code: def validate_updated_conda_dependencies(
      original_model_path, wheeled_model_path
  ):
      # Check if conda.yaml files of the original model and wheeled model are the same
      # excluding the dependencies
      wheeled_model_path = os.path.join(
          wheeled_model_path, _CONDA_ENV_FILE_NAME
      )
      original_conda_env_path = os.path.join(
          original_model_path, _CONDA_ENV_FILE_NAME
      )
  
      with open(wheeled_model_path) as wheeled_conda_env, open(
          original_conda_env_path
      ) as original_conda_env:
          wheeled_conda_env = yaml.safe_load(wheeled_conda_env)
          original_conda_env = yaml.safe_load(original_conda_env)
  
          for key in wheeled_conda_env:
              if key != "dependencies":
                  assert (
                      wheeled_conda_env[key] == original_conda_env[key]
                  )
              else:
                  assert (
                      wheeled_conda_env[key] != original_conda_env[key]
                  )
  
imports: import json
  import os
  import random
  import re
  from collections import namedtuple
  import numpy
  import pandas
  import pytest
  import sklearn.neighbors
  import yaml
  from sklearn import datasets
  import mlflow
  import mlflow.pyfunc.scoring_server
  from mlflow.exceptions import MlflowException
  from mlflow.models.wheeled_model import _WHEELS_FOLDER_NAME, WheeledModel
  from mlflow.pyfunc.model import MLMODEL_FILE_NAME, Model
  from mlflow.store.artifact.utils.models import _improper_model_uri_msg
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.environment import _CONDA_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME, _is_pip_deps, _mlflow_conda_env
  from tests.helper_functions import _is_available_on_pypi, _mlflow_major_version_string, pyfunc_serve_and_score_model
label_desc: Use image node_id 7 for calling a global function with example usage: validate_updated_conda_dependencies(original_model_path, wheeled_model_path) without return types