code: def _find_only_image_extracted_features_column(sframe, model_name):
      """
      Finds the only column in `sframe` with a type of array.array and has
      the length same as the last layer of the model in use.
      If there are zero or more than one image columns, an exception will
      be raised.
      """
      from array import array
  
      feature_column = _tkutl._find_only_column_of_type(
          sframe,
          target_type=array,
          type_name="array",
          col_name="deep_features",
      )
      if _is_image_deep_feature_sarray(
          sframe[feature_column], model_name
      ):
          return feature_column
      else:
          raise _ToolkitError(
              'No "{col_name}" column specified and no column with expected type "{type_name}" is found.'.format(
                  col_name="deep_features", type_name="array"
              )
          )
  
file_path: turicreate/src/python/turicreate/toolkits/image_analysis/image_analysis.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import turicreate
  import turicreate.toolkits._internal_utils
  from turicreate.toolkits._main import ToolkitError
  import turicreate.toolkits._internal_utils
  from .._internal_utils import _mac_ver
  from ..None import _pre_trained_models
  from ...data_structures.image import Image
  from ..None import _image_feature_extractor
label_desc: Use image node_id 5 for calling a global function with example usage: _find_only_image_extracted_features_column(sframe, model_name) and returns: feature_column