code: def validate_model(original_model, new_model):
      df1, df2 = original_model.predict(
          "Hello World"
      ), new_model.predict("Hello World")
      if isinstance(df2, str):
          df2 = (
              pd.DataFrame(json.loads(df2))
              .drop(columns=["index"])
              .reset_index()
              .drop(columns=["index"])
          )
      else:
          df2 = df2.reset_index().drop(columns=["index"])
      df1 = df1.reset_index().drop(columns=["index"])
  
      df1, df2 = fix_dataframe_with_respect_for_nlu_issues(df1, df2)
      pd.testing.assert_frame_equal(df1, df2)
  
imports: import json
  import os
  from pathlib import Path
  from unittest import mock
  import pandas
  import pyspark
  import pytest
  from johnsnowlabs import nlp
  from packaging.version import Version
  import mlflow
  import mlflow.utils.file_utils
  from mlflow import pyfunc
  from mlflow.environment_variables import MLFLOW_DFS_TMP
  from mlflow.models import Model, infer_signature
  from mlflow.models.utils import _read_example
  from mlflow.pyfunc import spark_udf
  from mlflow.utils.environment import _mlflow_conda_env
  from mlflow.utils.file_utils import TempDir
  from tests.helper_functions import assert_register_model_called_with_local_model_path
label_desc: Use image node_id 4 for calling a global function with example usage: validate_model(original_model, new_model) without return types