code: def before_unrolled_loop(
      placeholder: T.Buffer((1, 56, 56, 64), "float32"),
  ) -> None:
      # function attr dict
      T.func_attr({"global_symbol": "main", "tir.noalias": True})
      bgemm = T.alloc_buffer([6, 6, 196, 64], dtype="float32")
      inverse = T.alloc_buffer([4, 4, 196, 64], dtype="float32")
      for i2_0, i3_0, i2_1, i3_1 in T.grid(98, 4, 2, 16):
          for i0 in T.unroll(4):
              for i1 in T.unroll(4):
                  for i4 in T.unroll(6):
                      for i5 in T.unroll(6):
                          with T.block("inverse"):
                              vh, vw = T.axis.remap("SS", [i0, i1])
                              p = T.axis.spatial(196, i2_0 * 2 + i2_1)
                              co = T.axis.spatial(64, i3_0 * 16 + i3_1)
                              r_a, r_b = T.axis.remap("RR", [i4, i5])
                              T.reads(bgemm[r_a, r_b, p, co])
                              T.writes(inverse[vh, vw, p, co])
                              with T.init():
                                  inverse[vh, vw, p, co] = T.float32(0)
                              inverse[vh, vw, p, co] = (
                                  inverse[vh, vw, p, co]
                                  + bgemm[r_a, r_b, p, co]
                              )
  
imports: import tvm
  from tvm import meta_schedule
  from tvm import tir
  from tvm.script import tir
  from tvm.target import Target
label_desc: Use image node_id 3 for calling a global function with example usage: before_unrolled_loop(placeholder) without return types