code: def _raise_error_if_not_drawing_classifier_input_sframe(
      dataset, feature, target
  ):
      """
      Performs some sanity checks on the SFrame provided as input to
      `turicreate.drawing_classifier.create` and raises a ToolkitError
      if something in the dataset is missing or wrong.
      """
      from turicreate.toolkits._internal_utils import (
          _raise_error_if_not_sframe,
      )
  
      _raise_error_if_not_sframe(dataset)
      if feature not in dataset.column_names():
          raise _ToolkitError(
              "Feature column '%s' does not exist" % feature
          )
      if target not in dataset.column_names():
          raise _ToolkitError(
              "Target column '%s' does not exist" % target
          )
      if (
          dataset[feature].dtype != _tc.Image
          and dataset[feature].dtype != list
      ):
          raise _ToolkitError(
              "Feature column must contain images"
              + " or stroke-based drawings encoded as lists of strokes"
              + " where each stroke is a list of points and"
              + " each point is stored as a dictionary"
          )
      if dataset[target].dtype != int and dataset[target].dtype != str:
          raise _ToolkitError(
              "Target column contains "
              + str(dataset[target].dtype)
              + " but it must contain strings or integers to represent"
              + " labels for drawings."
          )
      if len(dataset) == 0:
          raise _ToolkitError("Input Dataset is empty!")
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import turicreate
  from turicreate.toolkits import _coreml_utils
  from turicreate.toolkits._model import Model
  import turicreate.toolkits._internal_utils
  from turicreate.toolkits._main import ToolkitError
  from turicreate._deps.minimal_package import _minimal_package_import_check
  from ..image_classifier._evaluation import Evaluation
  from ..None import _pre_trained_models
label_desc: Use image node_id 1 for calling a global function with example usage: _raise_error_if_not_drawing_classifier_input_sframe(dataset, feature, target) without return types