Yanghoon Kim
Yanghoon Kim
I found that if I let CUDA_VISIBLE_DEVICES='0', which means using only one GPU, the code works. The error rises from trainer.py: `#Our model outputs do not work with DataPrallel, so...
Because they have applied Monte Carlo search with a roll-out policy. The official rnncells in TF don't provide such a function.
@tnq177 Did you just use the code provided by tensorflow? can you tell me the details of the model?( tensorflow version, stack size, layer size, sampled_loss(sample size), voca_size, etc.) Thanks
@tnq177 oh, I thought it is tensorflow github. Thanks for replying
@tnq177 can you tell me which part of the prepare_data.py should I fix to using en-fr data as detailed in Bahdanau's paper? I tried several way, but it caused an...
@tnq177 Thanks a lot!
@nptdat In fact, that doesn't solve those problems. I think the only way make fully use of the gpu is 1. data parallelism 2. allocate each gpu to each layer/some...
> I see. I think it is not too common to have data parallelism on the same machine for seq2seq models, but people have found that putting different RNN layers...
Which gpu are you using? You just run the same code provided by tutorial?
the error above happened with tensorflow 1.2 While I re-installed to 1.0, I got a similar error: ``` INFO:tensorflow:Creating ZeroBridge in mode=eval INFO:tensorflow: ZeroBridge: {} INFO:tensorflow:Starting evaluation at 2017-06-30-06:18:48 I...