code: def test_gather_backward_with_empty_index_tensor(
      self, device, dtype, sparse_grad
  ):
      dim = -1
      input = torch.rand(
          [10, 5], dtype=dtype, device=device, requires_grad=True
      )
      index = torch.randint(
          0, 2, [3, 0], dtype=torch.int64, device=device
      )
      res = torch.gather(input, dim, index, sparse_grad=sparse_grad)
      res.sum().backward()
      grad = input.grad.to_dense() if sparse_grad else input.grad
      expected_grad = torch.zeros_like(input, requires_grad=False)
      self.assertEqual(grad, expected_grad, atol=0, rtol=0)
  
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 4 for calling the TestScatterGather obj's underlying member method code with example usage: obj.test_gather_backward_with_empty_index_tensor(device, dtype, sparse_grad) without return types