Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/5596#discussion_r29059297
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala ---
@@ -0,0 +1,63 @@
+/*
+ * 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.ml.feature
+
+import org.scalatest.FunSuite
+
+import org.apache.spark.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.mllib.util.MLlibTestSparkContext
+import org.apache.spark.mllib.util.TestingUtils._
+import org.apache.spark.sql.{Row, SQLContext}
+
+class Word2VecSuite extends FunSuite with MLlibTestSparkContext {
+
+ test("Word2Vec") {
+ val sqlContext = new SQLContext(sc)
+ import sqlContext.implicits._
+
+ val sentence = "a b " * 100 + "a c " * 10
+ val numOfWords = sentence.split(" ").size
+ val doc = sc.parallelize(Seq(sentence, sentence)).map(line =>
line.split(" "))
+
+ val codes = Map(
+ "a" ->
Array(-0.2811822295188904,-0.6356269121170044,-0.3020961284637451),
+ "b" ->
Array(1.0309048891067505,-1.29472815990448,0.22276712954044342),
+ "c" ->
Array(-0.08456747233867645,0.5137411952018738,0.11731560528278351)
+ )
+
+ val expected = doc.map { sentence =>
+ Vectors.dense(sentence.map(codes.apply).reduce((word1, word2) =>
+ word1.zip(word2).map { case (v1, v2) => v1 + v2 }
+ ).map(_ / numOfWords))
+ }
+
+ val docDF = doc.zip(expected).toDF("text", "expected")
+
+ val model = new Word2Vec()
+ .setVectorSize(3)
+ .setInputCol("text")
+ .setOutputCol("result")
+ .fit(docDF)
+
+ model.transform(docDF).select("result", "expected").collect().foreach {
+ case Row(vector1: Vector, vector2: Vector) =>
+ assert(vector1 ~== vector2 absTol 1E-5, "Transformed vector is
different with expected.")
--- End diff --
Please run this test multiple times and see whether this is deterministic.
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