code: def main(
      p0: T.Buffer((128, 128), "float32"),
      p1: T.Buffer((128, 128), "float32"),
      T_matmul_NT: T.Buffer((128, 128), "float32"),
  ) -> None:
      # function attr dict
      T.func_attr(
          {
              "layout_free_buffers": [1],
              "tir.noalias": True,
              "global_symbol": "main",
          }
      )
      # body
      # with T.block("root")
      for i0, i1, i2 in T.grid(128, 128, 128):
          with T.block("T_matmul_NT"):
              i, j, k = T.axis.remap("SSR", [i0, i1, i2])
              T.reads(p0[i, k], p1[j, k])
              T.writes(T_matmul_NT[i, j])
              T.block_attr({"layout_free_placeholders": []})
              with T.init():
                  T_matmul_NT[i, j] = T.float32(0)
              T_matmul_NT[i, j] = (
                  T_matmul_NT[i, j] + p0[i, k] * p1[j, k]
              )
  
imports: import pytest
  import tvm
  import tvm.meta_schedule
  import tvm.testing
  from tvm.script import tir
  from tvm.target import Target
  from tvm.target.codegen import llvm_lookup_intrinsic_id
  from tvm.tir import Schedule, floordiv, floormod
  from tvm.tir.tensor_intrin.cuda import *
  from tvm.tir.tensor_intrin.x86 import VNNI_DOT_16x4_INTRIN
label_desc: Use image node_id 1 for calling the Dense obj's underlying member method code with example usage: obj.main(p0, p1, T_matmul_NT) without return types