code: def _is_image_deep_feature_sarray(feature_sarray, model_name):
      """
      Finds if the given `SArray` has extracted features for a given model_name.
      """
      from array import array
  
      if not (len(feature_sarray) > 0):
          return False
      if feature_sarray.dtype != array:
          return False
      if type(feature_sarray[0]) != array:
          return False
      if (
          len(feature_sarray[0])
          != MODEL_TO_FEATURE_SIZE_MAPPING[model_name]
      ):
          raise _ToolkitError(
              "The given deep features are for a model other than {model_name}.".format(
                  model_name=model_name
              )
          )
      return True
  
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 6 for calling a global function with example usage: _is_image_deep_feature_sarray(feature_sarray, model_name) and returns: True, False, False, False