code: def original_func() -> None:
      A = T.alloc_buffer((128, 128), "float32")
      for i0, j0 in T.grid(128, 128):
          with T.block():
              i, j = T.axis.remap("SS", [i0, j0])
              A[i, j] = T.float32(0)
      for i0, j0, k0 in T.grid(32, 32, 32):
          with T.block():
              i, j, k = T.axis.remap("SSR", [i0, j0, k0])
              B = T.alloc_buffer((128, 128), "float32")
              C = T.alloc_buffer((128, 128), "float32")
              D = T.alloc_buffer((128, 128), "float32")
              if k == 0:
                  for ii, jj in T.grid(4, 4):
                      B[i * 4 + ii, j * 4 + jj] = A[
                          i * 4 + ii, j * 4 + jj
                      ]
              for ii, jj in T.grid(4, 4):
                  for kk in range(0, 4):
                      B[i * 4 + ii, j * 4 + jj] += C[
                          i * 4 + ii, k * 4 + kk
                      ]
                  for kk in range(0, 4):
                      B[i * 4 + ii, j * 4 + jj] += (
                          D[j * 4 + jj, k * 4 + kk]
                          * C[i * 4 + ii, k * 4 + kk]
                      )
  
imports: import numpy
  import tvm
  import tvm.testing
  from tvm import te
  from tvm.script import tir
  from tvm import relay, tir
  from tvm.relay.backend.te_compiler import lower_to_primfunc
  from tvm.tir.tensor_intrin.hexagon import VRMPY_u8u8i32_INTRIN
label_desc: Use image node_id 4 for calling a global function with example usage: original_func() without return types