def convert(model, input_features, output_features):
    """Convert a _imputer model to the protobuf spec.

    Parameters
    ----------
    model: Imputer
        A trained Imputer model.

    input_features: str
        Name of the input column.

    output_features: str
        Name of the output column.

    Returns
    -------
    model_spec: An object of type Model_pb.
        Protobuf representation of the model
    """
    if not (_HAS_SKLEARN):
        raise RuntimeError(
            "scikit-learn not found. scikit-learn conversion API is disabled."
        )

    # Test the scikit-learn model
    _sklearn_util.check_expected_type(model, StandardScaler)
    _sklearn_util.check_fitted(model, lambda m: hasattr(m, "mean_"))
    _sklearn_util.check_fitted(model, lambda m: hasattr(m, "scale_"))

    # Set the interface params.
    spec = proto.Model_pb2.Model()
    spec.specificationVersion = SPECIFICATION_VERSION
    spec = _set_transform_interface_params(spec, input_features, output_features)

    # Set the parameters
    tr_spec = spec.scaler
    for x in model.mean_:
        tr_spec.shiftValue.append(-x)

    for x in model.scale_:
        tr_spec.scaleValue.append(1.0 / x)

    return _MLModel(spec)
Convert a _imputer model to the protobuf spec.

    Parameters
    ----------
    model: Imputer
        A trained Imputer model.

    input_features: str
        Name of the input column.

    output_features: str
        Name of the output column.

    Returns
    -------
    model_spec: An object of type Model_pb.
        Protobuf representation of the model
    
coremltools/converters/sklearn/_standard_scaler.py