code: def test_ndarray_type(self):
      ndarray_val = TestTypes.TestClass(np.array(3))
      self.assertEqual(self._test_list[ndarray_val], 3)
      self.assertEqual(hash(ndarray_val), hash((3,)))
      ndarray_val_other = TestTypes.TestClass(np.array(3))
      self.assertEqual(ndarray_val, ndarray_val_other)
      int_val_other = TestTypes.TestClass(3)
      self.assertEqual(ndarray_val, int_val_other)
      ndarray_val_other = TestTypes.TestClass(np.array(4))
      self.assertNotEqual(ndarray_val, ndarray_val_other)
      ndarray_val = TestTypes.TestClass(np.array(((1, 2), (3, 4))))
      with self.assertRaises(ValueError):
          self._test_list[ndarray_val] = 1
      self.assertEqual(hash(ndarray_val), hash((1, 2, 3, 4)))
      ndarray_val_other = TestTypes.TestClass(((1, 2), (3, 4)))
      self.assertEqual(ndarray_val, ndarray_val_other)
      ndarray_val_other = TestTypes.TestClass(np.ndarray((1, 2, 3, 4)))
      self.assertNotEqual(ndarray_val, ndarray_val_other)
  
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 6 for calling the TestTypes obj's underlying member method code with example usage: obj.test_ndarray_type() without return types