code: def test_formatted_output(self):
      model_actions = torch.tensor([[1], [1]], dtype=torch.long)
      _ = self.eval_module.ingest_batch(self.batch, model_actions)
      self.eval_module._aggregate_across_instances()
      output = self.eval_module.get_formatted_result_string()
      self.assertIsInstance(output, str)
  
imports: import copy
  import unittest
  from dataclasses import replace
  from unittest.mock import MagicMock
  import torch
  from pytorch_lightning.loggers import TensorBoardLogger
  from reagent.core.types import CBInput
  from reagent.evaluation.cb.policy_evaluator import PolicyEvaluator
  from reagent.evaluation.cb.utils import add_importance_weights
  from reagent.models.linear_regression import LinearRegressionUCB
label_desc: Use image node_id 6 for calling the TestPolicyEvaluator obj's underlying member method code with example usage: obj.test_formatted_output() without return types