piiswrong commented on a change in pull request #9366: Refactor dropout
operator to use ParallelRandom generator and also react deterministically when
seeding
URL: https://github.com/apache/incubator-mxnet/pull/9366#discussion_r161605173
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File path: src/operator/nn/dropout-inl.h
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@@ -94,47 +72,124 @@ struct DropoutParam : public
dmlc::Parameter<DropoutParam> {
template<typename xpu, typename DType>
class DropoutOp : public Operator {
+#if defined(USE_MKL) && defined(_OPENMP)
+ static void BernoulliGenerate(common::random::RandGenerator<cpu, DType> gen,
+ int n, double p, int* r) {
+ typename RandGenerator<xpu, DType>::Impl genImpl(&gen, 1);
+ const int seed = 17 + genImpl.rand() % 4096; //
NOLINT(runtime/threadsafe_fn)
+ const int nthr = engine::OpenMP::Get()->GetRecommendedOMPThreadCount();
+#pragma omp parallel num_threads(nthr)
+ {
+ const int ithr = omp_get_thread_num();
+ const int avg_amount = (n + nthr - 1) / nthr;
+ const int my_offset = ithr * avg_amount;
+ const int my_amount = std::min(my_offset + avg_amount, n) - my_offset;
+ if (my_amount > 0) {
+ VSLStreamStatePtr stream;
+ vslNewStream(&stream, VSL_BRNG_MCG31, seed + my_offset);
+ vslSkipAheadStream(stream, my_offset);
Review comment:
can we move this to Resource::ParallelRandom so that all rngs are fast when
using mkl?
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