code: def _get_column_indices(indices, inputs, multiple=False):
      """
      Taken from https://github.com/onnx/sklearn-onnx/blob/9939c089a467676f4ffe9f3cb91098c4841f89d8/skl2onnx/common/utils.py#L105.
      Returns the requested graph inpudes based on their indices or names. See `_parse._get_column_index`.
      Args:
          indices: variables indices or names
          inputs: model inputs
  
      Returns:
          a tuple *(variable name, list of requested indices)* if *multiple* is False, a dictionary *{ var_index: [ list of
          requested indices ] }* if *multiple* is True
      """
      if multiple:
          res = OrderedDict()
          for p in indices:
              pt_var, pt_i = _get_column_index(p, inputs)
              if pt_var not in res:
                  res[pt_var] = []
              res[pt_var].append(pt_i)
          return res
      else:
          pt_var = None
          pt_is = []
          for p in indices:
              pt_v, pt_i = _get_column_index(p, inputs)
              pt_is.append(pt_i)
              if pt_var is None:
                  pt_var = pt_v
              elif pt_var != pt_v:
                  raise NotImplementedError(
                      "Hummingbird is not able to merge multiple columns from "
                      "multiple variables ({0}). You should think about merging "
                      "initial types.".format([pt_var, pt_v])
                  )
          return {pt_var: pt_is}
  
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 26 for calling a global function with example usage: _get_column_indices(indices, inputs, multiple) and returns: res, dict