49 lines
1.9 KiB
Python
49 lines
1.9 KiB
Python
|
#
|
||
|
|
# Licensed to the Apache Software Foundation (ASF) under one
|
||
|
|
# or more contributor license agreements. See the NOTICE file
|
||
|
|
# distributed with this work for additional information
|
||
|
|
# regarding copyright ownership. The ASF licenses this file
|
||
|
|
# to you under the Apache License, Version 2.0 (the
|
||
|
|
# "License"); you may not use this file except in compliance
|
||
|
|
# with the License. You may obtain a copy of the License at
|
||
|
|
#
|
||
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
||
|
|
#
|
||
|
|
# Unless required by applicable law or agreed to in writing,
|
||
|
|
# software distributed under the License is distributed on an
|
||
|
|
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
|
||
|
|
# KIND, either express or implied. See the License for the
|
||
|
|
# specific language governing permissions and limitations
|
||
|
|
# under the License.
|
||
|
|
|
||
|
|
import abc
|
||
|
|
from typing import Any, Optional
|
||
|
|
from pyspark.ml._typing import P, T, JM, ParamMap
|
||
|
|
|
||
|
|
from pyspark.ml import Estimator, Predictor, PredictionModel, Transformer, Model
|
||
|
|
from pyspark.ml.base import _PredictorParams
|
||
|
|
from pyspark.ml.param import Param, Params
|
||
|
|
|
||
|
|
class JavaWrapper:
|
||
|
|
def __init__(self, java_obj: Optional[Any] = ...) -> None: ...
|
||
|
|
def __del__(self) -> None: ...
|
||
|
|
|
||
|
|
class JavaParams(JavaWrapper, Params, metaclass=abc.ABCMeta):
|
||
|
|
def copy(self: P, extra: Optional[ParamMap] = ...) -> P: ...
|
||
|
|
def clear(self, param: Param) -> None: ...
|
||
|
|
|
||
|
|
class JavaEstimator(JavaParams, Estimator[JM], metaclass=abc.ABCMeta): ...
|
||
|
|
class JavaTransformer(JavaParams, Transformer, metaclass=abc.ABCMeta): ...
|
||
|
|
|
||
|
|
class JavaModel(JavaTransformer, Model, metaclass=abc.ABCMeta):
|
||
|
|
def __init__(self, java_model: Optional[Any] = ...) -> None: ...
|
||
|
|
|
||
|
|
class JavaPredictor(
|
||
|
|
Predictor[JM], JavaEstimator, _PredictorParams, metaclass=abc.ABCMeta
|
||
|
|
): ...
|
||
|
|
|
||
|
|
class JavaPredictionModel(PredictionModel[T], JavaModel, _PredictorParams):
|
||
|
|
@property
|
||
|
|
def numFeatures(self) -> int: ...
|
||
|
|
def predict(self, value: T) -> float: ...
|