code: def _get_converter_module(sk_obj):
      """
      Returns the module holding the conversion functions for a
      particular model).
      """
      try:
          cv_idx = _converter_lookup[sk_obj.__class__]
      except KeyError:
          raise ValueError(
              "Transformer '%s' not supported; supported transformers are %s."
              % (
                  repr(sk_obj),
                  ",".join(k.__name__ for k in _converter_module_list),
              )
          )
  
      return _converter_module_list[cv_idx]
  
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 2 for calling a global function with example usage: _get_converter_module(sk_obj) and returns: _converter_module_list