code: def test_simple_multi_input_int_to_float(self) -> None:
      net = BasicModel3()
  
      def wrapper_func(*inp):
          return net(*inp).float()
  
      inp1 = torch.tensor([[-10], [3]])
      inp2 = torch.tensor([[-5], [1]])
      self._occlusion_test_assert(
          wrapper_func,
          (inp1, inp2),
          ([[0.0], [1.0]], [[0.0], [-1.0]]),
          sliding_window_shapes=((1,), (1,)),
      )
  
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 6 for calling the Test obj's underlying member method code with example usage: obj.test_simple_multi_input_int_to_float() and returns: net