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: Placeholder docstring.
docstr_tok: ["Placeholder","docstring","."]
code: def _toolkit_and_version_from_tag(cls, image_tag):
      """Placeholder docstring."""
      tag_pattern = re.compile(
          "^([A-Z]*|[a-z]*)(\d.*)-(cpu|gpu)-(py2|py3)$"  # noqa: W605,E501 pylint: disable=anomalous-backslash-in-string
      )
      tag_match = tag_pattern.match(image_tag)
      if tag_match is not None:
          return tag_match.group(1), tag_match.group(2)
      return None, None
  
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 6 for calling the RLEstimator obj's underlying member method code with example usage: obj._toolkit_and_version_from_tag(cls, image_tag) and returns: None,  None, tag_match,  tag_match