buriburisuri / bytenet Goto Github PK

Thanks for the implementation, looks really clean and simple!

I noticed thought that the dynamic unfolding is not quite implemented. There's a max_length parameter, but it's of a fixed size, in the paper they seem to determine it dynamically and use bucketing for more efficient batching. Do you plan to implement this at some point? I might work on that, can reach out if I finish the implementation

I'm interested in monitoring validation loss during training. I tried to use sg_reuse() function as in the examples of your sugartensor repository. But it seems a little difficult to do this in Bytenet, maybe due to the concatenation (enc = enc.sg_concat(target=y_src.sg_lookup(emb=emb_y))) ?

Could you point me a way to calculation validation loss in Bytenet?

Many Thanks.

I was wondering if you plan to implement beam search for generation of translation candidates, as described here:

Alternatively I would be happy to implement this if you can offer some guidance or good references of best approach to do it.

It would be of great help if anyone suggest how to perform inference on entire NLTK dataset.

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Hi, I tried to load the pre-trained model with your code "translate.py", however, there is an error saying:
"
2018-03-27 13:20:54.342537: W tensorflow/core/framework/op_kernel.cc:1192] Not found: asset/train/model.ckpt-22512.data-00000-of-00001; No such file or directory
"
Is it possible to also upload the .data files? Thanks!