Github user Myasuka commented on the pull request:
https://github.com/apache/spark/pull/1290#issuecomment-121966507
hi, @avulanov , I have forked your repository about ann-benchmark
https://github.com/avulanov/ann-benchmark/blob/master/spark/spark.scala . I
feel a little confused about the mini-batch training, it seems that `batchSize`
in code `val trainer = new FeedForwardTrainer(topology, 780,
10).setBatchSize(batchSize)` means the size of sub-block matrix you group the
original input matrix into, and `setMiniBatchFraction(1.0)` in
`trainer.SGDOptimizer.setNumIterations(numIterations).setMiniBatchFraction(1.0).setStepSize(0.03)`
means you actually use full-batch gradient descent not the mini-batch gradient
descent method. Does it performs well on mnist8m data? Maybe you can share the
training parameters in detail, such as layer units, mini-batch size, stepsize
and so on.
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