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
      )
  
file_path: coremltools/coremltools/converters/sklearn/_converter_internal.py
imports: from ..._deps import _HAS_SKLEARN
  from ...models import _feature_management
  from ...models import datatypes
  from ...models.feature_vectorizer import create_feature_vectorizer
  from ...models.pipeline import Pipeline, PipelineClassifier, PipelineRegressor
  from collections import namedtuple
  from .None import _SVC, _SVR, _decision_tree_classifier, _decision_tree_regressor, _dict_vectorizer, _gradient_boosting_classifier, _gradient_boosting_regressor, _imputer, _k_neighbors_classifier, _linear_regression, _LinearSVC, _LinearSVR, _logistic_regression, _normalizer, _NuSVC, _NuSVR, _one_hot_encoder, _random_forest_classifier, _random_forest_regressor, _standard_scaler, _ridge_regression
label_desc: Use image node_id 3 for calling a global function with example usage: _is_sklearn_model(sk_obj) and returns: unknown