class_docstr: Plugin for understanding/debugging model inference.
    
class_docstr_tok: ["Plugin","for","understanding\/debugging","model","inference","."]
docstr: Returns a list of JSON objects for each feature in the example.
  
  Args:
    request: A request for features.
  
  Returns:
    A list with a JSON object for each feature.
    Numeric features are represented as {name: observedMin: observedMax:}.
    Categorical features are represented as {name: samples:[]}.
code: def _eligible_features_from_example_handler(self, request):
      """Returns a list of JSON objects for each feature in the example.
  
      Args:
        request: A request for features.
  
      Returns:
        A list with a JSON object for each feature.
        Numeric features are represented as {name: observedMin: observedMax:}.
        Categorical features are represented as {name: samples:[]}.
      """
      features_list = inference_utils.get_eligible_features(
          self.examples[0:NUM_EXAMPLES_TO_SCAN], NUM_MUTANTS
      )
      return http_util.Respond(
          request, features_list, "application/json"
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import io
  import json
  import logging
  import math
  import numpy
  import os
  import werkzeug
  from werkzeug import wrappers
  from six.moves import xrange
  from google.protobuf import json_format
  from grpc.framework.interfaces.face.face import AbortionError
  from werkzeug import wrappers
  import tensorflow
  from tensorboard.backend import http_util
  from tensorboard.plugins import base_plugin
  from utils import common_utils
  from utils import inference_utils
  from utils import platform_utils
label_desc: Use image node_id 16 for calling the WhatIfToolPlugin obj's underlying member method code with example usage: obj._eligible_features_from_example_handler(request) and returns: http_util