First CPU implementation of HashedNets compression algorithm for DNNs #220
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This is just changing the 'weights' vector to a compressed 'weightBucket' vector of size 'BUCKET_SIZE' per layer. Will have restructure other parts of the code for this to make algorithmic sense.
| fNet.setErrorFunction (DNN::ModeErrorFunction::CROSSENTROPY); | ||
| // net.setErrorFunction (ModeErrorFunction::SUMOFSQUARES); | ||
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| const int BUCKET_SIZE = 8; |
Contributor
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Hi Aditya,
Why bucket size is constant value here?
Author
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Hi Omar, that's because this is the checkGradients () function. As you can see above at lines 1100 - 03, this is a predefined Neural Net created just to see if the algorithm calculates gradients properly. This is independent of the actual training.
Member
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Could you rebase this PR and squash the duplicate commits? |
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Can one of the admins verify this patch? |
Author
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This patch needs some work. I'm closing the pull request for now. Will issue a new one after resolving the issues. |
This was referenced May 8, 2018
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This is an implementation of HashedNets (https://arxiv.org/pdf/1504.04788.pdf) in ROOT.
It is built over the existing implementation of DNNs in TMVA and supports multithreading.