code: def test_block_ptr_matmul_no_scf(shape, num_warps):
      capability = torch.cuda.get_device_capability()
      if capability[0] >= 9:
          pytest.skip("Hopper support is working in progress")
  
      m, n, k = shape
      a = torch.randn((m, k), device="cuda", dtype=torch.float16)
      b = torch.randn((k, n), device="cuda", dtype=torch.float16)
      c = torch.empty((m, n), device="cuda", dtype=torch.float32)
  
      grid = lambda META: (1,)
      matmul_no_scf_with_advance_kernel[grid](
          a_ptr=a,
          b_ptr=b,
          c_ptr=c,  #
          M=m,
          N=n,
          K=k,  #
          stride_am=a.stride(0),
          stride_ak=a.stride(1),  #
          stride_bk=b.stride(0),
          stride_bn=b.stride(1),  #
          stride_cm=c.stride(0),
          stride_cn=c.stride(1),  #
          BLOCK_M=m,
          BLOCK_N=n,
          BLOCK_K=k,  #
          num_warps=num_warps,
      )
      golden = torch.matmul(a, b)
      torch.testing.assert_close(c, golden, check_dtype=False)
  
imports: import pytest
  import torch
  import triton
  import triton.language
label_desc: Use image node_id 4 for calling a global function with example usage: test_block_ptr_matmul_no_scf(shape, num_warps) without return types