class_docstr: Handle end-to-end training and deployment of user-provided TensorFlow code.
class_docstr_tok: ["Handle","end-to-end","training","and","deployment","of","user-provided","TensorFlow","code","."]
docstr: Placeholder docstring
docstr_tok: ["Placeholder","docstring"]
code: def _only_python_3_supported(self):
      """Placeholder docstring"""
      if not self.framework_version:
          return False
      return (
          version.Version(self.framework_version)
          > self._HIGHEST_PYTHON_2_VERSION
      )
  
imports: from __future__ import absolute_import
  import logging
  from typing import Optional, Union, Dict
  from packaging import version
  from sagemaker import image_uris, s3, utils
  from sagemaker.deprecations import renamed_kwargs
  from sagemaker.estimator import Framework, EstimatorBase
  import sagemaker.fw_utils
  from sagemaker.tensorflow import defaults
  from sagemaker.tensorflow.model import TensorFlowModel
  from sagemaker.transformer import Transformer
  from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.tensorflow.training_compiler.config import TrainingCompilerConfig
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.utils import format_tags
label_desc: Use image node_id 4 for calling the TensorFlow obj's underlying member method code with example usage: obj._only_python_3_supported() and returns: unknown, False