Fixes doc-topic persistence if no prior are given on either the model…

… or the documents (by doing the usual thing of taking a randomized model to start)

core/src/main/java/org/apache/mahout/clustering/lda/cvb/PriorTrainingReducer.java

@@ -25,6 +25,7 @@
 import org.apache.hadoop.mapred.Reporter;
 import org.apache.hadoop.mapred.lib.MultipleOutputs;
 import org.apache.hadoop.mapreduce.Counter;
+import org.apache.mahout.common.RandomUtils;
 import org.apache.mahout.math.DenseMatrix;
 import org.apache.mahout.math.DenseVector;
 import org.apache.mahout.math.Matrix;
@@ -96,8 +97,9 @@ public void configure(JobConf conf) {
         log.info("No model files found, starting with uniform p(term|topic) prior");
         Matrix m = new DenseMatrix(numTopics, numTerms);
         m.assign(1.0 / numTerms);
-        readModel = new TopicModel(m, new DenseVector(numTopics).assign(1.0), eta, alpha, null,
-            numTrainThreads, modelWeight);
+        readModel = new TopicModel(numTopics, numTerms, eta, alpha,
+                                   RandomUtils.getRandom(c.getRandomSeed()), null,
+                                   numTrainThreads, modelWeight);
       }
 
       log.info("Initializing write model");