code: def test_triton_kernel_dependancies(self):
      def call_triton(
          x: torch.Tensor,
          y: torch.Tensor,
      ):
          output = torch.zeros_like(x)
          n_elements = output.numel()
          grid = lambda meta: (
              triton.cdiv(n_elements, meta["BLOCK_SIZE"]),
          )
          add_kernel_autotuned[grid](x, y, output, n_elements)
          output2 = torch.zeros_like(output)
          add_kernel_autotuned[grid](output, y, output2, n_elements)
          output3 = torch.add(output2, 1)
          return output3
  
      t1 = torch.rand(5, device="cuda")
      t2 = torch.rand(5, device="cuda")
      torch_result = call_triton(t1, t2)
      compiled_result = torch.compile(call_triton)(t1, t2)
      self.assertEqual(torch_result, compiled_result)
  
imports: from unittest.mock import patch
  import torch
  import torch._dynamo.test_case
  import torch._dynamo.testing
  from torch._higher_order_ops.triton_kernel_wrap import triton_kernel_wrapper_functional, triton_kernel_wrapper_mutation
  from torch._inductor import metrics
  from torch.testing._internal import common_utils
  from torch.testing._internal.common_utils import skipIfRocm
  from torch.testing._internal.triton_utils import *
label_desc: Use image node_id 12 for calling the KernelTests obj's underlying member method code with example usage: obj.test_triton_kernel_dependancies() and returns: output3