class_docstr: A ``Predictor`` implementation for inference against TensorFlow Serving endpoints.
docstr: Placeholder docstring.
docstr_tok: ["Placeholder","docstring","."]
code: def classify(self, data):
      """Placeholder docstring."""
      return self._classify_or_regress(data, "classify")
  
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 2 for calling the TensorFlowPredictor obj's underlying member method code with example usage: obj.classify(data) and returns: self