Dropout #182
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Dropout #182
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| local state = cudnn.dropout_rng_states[dev] | ||
| errcheck('cudnnSetDropoutDescriptor', self.dropDesc[0], | ||
| cudnn.getHandle(), self.p, | ||
| state:data(), state:nElement(), torch.seed()) |
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this would reset the seed of torch RNG - this is probably not something you want to do, as it can introduce non-desirable non-determinism. Better to use torch.random() here?
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cudnn.Dropout:setp() will be broken (for it to work, cudnn.Dropout:setp() should call setDropoutDescriptor using NULL as state argument if states are initialized already). (and thanks for these bindings!) |
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There is a potential problem with several dropout layers sharing the states and running concurrently in the different streams, but its hard to make this scenario completely safe. |
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cudnn.Dropout should take about a ton less memory because it stores masks in binary format and faster as well, thanks to @ngimel for explaining this.
can someone review please?
Btw, R5 is released, it's time to make it master @soumith ?