code: def test_multi_input():
      mod = tvm.relay.parse(
          """
  #[version = "0.0.5"]
  def @test_fused_add(%x: Tensor[(5, 7), float32], %y: Tensor[(5, 7), float32]) { %x }
  
  def @main(%a: Tensor[(5, 7), float32], %b: Tensor[(5, 7), float32]) -> Tensor[(5, 7), float32] {
    %0 = (%a, %b) /* ty=(Tensor[(5, 7), float32], Tensor[(5, 7), float32]) */;
    call_lowered(@test_fused_add, %0) /* ty=Tensor[(5, 7), float32] */
  }
          """,
      )
  
      # fmt: off
      @T.prim_func
      def func(a: T.handle, b: T.handle, output: T.handle) -> None:
          # function attr dict
          T.func_attr({"global_symbol": "test_mod___tvm_main__", "runner_function": True, "target": T.target({"kind":"llvm", "tag":"", "keys":["cpu"]}), "input_vars": [a, b], "output_vars": [output], "devices": []})
          a_buffer = T.match_buffer(a, [5, 7], dtype="float32", align=16)
          b_buffer = T.match_buffer(b, [5, 7], dtype="float32", align=16)
          output_buffer = T.match_buffer(output, [5, 7], dtype="float32", align=16)
          # body
          T.evaluate(T.tvm_call_cpacked("test_fused_add", a_buffer.data, b_buffer.data, output_buffer.data, T.reinterpret(T.uint64(0), dtype="handle"), dtype="int32"))
      # fmt: on
  
      _assert_lowered_main(mod, func, CallType.CPacked)
  
imports: import numpy
  import pytest
  import tvm
  import tvm.testing
  from tvm.ir import assert_structural_equal
  from tvm.relay.backend.aot import AOTLowerMain, CallType
  from tvm.script import tir
label_desc: Use image node_id 13 for calling a global function with example usage: test_multi_input() without return types