code: def test_compile_fused_identity_cast():
      # a fused function that would optimized to identity
      x = relay.var("x", shape=[16], dtype="float32")
      y = relay.cast(x, "float32")
      func1 = relay.Function([x], y).with_attr("Primitive", 1)
  
      # a fused function with param pass-through
      x = relay.var("x", shape=[16], dtype="float32")
      y = relay.add(x, relay.const(3.14, "float32"))
      func2 = relay.Function([x], relay.Tuple([x, y])).with_attr(
          "Primitive", 1
      )
  
      x_global = relay.var("xx", shape=[16], dtype="float32")
      tup = func2(x_global)
      y_global = func1(
          relay.TupleGetItem(tup, 0) + relay.TupleGetItem(tup, 1)
      )
  
      mod = tvm.IRModule.from_expr(relay.Function([x_global], y_global))
      for target, device in tvm.testing.enabled_targets():
          with tvm.transform.PassContext(opt_level=2):
              graph, lib, _ = relay.build(mod, target=target)
              executor = graph_executor.create(
                  graph, lib, device=device
              )
              executor.run()
  
imports: import numpy
  import pytest
  from unittest.mock import patch
  import tvm
  import json
  from tvm import relay
  from tvm.contrib import graph_executor
  from tvm.relay.op import add
  import tvm.testing
  from tvm.relay.testing import mlp
  from tvm import rpc
  from tvm.contrib import utils
label_desc: Use image node_id 13 for calling a global function with example usage: test_compile_fused_identity_cast() without return types