code: def test_default_score(self) -> None:
      # test custom default score
      default_score = 56.3
      bandit = UCB1MAB(default_score=default_score)
      policy = Policy(
          scorer=bandit,
          sampler=GreedyActionSampler(),
      )
      trainer = MABTrainer(policy)
      trainer.cb_training_step(self.batch, 0, 0)
  
      pred_arm_ids = torch.tensor([[1, 3], [6, 4], [5, 2]]).long()
      model_output = bandit(pred_arm_ids)
  
      ucb = model_output["ucb"].numpy()
      # check that we return default_score for arms which we haven't observed
      self.assertAlmostEqual(
          np.unique(ucb[[0, 1, 2, 2], [0, 0, 0, 1]])[0],
          default_score,
          places=5,
      )
  
      self.assertFalse(default_score in set(ucb[0:1, 1]))
  
file_path: ReAgent/reagent/test/models/test_mab.py
imports: import unittest
  from dataclasses import replace
  import numpy
  import numpy.testing
  import torch
  from reagent.core.types import CBInput
  from reagent.gym.policies.policy import Policy
  from reagent.gym.policies.samplers.discrete_sampler import GreedyActionSampler
  from reagent.models.mab import UCB1MAB
  from reagent.training.cb.mab_trainer import MABTrainer
label_desc: Use image node_id 3 for calling the TestUCB1MAB obj's underlying member method code with example usage: obj.test_default_score() without return types