code: def _is_sklearn_model(sk_obj):
      if not (_HAS_SKLEARN):
          raise RuntimeError(
              "scikit-learn not found. scikit-learn conversion API is disabled."
          )
      from sklearn.pipeline import Pipeline as sk_Pipeline
  
      return (
          isinstance(sk_obj, sk_Pipeline)
          or sk_obj.__class__ in _converter_lookup
      )
  
imports: from ...models import _feature_management
  from ...models import datatypes
  from ...models.feature_vectorizer import create_feature_vectorizer
  from ...models.pipeline import Pipeline, PipelineRegressor, PipelineClassifier
  from ..._deps import _HAS_SKLEARN
  from collections import namedtuple
  import numpy
  from six import string_types
  from .None import _one_hot_encoder
  from .None import _dict_vectorizer
  from .None import _NuSVC
  from .None import _NuSVR
  from .None import _SVC
  from .None import _SVR
  from .None import _LinearSVC
  from .None import _LinearSVR
  from .None import _linear_regression
  from .None import _decision_tree_classifier
  from .None import _decision_tree_regressor
  from .None import _gradient_boosting_classifier
  from .None import _gradient_boosting_regressor
  from .None import _logistic_regression
  from .None import _normalizer
  from .None import _imputer
  from .None import _random_forest_classifier
  from .None import _random_forest_regressor
  from .None import _standard_scaler
  from .None import _k_neighbors_classifier
label_desc: Use image node_id 3 for calling a global function with example usage: _is_sklearn_model(sk_obj) and returns: unknown