class_docstr: A ``FrameworkModel`` implementation for inference with TensorFlow Serving.
docstr: Return true if TF version is EIA enabled
docstr_tok: ["Return","true","if","TF","version","is","EIA","enabled"]
code: def _eia_supported(self):
      """Return true if TF version is EIA enabled"""
      framework_version = [
          int(s) for s in self.framework_version.split(".")
      ][:2]
      return (
          framework_version != [2, 1]
          and framework_version != [2, 2]
          and framework_version <= self.LATEST_EIA_VERSION
      )
  
imports: from __future__ import absolute_import
  import logging
  from typing import Union, Optional, List, Dict
  import sagemaker
  from sagemaker import image_uris, s3, ModelMetrics
  from sagemaker.deserializers import JSONDeserializer
  from sagemaker.deprecations import removed_kwargs
  from sagemaker.drift_check_baselines import DriftCheckBaselines
  from sagemaker.metadata_properties import MetadataProperties
  from sagemaker.predictor import Predictor
  from sagemaker.serializers import JSONSerializer
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.workflow.pipeline_context import PipelineSession
  from sagemaker.utils import format_tags
label_desc: Use image node_id 4 for calling the TensorFlowModel obj's underlying member method code with example usage: obj._eia_supported() and returns: unknown