code: def test_improper_stride(self) -> None:
      net = BasicModel_ConvNet_One_Conv()
      inp = torch.arange(16, dtype=torch.float).view(1, 1, 4, 4)
      occ = Occlusion(net)
      # Check error when too few stride dimensions
      with self.assertRaises(AssertionError):
          _ = occ.attribute(
              inp,
              sliding_window_shapes=(1, 2, 2),
              strides=(1, 2),
              target=0,
          )
  
      # Check error when too many stride dimensions
      with self.assertRaises(AssertionError):
          _ = occ.attribute(
              (inp, inp),
              sliding_window_shapes=((1, 1, 2), (1, 2, 2)),
              strides=((1, 1, 2), (2, 1, 2, 2)),
              target=0,
          )
  
      # Check error when too many stride tuples
      with self.assertRaises(AssertionError):
          _ = occ.attribute(
              (inp, inp),
              sliding_window_shapes=((1, 1, 2), (1, 2, 2)),
              strides=((1, 1, 2), (1, 2, 2), (1, 2, 2)),
              target=0,
          )
  
imports: import io
  import unittest
  import unittest.mock
  from typing import Any, Callable, Tuple, Union
  import torch
  from captum._utils.typing import BaselineType, TargetType, TensorLikeList, TensorOrTupleOfTensorsGeneric
  from captum.attr._core.occlusion import Occlusion
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel3, BasicModel_ConvNet_One_Conv, BasicModel_MultiLayer, BasicModel_MultiLayer_MultiInput
  from torch import Tensor
label_desc: Use image node_id 2 for calling the Test obj's underlying member method code with example usage: obj.test_improper_stride() without return types