Source code for skl2onnx

# SPDX-License-Identifier: Apache-2.0

Main entry point to the converter from the *scikit-learn* to *onnx*.
__version__ = "1.10.2"
__author__ = "Microsoft"
__producer__ = "skl2onnx"
__producer_version__ = __version__
__domain__ = "ai.onnx"
__model_version__ = 0
__max_supported_opset__ = 15  # Converters are tested up to this version.

from .convert import convert_sklearn, to_onnx, wrap_as_onnx_mixin  # noqa
from ._supported_operators import (  # noqa
    update_registered_converter, get_model_alias
from ._parse import update_registered_parser  # noqa
from .proto import get_latest_tested_opset_version  # noqa

[docs]def supported_converters(from_sklearn=False): """ Returns the list of supported converters. To find the converter associated to a specific model, the library gets the name of the model class, adds ``'Sklearn'`` as a prefix and retrieves the associated converter if available. :param from_sklearn: every supported model is mapped to converter by a name prefixed with ``'Sklearn'``, the prefix is removed if this parameter is False but the function only returns converters whose name is prefixed by ``'Sklearn'`` :return: list of supported models as string """ from .common._registration import _converter_pool # noqa # The two following lines populates the list of supported converters. from . import shape_calculators # noqa from . import operator_converters # noqa names = sorted(_converter_pool.keys()) if from_sklearn: return [_[7:] for _ in names if _.startswith('Sklearn')] return list(names)