class_docstr: Handle end-to-end training and deployment of custom RLEstimator code.
class_docstr_tok: ["Handle","end-to-end","training","and","deployment","of","custom","RLEstimator","code","."]
docstr: Toolkit name and framework name for retrieving Docker image URI config.
docstr_tok: ["Toolkit","name","and","framework","name","for","retrieving","Docker","image","URI","config","."]
code: def _image_framework(self):
      """Toolkit name and framework name for retrieving Docker image URI config."""
      return "-".join((self.toolkit, self.framework))
  
imports: from __future__ import absolute_import
  import enum
  import logging
  import re
  from typing import Union, Optional, List, Dict
  from sagemaker import image_uris, fw_utils
  from sagemaker.estimator import Framework, EstimatorBase
  from sagemaker.model import FrameworkModel, SAGEMAKER_OUTPUT_LOCATION
  from sagemaker.mxnet.model import MXNetModel
  from sagemaker.tensorflow.model import TensorFlowModel
  from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
  from sagemaker.workflow.entities import PipelineVariable
label_desc: Use image node_id 12 for calling the RLEstimator obj's underlying member method code with example usage: obj._image_framework() and returns: str