def METHOD_NAME():
    m, n, k = 128, 128, 128
    axis_k = te.reduce_axis((0, k), "k")
    A = te.placeholder((m, k), name="A")
    B = te.placeholder((k, n), name="B")
    C = te.compute((m, n), lambda x, y: te.sum(A[x, axis_k] * B[y, axis_k], axis=axis_k), name="C")
    s = te.create_schedule(C.op)
    # check lowering with the CSE pass disabled as otherwise it would do some commoning
    with tvm.transform.PassContext(opt_level=3, disabled_pass=["tir.CommonSubexprElimTIR"]):
        ir_mod = tvm.lower(s, [A, B, C])
    tvm.ir.assert_structural_equal(ir_mod, LoweredModule)
    # check building
    mod = tvm.build(s, [A, B, C], target="llvm")
    _check_module_with_numpy(mod)