code: def Matmul(a: T.handle, b: T.handle, c: T.handle) -> None:
      T.func_attr({"global_symbol": "main"})
      A = T.match_buffer(a, (128, 256), "float32")
      B = T.match_buffer(b, (256, 512), "float32")
      C = T.match_buffer(c, (128, 512), "float32")
      for i, j, k in T.grid(128, 256, 512):
          with T.block("matmul"):
              vi, vj, vk = T.axis.remap("SSR", [i, j, k])
              with T.init():
                  C[vi, vj] = 0.0
              C[vi, vj] = C[vi, vj] + A[vi, vk] * B[vk, vj]
  
imports: from tvm.meta_schedule.arg_info import ArgInfo, TensorInfo
  from tvm.script import tir
label_desc: Use image node_id 1 for calling a global function with example usage: Matmul(a, b, c) without return types