code: def test_linucb_weights(self):
      # make sure that using a weight is same as processing an example several times
      batch_with_weight = copy.deepcopy(self.batch)
      batch_with_weight.weight = 3 * torch.ones((self.batch_size, 1))
  
      scorer_1 = LinearRegressionUCB(self.x_dim)
      scorer_2 = LinearRegressionUCB(self.x_dim)
      policy_1 = Policy(scorer=scorer_1, sampler=GreedyActionSampler())
      policy_2 = Policy(scorer=scorer_2, sampler=GreedyActionSampler())
      trainer_1 = LinUCBTrainer(policy_1)
      trainer_2 = LinUCBTrainer(policy_2)
  
      trainer_1.training_step(batch_with_weight, 0)
      trainer_1.on_train_epoch_end()
      for i in range(3):
          trainer_2.training_step(self.batch, i)
      trainer_2.on_train_epoch_end()
  
      npt.assert_array_less(
          np.zeros(scorer_1.avg_A.shape), scorer_1.avg_A.numpy()
      )  # make sure A got updated
      npt.assert_allclose(
          scorer_1.avg_A.numpy(), scorer_2.avg_A.numpy(), rtol=1e-4
      )
      npt.assert_allclose(
          scorer_1.avg_b.numpy(), scorer_2.avg_b.numpy(), rtol=1e-4
      )
  
imports: import copy
  import unittest
  import numpy
  import numpy.testing
  import torch
  from libfb.py.collections import AttrDict
  from pytorch_lightning.loggers import TensorBoardLogger
  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.linear_regression import LinearRegressionUCB
  from reagent.training.cb.linucb_trainer import LinUCBTrainer
  from reagent.training.cb.utils import add_chosen_arm_features
  from reagent.training.parameters import LinUCBTrainerParameters
  from torchrec.fb.metrics.meta_config import DefaultTaskInfo, MetricsConfig, QPSDef, RecMetricDef, RecMetricEnum
  from torchrec.fb.metrics.meta_metrics import generate_metric_module, RecMetricModule
label_desc: Use image node_id 6 for calling the TestLinUCB obj's underlying member method code with example usage: obj.test_linucb_weights() without return types