code: def test_cat(self, dtype):
      def cat_along_dim(d):
          def forward_cat(*inputs):
              return torch.cat(inputs, d)
  
          return forward_cat
  
      for xshape in [
          [8, 8, 8, 8],
          [64, 8, 32],
          [2048, 64],
      ]:
          for d in range(len(xshape)):
              x = torch.rand(xshape)
              _, graph = self.checkTrace(
                  cat_along_dim(d), [x, x, x], dtype
              )
              self.assertGraphContainsExactly(
                  graph, LLGA_FUSION_GROUP, 1
              )
  
imports: import sys
  import torch
  import unittest
  import itertools
  import torch.nn
  from functools import wraps
  from concurrent import futures
  import torch.nn.functional
  import torch.fx.experimental.optimization
  from torch.testing._internal.jit_utils import JitTestCase
  from torch.testing._internal.common_utils import run_tests, TEST_SCIPY, IS_WINDOWS, IS_MACOS
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCPU, dtypes
label_desc: Use image node_id 16 for calling the TestOp obj's underlying member method code with example usage: obj.test_cat(dtype) and returns: forward_cat, torch