code: def test_multiple_output():
      x = relay.var("x", shape=(1, 3, 48, 16), dtype="float32")
      t = relay.split(x, [12, 16, 32], 2).astuple()
      x0 = relay.TupleGetItem(t, 0)
      x1 = relay.TupleGetItem(t, 1)
      x2 = relay.TupleGetItem(t, 2)
      x3 = relay.TupleGetItem(t, 3)
      p0 = relay.const(
          np.random.uniform(-1, 1, (3, 3, 1, 1)).astype("float32")
      )
      y = (
          relay.nn.conv2d(
              x2,
              p0,
              kernel_size=(1, 1),
              kernel_layout="OIHW",
              out_dtype="float32",
          )
          + x3
      )
  
      func = relay.Function([x], relay.Tuple([x0, x1, y]))
      mod = tvm.IRModule.from_expr(func)
      mod = relay.transform.InferType()(mod)
      target = tvm.target.Target("llvm")
      device = tvm.cpu()
      lib = relay.build(mod, target=target)
      m = debug_executor.GraphModuleDebug(
          lib["debug_create"]("default", device),
          [device],
          lib.get_graph_json(),
          None,
      )
      nodes = m.debug_datum.get_graph_nodes()
      assert nodes[2]["shape"] == [3, 3, 1, 1]
  
imports: import json
  import os
  import re
  import sys
  import time
  from distutils.log import debug
  import numpy
  import pytest
  import tvm
  import tvm.testing
  from tvm import rpc, te
  from tvm._ffi.base import TVMError
  from tvm.contrib import utils
  from tvm.contrib.debugger import debug_executor
  from tvm import relay
label_desc: Use image node_id 10 for calling a global function with example usage: test_multiple_output() without return types