code: def convert(model, features, target):
      """Convert a Support Vector Regressor (SVR) model to the protobuf spec.
      Parameters
      ----------
      model: SVR
          A trained SVR encoder model.
  
      feature_names: [str]
          Name of the input columns.
  
      target: str
          Name of the output column.
  
      Returns
      -------
      model_spec: An object of type Model_pb.
          Protobuf representation of the model
      """
      spec = _generate_base_svm_regression_spec(model)
      spec = set_regressor_interface_params(spec, features, target)
      return _MLModel(spec)
  
file_path: turicreate/src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_SVR.py
imports: from ...proto import Model_pb2
  from ...models._interface_management import set_regressor_interface_params
  from ...None import SPECIFICATION_VERSION
  from ..._deps import _HAS_SKLEARN
  from ...models import MLModel
  from ._svm_common import _set_kernel
label_desc: Use image node_id 2 for calling a global function with example usage: convert(model, features, target) and returns: _MLModel