code: def setUp(self) -> None:
      self._int_float_values = TestValues.TestIntKeyValues(
          [2.2, 4.4, 1.1, 3.3]
      )
      self._tuple_float_float_values = (
          TestValues.TestTupleFloatKeyValues(
              {
                  TestValues.TestTupleFloatType((1.0, 2.0)): 2.2,
                  TestValues.TestTupleFloatType((3.0, 4.0)): 4.4,
                  TestValues.TestTupleFloatType((5.0, 6.0)): 1.1,
                  TestValues.TestTupleFloatType((7.0, 8.0)): 3.3,
              }
          )
      )
      self._int_array_values = TestValues.TestIntKeyValues(
          np.array((2.2, 4.4, 1.1, 3.3))
      )
      self._int_tensor_values = TestValues.TestIntKeyValues(
          torch.tensor((2.2, 4.4, 1.1, 3.3))
      )
  
imports: import unittest
  from typing import Tuple, Union
  import numpy
  import torch
  from reagent.ope.estimators.types import ActionDistribution, TypeWrapper, Values
label_desc: Use image node_id 1 for calling the TestValues obj's underlying member method code with example usage: obj.setUp() without return types