code: def test_get_jsonnable_obj():
      from mlflow.pyfunc.scoring_server import _get_jsonable_obj
  
      py_ary = [["a", "b", "c"], ["e", "f", "g"]]
      np_ary = _get_jsonable_obj(np.array(py_ary))
      assert json.dumps(py_ary, cls=NumpyEncoder) == json.dumps(
          np_ary, cls=NumpyEncoder
      )
      np_ary = _get_jsonable_obj(np.array(py_ary, dtype=type(str)))
      assert json.dumps(py_ary, cls=NumpyEncoder) == json.dumps(
          np_ary, cls=NumpyEncoder
      )
  
imports: import json
  import math
  import os
  import random
  import signal
  from collections import namedtuple
  from io import StringIO
  import keras
  import numpy
  import pandas
  import pytest
  import sklearn.neighbors
  from packaging.version import Version
  from sklearn import datasets
  import mlflow.pyfunc.scoring_server
  import mlflow.sklearn
  from mlflow.models import ModelSignature, infer_signature
  from mlflow.protos.databricks_pb2 import BAD_REQUEST, ErrorCode
  from mlflow.pyfunc import PythonModel
  from mlflow.pyfunc.scoring_server import get_cmd
  from mlflow.types import ColSpec, DataType, ParamSchema, ParamSpec, Schema
  from mlflow.types.schema import Array, Object, Property
  from mlflow.utils import env_manager
  from mlflow.utils.file_utils import TempDir
  from mlflow.utils.proto_json_utils import NumpyEncoder
  from mlflow.version import VERSION
  from tests.helper_functions import expect_status_code, pyfunc_serve_and_score_model, random_int, random_str
label_desc: Use image node_id 29 for calling a global function with example usage: test_get_jsonnable_obj() without return types