Welcome to join us! Please follow the readme file https://github.com/apache/incubator-singa/tree/dev for installation and a CNN example. We will add more documentation next week and prepare the release by the end of this month.
Thanks. regards, On Tue, Jul 19, 2016 at 2:02 PM, Shayan Shams <ssha...@lsu.edu> wrote: > Thats a good news that you are working on lstm and gru implementation and > im more than glad to help in developing that. I have been following your > development on bersion 1 and i really like it. Very good job. Just to be > clear in version one you will have both GRU and also Lstm im asking because > in the current version you just have the GRU > Thanks alot > And i start working on version1 asap > > Shayan Shams > > On Jul 19, 2016, at 00:58, Wang Wei <wangwei...@gmail.com> wrote: > > Yes. We will support CPU and GPU for CNN and RNN. > The v0.3 supports CPU and GPU for CNN and GRU. > We are working on v1.0 which would be much easier to use and to customize. > The GPU part of RNN (including LSTM/GRU/TANH) would be ready next week. > I am busy on the v1.0 development, and may not have time to work on LSTM > for v0.3 until the end of this month. > Sorry about that.. > > I would encourage you to try v1.0 and help us to improve it as you are > familiar with LSTM and GRU. > > regards, > Wei > > > On Tue, Jul 19, 2016 at 1:44 PM, Shayan Shams <ssha...@lsu.edu> wrote: > >> >> Hi Wei >> Thanks for reply i am using lstm on the top of cnn for some medical image >> data I do have gpu but i prefer to have both gpu and cpu code and as far as >> i know you guys have gru but not lstm implemented and another reason i have >> changed the cnn codes and im running them on cpu so it would be great if i >> can run both of them on cpu >> Shayan Shams >> >> On Jul 19, 2016, at 00:22, Wang Wei <wangwei...@gmail.com> wrote: >> >> Hi Shanyan, >> >> May I know your purpose or application of running lstm? >> We are working on RNN (LSTM/TANH/GRU) using cuDNN >> https://github.com/apache/incubator-singa/pull/203 >> >> If you have GPU, I think it would be more efficient to use cuDNN v5 for >> RNN applications. >> >> regards, >> Wei >> >> On Mon, Jul 18, 2016 at 12:53 PM, Shayan Shams <ssha...@lsu.edu> wrote: >> >>> Dear all, >>> >>> I am writing to ask for you consultation about a problem that I have >>> been faced with. I tried to use the current GRU implementation and change >>> it a little bit to create LSTM on singa, I have created the following >>> files in singe >>> >>> "lstm.cc" >>> >>> lstm section in "job.proto" >>> >>> lstm connection layer in "neuralnet.h" >>> >>> lstm layer in "neuron_layer.h" >>> >>> and also I created one function called mem to return mem_ in "layer.h" >>> >>> I have registered my layer in "driver.cc" >>> >>> I have attached all the files. >>> >>> I was able to recompile the singa but when I tried to run the char-rnn >>> example for which the conf file is there with just changing the gru layer >>> to lstm, >>> >>> it is compiled and running without any error but after some steps of >>> training the gradvec[1] is getting so big that I get nan for lost. I >>> tried different parameter and if I make the learning rate small it works >>> but it doesnt converge. >>> >>> I tried to debug it but i couldnt. >>> >>> >>> so would you mind please take a look at it and guide me in correct >>> direction, I know its a lot to ask but any help is very much appreciated. >>> >>> I sincerely appreciate your kindness and consideration. >>> >>> Yours Sincerely, >>> >>> Shayan Shams >>> >> >> >