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[SPARK-19110][ML][MLLIB]:DistributedLDAModel returns different logPrior for original and loaded model #16491

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[SPARK-19110][ML][MLLIB]:DistributedLDAModel returns different logPrior for original and loaded model #16491

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31d9bce
fix the bug of logPrior
wangmiao1981 Jan 6, 2017
a29d078
improve test
wangmiao1981 Jan 6, 2017
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4 changes: 2 additions & 2 deletions mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -745,12 +745,12 @@ class DistributedLDAModel private[clustering] (
val N_wk = vertex._2
val smoothed_N_wk: TopicCounts = N_wk + (eta - 1.0)
val phi_wk: TopicCounts = smoothed_N_wk :/ smoothed_N_k
(eta - 1.0) * sum(phi_wk.map(math.log))
sumPrior + (eta - 1.0) * sum(phi_wk.map(math.log))
} else {
val N_kj = vertex._2
val smoothed_N_kj: TopicCounts = N_kj + (alpha - 1.0)
val theta_kj: TopicCounts = normalize(smoothed_N_kj, 1.0)
(alpha - 1.0) * sum(theta_kj.map(math.log))
sumPrior + (alpha - 1.0) * sum(theta_kj.map(math.log))
}
}
graph.vertices.aggregate(0.0)(seqOp, _ + _)
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8 changes: 8 additions & 0 deletions mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
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Expand Up @@ -260,6 +260,14 @@ class LDASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead
Vectors.dense(model2.topicsMatrix.toArray) absTol 1e-6)
assert(Vectors.dense(model.getDocConcentration) ~==
Vectors.dense(model2.getDocConcentration) absTol 1e-6)
val logPrior = model.asInstanceOf[DistributedLDAModel].logPrior
val logPrior2 = model2.asInstanceOf[DistributedLDAModel].logPrior
val trainingLogLikelihood =
model.asInstanceOf[DistributedLDAModel].trainingLogLikelihood
val trainingLogLikelihood2 =
model2.asInstanceOf[DistributedLDAModel].trainingLogLikelihood
assert(logPrior ~== logPrior2 absTol 1e-6)
assert(trainingLogLikelihood ~== trainingLogLikelihood2 absTol 1e-6)
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@felixcheung felixcheung Jan 6, 2017

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should we check trainingLogLikelihood and logPrior are not changing for LocalLDAModel?

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@wangmiao1981 wangmiao1981 Jan 6, 2017

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logLikelihood and logPrior are only for distributed model.

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@felixcheung felixcheung Jan 6, 2017

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right - I mean that they are not persisted & loaded into an unexpected but valid value (!= Double.NaN)

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@wangmiao1981 wangmiao1981 Jan 7, 2017

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LocalLDAModel doesn't extend DistributedLDAModel and vice versa. I am not clear how to check trainingLogLikelihood and logPrior in LocalLDAModel.

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@felixcheung felixcheung Jan 7, 2017

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Ok, I guess I remember this wrong because of the other PR.

}
val lda = new LDA()
testEstimatorAndModelReadWrite(lda, dataset,
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