From b51a4cdff3a7e640a8a66f7a9c17021f3056fd34 Mon Sep 17 00:00:00 2001 From: Liang-Chi Hsieh Date: Mon, 14 Dec 2015 09:59:42 -0800 Subject: [SPARK-12016] [MLLIB] [PYSPARK] Wrap Word2VecModel when loading it in pyspark JIRA: https://issues.apache.org/jira/browse/SPARK-12016 We should not directly use Word2VecModel in pyspark. We need to wrap it in a Word2VecModelWrapper when loading it in pyspark. Author: Liang-Chi Hsieh Closes #10100 from viirya/fix-load-py-wordvecmodel. --- .../spark/mllib/api/python/PythonMLLibAPI.scala | 33 ------------ .../mllib/api/python/Word2VecModelWrapper.scala | 62 ++++++++++++++++++++++ 2 files changed, 62 insertions(+), 33 deletions(-) create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/api/python/Word2VecModelWrapper.scala (limited to 'mllib') diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala index 8d546e3d60..29160a10e1 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala @@ -680,39 +680,6 @@ private[python] class PythonMLLibAPI extends Serializable { } } - private[python] class Word2VecModelWrapper(model: Word2VecModel) { - def transform(word: String): Vector = { - model.transform(word) - } - - /** - * Transforms an RDD of words to its vector representation - * @param rdd an RDD of words - * @return an RDD of vector representations of words - */ - def transform(rdd: JavaRDD[String]): JavaRDD[Vector] = { - rdd.rdd.map(model.transform) - } - - def findSynonyms(word: String, num: Int): JList[Object] = { - val vec = transform(word) - findSynonyms(vec, num) - } - - def findSynonyms(vector: Vector, num: Int): JList[Object] = { - val result = model.findSynonyms(vector, num) - val similarity = Vectors.dense(result.map(_._2)) - val words = result.map(_._1) - List(words, similarity).map(_.asInstanceOf[Object]).asJava - } - - def getVectors: JMap[String, JList[Float]] = { - model.getVectors.map({case (k, v) => (k, v.toList.asJava)}).asJava - } - - def save(sc: SparkContext, path: String): Unit = model.save(sc, path) - } - /** * Java stub for Python mllib DecisionTree.train(). * This stub returns a handle to the Java object instead of the content of the Java object. diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/Word2VecModelWrapper.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/Word2VecModelWrapper.scala new file mode 100644 index 0000000000..0f55980481 --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/Word2VecModelWrapper.scala @@ -0,0 +1,62 @@ +/* + * 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.spark.mllib.api.python + +import java.util.{ArrayList => JArrayList, List => JList, Map => JMap} +import scala.collection.JavaConverters._ + +import org.apache.spark.SparkContext +import org.apache.spark.api.java.JavaRDD +import org.apache.spark.mllib.feature.Word2VecModel +import org.apache.spark.mllib.linalg.{Vector, Vectors} + +/** + * Wrapper around Word2VecModel to provide helper methods in Python + */ +private[python] class Word2VecModelWrapper(model: Word2VecModel) { + def transform(word: String): Vector = { + model.transform(word) + } + + /** + * Transforms an RDD of words to its vector representation + * @param rdd an RDD of words + * @return an RDD of vector representations of words + */ + def transform(rdd: JavaRDD[String]): JavaRDD[Vector] = { + rdd.rdd.map(model.transform) + } + + def findSynonyms(word: String, num: Int): JList[Object] = { + val vec = transform(word) + findSynonyms(vec, num) + } + + def findSynonyms(vector: Vector, num: Int): JList[Object] = { + val result = model.findSynonyms(vector, num) + val similarity = Vectors.dense(result.map(_._2)) + val words = result.map(_._1) + List(words, similarity).map(_.asInstanceOf[Object]).asJava + } + + def getVectors: JMap[String, JList[Float]] = { + model.getVectors.map({case (k, v) => (k, v.toList.asJava)}).asJava + } + + def save(sc: SparkContext, path: String): Unit = model.save(sc, path) +} -- cgit v1.2.3