code: def test_triton_kernel_various_args(self):
      @triton.autotune(
          configs=[triton.Config({"BLOCK_SIZE": 128})],
          key=[],
      )
      @triton.jit
      def pass_kernel(
          out_ptr,
          n_elements,
          dummy_None,
          dummy_empty,
          dummy_float,
          BLOCK_SIZE: "tl.constexpr",
          RANDOM_SIZE: "tl.constexpr",
      ):
          pass
  
      @torch.compile
      def call_triton(output):
          n_elements = output.numel()
          grid = (n_elements,)
          pass_kernel[grid](
              output,
              n_elements,
              None,
              torch.empty_like(output),
              3.1415926,
              RANDOM_SIZE=0,
          )
          return output
  
      output = torch.randn(5, device="cuda")
      # Make sure this does not crash
      call_triton(output)
  
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 11 for calling the KernelTests obj's underlying member method code with example usage: obj.test_triton_kernel_various_args() and returns: output