code: def _fetch_input_slice(topology, inputs, column_indices):
      """
      Taken from https://github.com/onnx/sklearn-onnx/blob/9939c089a467676f4ffe9f3cb91098c4841f89d8/skl2onnx/_parse.py#L53.
      """
      if not isinstance(inputs, list):
          raise TypeError("Parameter inputs must be a list.")
      if len(inputs) == 0:
          raise RuntimeError(
              "Operator ArrayFeatureExtractor requires at least one inputs."
          )
      if len(inputs) != 1:
          raise RuntimeError(
              "Operator ArrayFeatureExtractor does not support multiple input tensors."
          )
      if (
          len(inputs) == 1
          and len(column_indices) == 1
          and inputs[0].type is not None
          and (
              len(inputs[0].type.shape) == 1
              or inputs[0].type.shape[1] == 1
          )
      ):
          return inputs
      array_feature_extractor_operator = (
          topology.declare_logical_operator(
              "SklearnArrayFeatureExtractor"
          )
      )
      array_feature_extractor_operator.inputs = inputs
      array_feature_extractor_operator.column_indices = column_indices
      output_variable_name = topology.declare_logical_variable(
          "extracted_feature_columns", inputs[0].type
      )
      array_feature_extractor_operator.outputs.append(
          output_variable_name
      )
      return array_feature_extractor_operator.outputs
  
imports: from collections import OrderedDict
  from copy import deepcopy
  import pprint
  from uuid import uuid4
  import numpy
  from onnxconverter_common.optimizer import LinkedNode, _topological_sort
  from sklearn import pipeline
  from sklearn.compose import ColumnTransformer
  from sklearn.ensemble import BaggingClassifier, BaggingRegressor
  from sklearn.model_selection import GridSearchCV, RandomizedSearchCV
  from sklearn.multioutput import MultiOutputRegressor, RegressorChain
  from sklearn.preprocessing import OneHotEncoder
  from .containers import CommonSklearnModelContainer, CommonONNXModelContainer, CommonSparkMLModelContainer
  from ._topology import Topology
  from ._utils import sklearn_installed, sparkml_installed
  from .operator_converters import constants
  from .supported import get_sklearn_api_operator_name, get_onnxml_api_operator_name, get_sparkml_api_operator_name
label_desc: Use image node_id 24 for calling a global function with example usage: _fetch_input_slice(topology, inputs, column_indices) and returns: array_feature_extractor_operator, inputs