code: def test_EmpiricalBayesThompsonSamplerFit(self) -> None:
      generator = EmpiricalBayesThompsonSampler(min_weight=0.0)
      generator.fit(
          # pyre-fixme[6]: For 1st param expected `List[List[List[Union[None,
          #  bool, float, int, str]]]]` but got `List[List[List[int]]]`.
          Xs=self.Xs,
          # pyre-fixme[6]: For 2nd param expected `List[List[float]]` but got
          #  `List[List[int]]`.
          Ys=self.Ys,
          # pyre-fixme[6]: For 3rd param expected `List[List[float]]` but got
          #  `List[List[int]]`.
          Yvars=self.Yvars,
          # pyre-fixme[6]: For 4th param expected `List[List[Union[None, bool,
          #  float, int, str]]]` but got `List[List[int]]`.
          parameter_values=self.parameter_values,
          outcome_names=self.outcome_names,
      )
      self.assertEqual(generator.X, self.Xs[0])
      self.assertTrue(
          np.allclose(
              np.array(generator.Ys),
              np.array(
                  [[1.3, 2.1, 2.9, 3.7], [0.25, 0.25, 0.25, 0.25]]
              ),
          )
      )
      self.assertTrue(
          np.allclose(
              np.array(generator.Yvars),
              np.array(
                  [
                      [1.03, 0.87, 0.87, 1.03],
                      [0.375, 0.375, 0.375, 1.375],
                  ]
              ),
          )
      )
  
file_path: Ax/ax/models/tests/test_eb_thompson.py
imports: from unittest.mock import patch
  import numpy
  from ax.models.discrete.eb_thompson import EmpiricalBayesThompsonSampler
  from ax.utils.common.testutils import TestCase
label_desc: Use image node_id 2 for calling the EmpiricalBayesThompsonSamplerTest obj's underlying member method code with example usage: obj.test_EmpiricalBayesThompsonSamplerFit() without return types