feat2": (1, output_features[1]["name"]),
          "feat3": (2, output_features[2]["name"]),
      }
  
      # generate list of dependencies with real feature names
      generated_dependencies = [
          feature_names[feat_name][1] for feat_name in dependencies
      ]
  
      # specify dependencies for the main_feature
      output_features[feature_names[main_feature][0]][
          "dependencies"
      ] = generated_dependencies
  
      return output_features
  
imports: import multiprocessing
  import os
  import random
  import shutil
  import sys
  import traceback
  import unittest
  import uuid
  from distutils.util import strtobool
  import cloudpickle
  import numpy
  import pandas
  from ludwig.api import LudwigModel
  from ludwig.backend import LocalBackend
  from ludwig.constants import VECTOR, COLUMN, NAME, PROC_COLUMN
  from ludwig.data.dataset_synthesizer import DATETIME_FORMATS
  from ludwig.data.dataset_synthesizer import build_synthetic_dataset
  from ludwig.experiment import experiment_cli
  from ludwig.features.feature_utils import compute_feature_hash
  from ludwig.utils.data_utils import read_csv, replace_file_extension
label_desc: Use image node_id 19 for calling a global function with example usage: generate_output_features_with_dependencies(main_feature, dependencies) and returns: output_features