Enable test for stratified sampling for multi-class after load-balancing.
again
Merge branch 'master' into arno-deeplearning2
Merge branch 'master' into arno-deeplearning2
Merge branch 'master' into arno-deeplearning2
Added asyncExec call to MRTask2 intended to be used for non-blocking task invocation (either using continuation/callback style or do not wait for the results at all).

The functionality is basically the same as of dfork call, except the invoked task will run at the same priority level as the calling thread or min_priority if called outside of FJ framework (whereas dfork automatically increases the priority level to avoid deadlock).

Adapted GLM2 (and Parse2) to use this call instead of dfork so that every GLM2 iteration runs at the same priority level (GLM2 launches iterations from FJ thread but uses continuation style callback and not blocking, so there is no risk of deadlock).
Merge remote-tracking branch 'origin/master'
Remove hard-to-do check (can fail sometimes).
Convert everything to single-precision math in Deep Learning, optimized fprop Mat-Vec now even faster.
Modify NeuralNet to do everything in single precision.
Match single prevision behavior of DeepLearning and NeuralNet.
Increase tolerance for JUnit tests that compare against reference implementation (since we changed to single precision, and reference implementation uses double/float mix).
Add more epochs for Spirals test to finish with single precision.
Code cleanup.
Significantly speed up ADADELTA by using approximate sqrt and 1./sqrt functions.
Cosmetics.
Add fast approximations for sqrt and 1./sqrt and exp.
Speedup ADADELTA by using fast sqrt approximation and combined arrays to reduce cache misses.
Add fast approximation for log(x) for x>1.
Starting point for partial sums for bprop.