lindong28 commented on code in PR #90: URL: https://github.com/apache/flink-ml/pull/90#discussion_r865962589
########## flink-ml-lib/src/main/java/org/apache/flink/ml/common/optimizer/Optimizer.java: ########## @@ -0,0 +1,47 @@ +/* + * 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. + */ + +package org.apache.flink.ml.common.optimizer; + +import org.apache.flink.annotation.Internal; +import org.apache.flink.ml.common.feature.LabeledPointWithWeight; +import org.apache.flink.ml.common.lossfunc.LossFunc; +import org.apache.flink.ml.linalg.DenseVector; +import org.apache.flink.streaming.api.datastream.DataStream; + +/** + * An optimizer is a function to modify the weight of a machine learning model, which aims to find + * the optimal parameter configuration for a machine learning model. Examples of optimizers could be + * stochastic gradient descent (SGD), L-BFGS, etc. + */ +@Internal +public interface Optimizer { + /** + * Optimize the given loss function using the init model and the training data. + * + * @param bcInitModel The broadcast init model. Note that each task contains one DenseVector as + * the model data and the model data on each task are exactly the same. + * @param trainData The training data. + * @param lossFunc The loss function to optimize. + * @return The fitted model. Note that the parallelism of the returned stream is one. + */ + DataStream<DenseVector> optimize( + DataStream<DenseVector> bcInitModel, Review Comment: `initial` seems unnecessary because even if we remove this word, we can still correctly explain the semantics of this Java doc more concisely. For example, the Java doc of this method could be `Optimizes the given loss function using the given model data and the training data`. I am also OK to keep the existing name `initialModelData`. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
