code: def test_linear_reward_parametric_reward_fail(self):
      avg_eval_loss = self._test_linear_reward_parametric_reward(
          ground_truth_reward_from_multiple_steps=True
      )
      # fail to learn
      threshold = 100.0
      assert avg_eval_loss > threshold
  
imports: import logging
  import unittest
  import pytorch_lightning
  import torch
  from reagent.core import parameters, types
  from reagent.models.synthetic_reward import NGramConvolutionalNetwork, NGramFullyConnectedNetwork, SequenceSyntheticRewardNet, SingleStepSyntheticRewardNet, SyntheticRewardNet, TransformerSyntheticRewardNet
  from reagent.optimizer.union import classes, Optimizer__Union
  from reagent.reporting.reward_network_reporter import RewardNetworkReporter
  from reagent.training import RewardNetTrainer
  from reagent.training.reward_network_trainer import LossFunction
  from torch.utils.data import DataLoader
label_desc: Use image node_id 3 for calling the TestSyntheticRewardTraining obj's underlying member method code with example usage: obj.test_linear_reward_parametric_reward_fail() without return types