code: def test_merge_object_example():
      obj1 = Object(
          properties=[
              Property(name="a", dtype=DataType.string),
              Property(name="b", dtype=DataType.double),
          ]
      )
      obj1_dict = obj1.to_dict()
      obj2 = Object(
          properties=[
              Property(name="a", dtype=DataType.string),
              Property(name="c", dtype=DataType.boolean),
          ]
      )
      obj2_dict = obj2.to_dict()
      updated_obj = obj1._merge(obj2)
      assert updated_obj == Object(
          properties=[
              Property(name="a", dtype=DataType.string),
              Property(name="b", dtype=DataType.double, required=False),
              Property(
                  name="c", dtype=DataType.boolean, required=False
              ),
          ]
      )
      assert obj1.to_dict() == obj1_dict
      assert obj2.to_dict() == obj2_dict
  
imports: import datetime
  import json
  import math
  import re
  import numpy
  import pandas
  import pyspark
  import pyspark.sql.types
  import pytest
  from scipy.sparse import csc_matrix, csr_matrix
  from mlflow.exceptions import MlflowException
  from mlflow.models.utils import _enforce_tensor_spec
  from mlflow.pyfunc import _parse_spark_datatype
  from mlflow.types import DataType
  from mlflow.types.schema import Array, ColSpec, Object, ParamSchema, ParamSpec, Property, Schema, TensorSpec
  from mlflow.types.utils import _get_tensor_shape, _infer_colspec_type, _infer_param_schema, _infer_schema, _validate_input_dictionary_contains_only_strings_and_lists_of_strings
label_desc: Use image node_id 42 for calling a global function with example usage: test_merge_object_example() without return types