code: def create_ground_truth_net(ng_param):
      dim_input = sum([len(ng_param[k].choices) for k in ng_param])
      dim_model = 256
      gt_net = GroundTruthNet(dim_input, dim_model)
      print(
          f"Ground-Truth Net DIM_INPUT={dim_input}, DIM_MODEL={dim_model}"
      )
      return gt_net
  
imports: import random
  import unittest
  from collections import defaultdict
  from typing import Dict
  import nevergrad
  import numpy
  import torch
  import torch.nn
  from reagent.lite.optimizer import BayesianByBackpropOptimizer, BayesianMLPEnsemblerOptimizer, BayesianOptimizerBase, GREEDY_TEMP, GumbelSoftmaxOptimizer, NeverGradOptimizer, PolicyGradientOptimizer, QLearningOptimizer, RandomSearchOptimizer, sol_to_tensors
label_desc: Use image node_id 3 for calling a global function with example usage: create_ground_truth_net(ng_param) and returns: gt_net