code: def test_gather_expanded_index(self, device, dtype):
      # Test when index is [N, 1], which would have stride [1, 0]
      # should be excluded from the fast path when index ix expanded
      input = torch.arange(25).view(5, 5)
      input2 = input.to(dtype=dtype)
  
      idx = torch.arange(5).view(5, 1)
      out = torch.gather(input, 0, idx)
      out2 = torch.gather(input2, 0, idx)
  
      self.assertEqual(out.to(dtype=dtype), out2)
  
      def helper(input_size, idx_size):
          input = torch.randn(input_size, device=device).to(dtype=dtype)
          input2 = input.clone()
  
          shape = [1] * len(input_size)
          shape[0] = idx_size
          dim_size = input_size[0]
          idx = torch.randint(0, dim_size, shape)
  
          # Test the fast path on gather when index is expanded
          expanded_shape = input_size
          expanded_shape[0] = idx_size
          idx = idx.expand(expanded_shape)
          idx2 = idx.contiguous()
  
          out = torch.gather(input, 0, idx)
          out2 = torch.gather(input2, 0, idx2)
  
          self.assertEqual(out, out2)
  
      helper([50, 17], 100)
      helper([50, 1], 100)
      helper([50, 8, 7], 100)
      helper([50, 3, 4, 5], 100)
  
imports: import random
  import torch
  from torch.testing import make_tensor
  from torch.testing._internal.common_utils import parametrize, run_tests, TestCase, DeterministicGuard
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCPU, dtypes, dtypesIfCUDA, toleranceOverride, tol
  from torch.testing._internal.common_dtype import get_all_dtypes
label_desc: Use image node_id 17 for calling the TestScatterGather obj's underlying member method code with example usage: obj.test_gather_expanded_index(device, dtype) without return types