Github user feynmanliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/7760#discussion_r35836602
--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala ---
@@ -281,6 +282,67 @@ class LDASuite extends SparkFunSuite with
MLlibTestSparkContext {
assert(ldaModel.logPerplexity(docs) ~== -3.690D relTol 1E-3D)
}
+ test("LocalLDAModel predict") {
+ val k = 2
+ val vocabSize = 6
+ val alpha = 0.01
+ val eta = 0.01
+ val gammaShape = 100
+ // obtained from LDA model trained in gensim, see below
+ val topics = new DenseMatrix(numRows = vocabSize, numCols = k, values
= Array(
+ 1.86738052, 1.94056535, 1.89981687, 0.0833265, 0.07405918,
0.07940597,
+ 0.15081551, 0.08637973, 0.12428538, 1.9474897, 1.94615165,
1.95204124))
+
+ def toydata: Array[(Long, Vector)] = Array(
+ Vectors.sparse(6, Array(0, 1), Array(1, 1)),
+ Vectors.sparse(6, Array(1, 2), Array(1, 1)),
+ Vectors.sparse(6, Array(0, 2), Array(1, 1)),
+ Vectors.sparse(6, Array(3, 4), Array(1, 1)),
+ Vectors.sparse(6, Array(3, 5), Array(1, 1)),
+ Vectors.sparse(6, Array(4, 5), Array(1, 1))
+ ).zipWithIndex.map { case (wordCounts, docId) => (docId.toLong,
wordCounts) }
+ val docs = sc.parallelize(toydata)
+
--- End diff --
OK
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