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- adding runtime ``GPU-health'' check
- modifying Dropout, adding MaxNorm
- extending log-prints in lattice decoding (can be used for confidence monitoring)



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trunk,nnet1 : changing CuMatrix -> CuMatrixBase and CuVector -> CuVectorBase in interfaces, where applicable. Note the 'Base' classes mean that the dimensions are fixed and object has pre-allocated data.



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trunk,nnet: committing latest nnet code, preparation for CNNs, a binary tool for initialization (will be used in examples later)



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- new per-frame randomizers (future plan to remove Cache, and use lightweight randomizers instead, already in rbm-train-cd1-frmshuff and nnet-train-frmshuff)
- nnet training tools added verbose level3 for analyzing graidents, or feedforward data
- cross entropy loss now has progressive reporting 



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sandbox/dan2: merge various changes from trunk, plus some changes to enable efficient GPU-based training after 'mix-up'.

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trunk,nnet1: warning! changes to Component/Nnet interaface to be closer to Dan's, you may need to fix your extensions to nnet1 code, main changes are:
- nnet files now have optional begin/end tokens <Nnet></Nnet> (backward compatibility)
- in the Nnet API, "*Layer" was replaced by "*Component", which better corresponds to code
- removed *Nnet pointer from Component and constructors, it was unused
- addded Component::Copy() method, simplified nnet consistency checks Nnet::Check()
- fixed "Copyright" notices



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Update COPYING notice to further clarify our conventions regarding copyright and multiple authors; update Apache headers to point to COPYING notice.

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- NN-training hyper-parameters now in classes NnetTrainOptions RbmTrainOptions
- removing nnet-trim-n-last-transforms (functionality now in nnet-copy --remove-last-layers)



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- updating RBM training
- plus some minor updates



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fixing the GPU build process which now uses multiple CUDA compute capabilities



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