Hi everyone, following up on this topic, how about performing a shared evaluation of the tools we mentioned so far? I'd address this by deciding upon a "shared MT task" on a well known and not so big dataset and then getting an evaluation run for each of those toolkits. The evaluation task would require gettin: - an accuracy metric value (BLEU? I know it's questionable, otherwise what else?) - a prediction speed measure (e.g. translations per second), reporting also the hardware used - a training speed measure (e.g. seconds/minutes/hours taken to train the model)
What do others think? Regards, Tommaso On Wed, 21 Oct 2020 at 15:57, Tommaso Teofili <tommaso.teof...@gmail.com> wrote: > hi Michael, > > nice to hear from you too on the dev@ list! We're looking forward to see > you involved :) > If I understood Thamme's proposal correctly, the paper is just a way to > write down our own evaluation of current approaches to NMT; that would help > us decide on our own way to pursue MT. > At this stage I am not sure what we'll end up doing, it'd be nice not to > just be a wrapper for one of those existing NMT tools, but let's see. > > Regards, > Tommaso > > > On Tue, 20 Oct 2020 at 15:37, Michael Wall <mjw...@apache.org> wrote: > >> Hi, >> >> Been watching Joshua since it was incubating. Finally may have some >> free time and am would like to get involved. >> >> The NMT stuff looks interesting. I don't have an overleaf account, so >> maybe my next question is answered there. What is the end result of >> the paper? Will you be choosing a framework to add to Joshua. And if >> so, what will make it different than just using said framework on it's >> own? >> >> Thanks >> >> Mike >> >> On Tue, Oct 20, 2020 at 5:34 AM Tommaso Teofili >> <tommaso.teof...@gmail.com> wrote: >> > >> > I've also added M2M-100 from FB-AI [1]. >> > >> > Regarding desiderata, here's an unsorted list of first things that come >> to >> > my mind: >> > - runs also on jvm >> > - low resource requirements (e.g. for training) >> > - can leverage existing / pretrained models >> > - word and phrase translation capabilities >> > - good effectiveness :) >> > >> > Regards, >> > Tommaso >> > >> > [1] : >> > >> https://about.fb.com/news/2020/10/first-multilingual-machine-translation-model/ >> > >> > On Mon, 19 Oct 2020 at 14:09, Tommaso Teofili < >> tommaso.teof...@gmail.com> >> > wrote: >> > >> > > Thanks a lot Thamme, I sticked to AL-2 compatible ones, but I agree >> we can >> > > surely have a look at others having different licensing too. >> > > In the meantime I've added all of your suggestions to the paper (with >> > > related reference when available). >> > > We should decide what our desiderata are and establish a first set of >> eval >> > > benchmark just to understand what can work for us, at least >> initially, then >> > > we can have a more thorough evaluation with a small number of >> "candidates". >> > > >> > > Regards, >> > > Tommaso >> > > >> > > On Mon, 19 Oct 2020 at 09:05, Thamme Gowda <tgow...@gmail.com> wrote: >> > > >> > >> Tomaso, >> > >> >> > >> Awesome! Thanks for the links. >> > >> I will be happy to join, (But I wont be able to contribute to the >> actual >> > >> paper untill Oct 24). >> > >> >> > >> I suggest we should consider popular NMT toolkits for the survey >> > >> regardless >> > >> of their compatibility with AL-2. >> > >> We should see all the tricks and features, and know if we are >> missing out >> > >> on any useful features after enforcing the AL-2 filter (and create >> issues >> > >> for adding those features). >> > >> >> > >> here are some more NMT toolkits to be included in the survey. >> > >> - Fairseq https://github.com/pytorch/fairseq >> > >> - Tensor2tensor https://github.com/tensorflow/tensor2tensor/ >> > >> - Nematus https://github.com/EdinburghNLP/nematus >> > >> - xNMT