code: def config_value_impl(
      sagemaker_session: Session,
      config_path: str,
      sagemaker_config: dict,
  ):
      if config_path == TRAINING_JOB_ENABLE_NETWORK_ISOLATION_PATH:
          return config_enable_network_isolation
  
      if config_path == TRAINING_JOB_ROLE_ARN_PATH:
          return config_role
  
      if config_path == TRAINING_JOB_INTER_CONTAINER_ENCRYPTION_PATH:
          return config_intercontainer_encryption
  
      if config_path == MODEL_EXECUTION_ROLE_ARN_PATH:
          return config_inference_role
  
      if config_path == MODEL_ENABLE_NETWORK_ISOLATION_PATH:
          return config_inference_enable_network_isolation
  
      raise AssertionError(f"Bad config path: {config_path}")
  
imports: from __future__ import absolute_import
  import random
  from unittest import mock
  import unittest
  from sagemaker.base_predictor import Predictor
  from sagemaker.config.config_schema import MODEL_ENABLE_NETWORK_ISOLATION_PATH, MODEL_EXECUTION_ROLE_ARN_PATH, TRAINING_JOB_ENABLE_NETWORK_ISOLATION_PATH, TRAINING_JOB_INTER_CONTAINER_ENCRYPTION_PATH, TRAINING_JOB_ROLE_ARN_PATH
  from sagemaker.jumpstart.constants import DEFAULT_JUMPSTART_SAGEMAKER_SESSION
  from sagemaker.jumpstart.estimator import JumpStartEstimator
  from sagemaker.session import Session
  from sagemaker.utils import resolve_value_from_config
  from tests.unit.sagemaker.jumpstart.utils import get_special_model_spec
label_desc: Use image node_id 1 for calling a global function with example usage: config_value_impl(sagemaker_session, config_path, sagemaker_config) and returns: config_enable_network_isolation, config_role, config_intercontainer_encryption, config_inference_role, config_inference_enable_network_isolation