code: def get_numeric_features_to_observed_range(examples):
      """Returns numerical features and their observed ranges.
  
      Args:
        examples: Examples to read to get ranges.
  
      Returns:
        A dict mapping feature_name -> {'observedMin': 'observedMax': } dicts,
        with a key for each numerical feature.
      """
      observed_features = collections.defaultdict(
          list
      )  # name -> [value, ]
      for example in examples:
          for feature_name in get_numeric_feature_names(example):
              original_feature = parse_original_feature_from_example(
                  example, feature_name
              )
              observed_features[feature_name].extend(
                  original_feature.original_value
              )
      return {
          feature_name: {
              "observedMin": min(feature_values),
              "observedMax": max(feature_values),
          }
          for feature_name, feature_values in iteritems(
              observed_features
          )
      }
  
imports: from __future__ import division
  from __future__ import print_function
  import collections
  import copy
  import json
  import math
  from absl import logging
  import numpy
  import tensorflow
  from google.protobuf import json_format
  from six import binary_type, string_types, integer_types
  from six import iteritems
  from six.moves import zip
  from inspect import signature
  from utils import common_utils
  from utils import platform_utils
  from tensorflow_serving.apis import classification_pb2
  from tensorflow_serving.apis import inference_pb2
  from tensorflow_serving.apis import regression_pb2
label_desc: Use image node_id 7 for calling a global function with example usage: get_numeric_features_to_observed_range(examples) and returns: unknown