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#
# 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.
#
"""
DataFrame-based machine learning APIs to let users quickly assemble and configure practical
machine learning pipelines.
"""
from pyspark.ml.base import (
Estimator,
Model,
Predictor,
PredictionModel,
Transformer,
UnaryTransformer,
)
from pyspark.ml.pipeline import Pipeline, PipelineModel
from pyspark.ml import (
classification,
clustering,
evaluation,
feature,
fpm,
image,
recommendation,
regression,
stat,
tuning,
util,
linalg,
param,
)
from pyspark.ml.torch.distributor import TorchDistributor
__all__ = [
"Transformer",
"UnaryTransformer",
"Estimator",
"Model",
"Predictor",
"PredictionModel",
"Pipeline",
"PipelineModel",
"classification",
"clustering",
"evaluation",
"feature",
"fpm",
"image",
"recommendation",
"regression",
"stat",
"tuning",
"util",
"linalg",
"param",
"TorchDistributor",
]