code: def retrieve_default(
      endpoint_name: str,
      sagemaker_session: Session = DEFAULT_JUMPSTART_SAGEMAKER_SESSION,
      region: Optional[str] = None,
      model_id: Optional[str] = None,
      model_version: Optional[str] = None,
      tolerate_vulnerable_model: bool = False,
      tolerate_deprecated_model: bool = False,
  ) -> Predictor:
      """Retrieves the default predictor for the model matching the given arguments.
  
      Args:
          endpoint_name (str): Endpoint name for which to create a predictor.
          sagemaker_session (Session): The SageMaker Session to attach to the Predictor.
              (Default: sagemaker.jumpstart.constants.DEFAULT_JUMPSTART_SAGEMAKER_SESSION).
          region (str): The AWS Region for which to retrieve the default predictor.
              (Default: None).
          model_id (str): The model ID of the model for which to
              retrieve the default predictor. (Default: None).
          model_version (str): The version of the model for which to retrieve the
              default predictor. (Default: None).
          tolerate_vulnerable_model (bool): True if vulnerable versions of model
              specifications should be tolerated (exception not raised). If False, raises an
              exception if the script used by this version of the model has dependencies with known
              security vulnerabilities. (Default: False).
          tolerate_deprecated_model (bool): True if deprecated models should be tolerated
              (exception not raised). False if these models should raise an exception.
              (Default: False).
      Returns:
          Predictor: The default predictor to use for the model.
  
      Raises:
          ValueError: If the combination of arguments specified is not supported.
      """
  
      if not is_jumpstart_model_input(model_id, model_version):
          raise ValueError(
              "Must specify JumpStart `model_id` and `model_version` "
              "when retrieving default predictor."
          )
  
      predictor = Predictor(
          endpoint_name=endpoint_name,
          sagemaker_session=sagemaker_session,
      )
  
      return get_default_predictor(
          predictor=predictor,
          model_id=model_id,
          model_version=model_version,
          region=region,
          tolerate_deprecated_model=tolerate_deprecated_model,
          tolerate_vulnerable_model=tolerate_vulnerable_model,
          sagemaker_session=sagemaker_session,
      )
  
imports: from __future__ import print_function, absolute_import
  from typing import Optional
  from sagemaker.jumpstart.constants import DEFAULT_JUMPSTART_SAGEMAKER_SESSION
  from sagemaker.jumpstart.factory.model import get_default_predictor
  from sagemaker.jumpstart.utils import is_jumpstart_model_input
  from sagemaker.session import Session
  from sagemaker.base_predictor import Predictor, PredictorBase, RealTimePredictor
label_desc: Use image node_id 1 for calling a global function with example usage: retrieve_default(endpoint_name, sagemaker_session, region, model_id, model_version, tolerate_vulnerable_model, tolerate_deprecated_model) and returns: get_default_predictor