code: def test_reduce_fusion_layers(self):
      expected_output_for_method = {
          "max": torch.Tensor(
              [[[4, 2], [3, 4]], [[5, 6], [6, 5]], [[4, 3], [5, 2]]]
          ).float(),
          "sum": torch.Tensor(
              [[[5, 0], [6, 4]], [[5, 8], [10, 8]], [[7, 4], [7, 3]]]
          ).float(),
          "prod": torch.Tensor(
              [
                  [[4, -4], [9, 0]],
                  [[0, 12], [24, 15]],
                  [[12, 3], [10, 2]],
              ]
          ).float(),
      }
  
      for method, expected_output in expected_output_for_method.items():
          model = make_fusion_layer(
              method,
              [
                  self.fake_input_1.shape[-1],
                  self.fake_input_2.shape[-1],
              ],
          )
          output = model([self.fake_input_1, self.fake_input_2])
          self.assertTrue(torch.equal(output, expected_output))
          self.assertEqual(
              model.output_dim, self.fake_input_1.shape[-1]
          )
  
file_path: pytorchvideo/tests/test_layers_fusion.py
imports: import unittest
  import torch
  from pytorchvideo.layers import make_fusion_layer
label_desc: Use image node_id 2 for calling the TestFusion obj's underlying member method code with example usage: obj.test_reduce_fusion_layers() without return types