code: def test_synthetic():
      for device in ["llvm", "cuda"]:
          if not tvm.testing.device_enabled(device):
              print("skip because %s is not enabled..." % device)
              return
  
      input_shape = (1, 5, 23, 61)
  
      def verify(data):
          mod, params = relay.testing.synthetic.get_workload(
              input_shape=input_shape
          )
          with tvm.transform.PassContext(opt_level=3):
              lib = relay.build_module.build(mod, "llvm", params=params)
          dev = tvm.cpu()
          module = graph_executor.GraphModule(lib["default"](dev))
          module.set_input("data", data)
          module.run()
          out = module.get_output(0).numpy()
          return out
  
      (
          synthetic_mod,
          synthetic_params,
      ) = relay.testing.synthetic.get_workload(input_shape=input_shape)
      with tvm.transform.PassContext(opt_level=3):
          synthetic_gpu_lib = relay.build_module.build(
              synthetic_mod, "cuda", params=synthetic_params
          )
  
      temp = utils.tempdir()
      path_lib = temp.relpath("deploy_lib.so")
      synthetic_gpu_lib.export_library(path_lib)
  
      loaded_lib = tvm.runtime.load_module(path_lib)
      data = np.random.uniform(-1, 1, size=input_shape).astype(
          "float32"
      )
      dev = tvm.cuda()
      module = graph_executor.GraphModule(loaded_lib["default"](dev))
      module.set_input("data", data)
      module.run()
      out = module.get_output(0).numpy()
  
      tvm.testing.assert_allclose(out, verify(data), atol=1e-5)
  
file_path: tvm/tests/python/codegen/test_target_codegen_blob.py
imports: import ctypes
  import numpy
  from tvm import relay
  import tvm.relay.testing
  from tvm.contrib import graph_executor, cc, utils, popen_pool, tar
  import tvm
  import tvm.testing
  from tvm.script import ir, tir
label_desc: Use image node_id 1 for calling a global function with example usage: test_synthetic() and returns: out