code: def test_triton_kernel_matmul_tracking(self):
      @triton.jit
      def ones_kernel(x_ptr, n_elements, BLOCK_SIZE: "tl.constexpr"):
          pid = tl.program_id(axis=0)
          block_start = pid * BLOCK_SIZE
          offsets = block_start + tl.arange(0, BLOCK_SIZE)
          mask = offsets < n_elements
          x = 1.0
          tl.store(x_ptr + offsets, x, mask=mask)
  
      @torch.compile
      def f(x):
          out = torch.zeros_like(x)
          ones_kernel[(4,)](out, 16, BLOCK_SIZE=16)
          return torch.mm(out, x) + 10
  
      x = torch.randn(4, 4, device="cuda")
      torch_out = f(x)
      python_out = torch.mm(torch.ones(4, 4, device="cuda"), x) + 10
      self.assertEqual(torch_out, python_out)
  
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 19 for calling the KernelTests obj's underlying member method code with example usage: obj.test_triton_kernel_matmul_tracking() and returns: unknown