code: def test_ndarray_reflection():
      # Make two `NDArrayWrapper`s that point to the same underlying array.
      np_array = np.random.uniform(size=(10, 2)).astype("float32")
      tvm_array = tvm.nd.array(np_array)
      param_dict = {"x": tvm_array, "y": tvm_array}
      assert param_dict["x"].same_as(param_dict["y"])
      # Serialize then deserialize `param_dict`.
      deser_param_dict = relay.load_param_dict(
          runtime.save_param_dict(param_dict)
      )
      # Make sure the data matches the original data and `x` and `y` contain the same data.
      np.testing.assert_equal(
          deser_param_dict["x"].numpy(), tvm_array.numpy()
      )
      # Make sure `x` and `y` contain the same data.
      np.testing.assert_equal(
          deser_param_dict["x"].numpy(), deser_param_dict["y"].numpy()
      )
  
file_path: tvm/tests/python/relay/test_param_dict.py
imports: import os
  import numpy
  import tvm
  from tvm import te, runtime
  import json
  import base64
  from tvm._ffi.base import py_str
  from tvm.relay.op import add
  from tvm import relay
  from tvm import rpc
  from tvm.contrib import utils, graph_executor
label_desc: Use image node_id 2 for calling a global function with example usage: test_ndarray_reflection() without return types