https://github.com/neulab/xnmt >> > >> - XLM https://github.com/facebookresearch/XLM/ >> > >> |-> MASS https://github.com/microsoft/MASS/ --> >> > >> https://github.com/thammegowda/unmass (took that and made it >> easier to >> > >> install and use) >> > >> >> > >> Some old stuff which we are defnitely not going to use but worth >> > >> mentioning >> > >> in the survey (for the sake of completion) >> > >> - https://github.com/google/seq2seq >> > >> - https://github.com/tensorflow/nmt >> > >> - https://github.com/isi-nlp/Zoph_RNN >> > >> >> > >> >> > >> >> > >> Cheers, >> > >> TG >> > >> >> > >> >> > >> ಭಾನು, ಅಕ್ಟೋ 18, 2020 ರಂದು 11:17 ಅಪರಾಹ್ನ ಸಮಯಕ್ಕೆ ರಂದು Tommaso Teofili >> < >> > >> tommaso.teof...@gmail.com> ಅವರು ಬರೆದಿದ್ದಾರೆ: >> > >> >> > >> > Following up on the report topic, I've created an overleaf doc for >> > >> everyone >> > >> > who's interested in working on this [1]. >> > >> > >> > >> > First set of (AL-2 compatible) NMT toolkits I've found: >> > >> > - Joey NMT [2] >> > >> > - OpenNMT [3] >> > >> > - MarianNMT [4] >> > >> > - Sockeye [5] >> > >> > - and of course RTG already shared by Thamme [6] >> > >> > >> > >> > Regards, >> > >> > Tommaso >> > >> > >> > >> > [1] : https://www.overleaf.com/8617554857qkvtqtpcxxmw >> > >> > [2] : https://github.com/joeynmt/joeynmt >> > >> > [3] : https://github.com/OpenNMT >> > >> > [4] : https://github.com/marian-nmt/marian >> > >> > [5] : https://github.com/awslabs/sockeye >> > >> > [6] : https://github.com/isi-nlp/rtg-xt >> > >> > >> > >> > On Wed, 14 Oct 2020 at 11:06, Tommaso Teofili < >> > >> tommaso.teof...@gmail.com> >> > >> > wrote: >> > >> > >> > >> > > very good idea Thamme! >> > >> > > I'd be up for writing such a short survey paper as a result of >> our >> > >> > > analysis. >> > >> > > >> > >> > > Regards, >> > >> > > Tommaso >> > >> > > >> > >> > > >> > >> > > On Wed, 14 Oct 2020 at 05:23, Thamme Gowda <tgow...@gmail.com> >> wrote: >> > >> > > >> > >> > >> Tomasso and others, >> > >> > >> >> > >> > >> > I think we may now go into a research phase to understand what >> > >> > existing >> > >> > >> toolkit we can more easily integrate with. >> > >> > >> Agreed. >> > >> > >> if we can write a (short) report that compares various NMT >> toolkits >> > >> of >> > >> > >> 2020, it would be useful for us to make this decision as well >> as to >> > >> the >> > >> > >> NMT >> > >> > >> community. >> > >> > >> Something like a survey paper on NMT research but focus on >> toolkits >> > >> and >> > >> > >> software engineering part. >> > >> > >> >> > >> > >> >> > >> > >> >> > >> > >> ಶುಕ್ರ, ಅಕ್ಟೋ 9, 2020 ರಂದು 11:39 ಅಪರಾಹ್ನ ಸಮಯಕ್ಕೆ ರಂದು Tommaso >> Teofili >> > >> < >> > >> > >> tommaso.teof...@gmail.com> ಅವರು ಬರೆದಿದ್ದಾರೆ: >> > >> > >> >> > >> > >> > Thamme, Jeff, >> > >> > >> > >> > >> > >> > your contributions will be very important for the project and >> the >> > >> > >> > community, especially given your NLP background, thanks for >> your >> > >> > >> support! >> > >> > >> > >> > >> > >> > I agree moving towards NMT is the best thing to do at this >> point >> > >> for >> > >> > >> > Joshua. >> > >> > >> > >> > >> > >> > Thamme, thanks for your suggestions! >> > >> > >> > I think we may now go into a research phase to understand what >> > >> > existing >> > >> > >> > toolkit we can more easily integrate with. >> > >> > >> > Of course if you like to integrate your own toolkit then >> that'd be >> > >> > even >> > >> > >> > more interesting to see how it compares to others. >> > >> > >> > >> > >> > >> > If that means moving to Python I think it's not a problem; we >> can >> > >> > still >> > >> > >> > work on Java bindings to ship a new Joshua Decoder >> implementation. >> > >> > >> > >> > >> > >> > The pretrained models topic is imho something we will have to >> > >> embrace >> > >> > at >> > >> > >> > some point, so that others can: >> > >> > >> > a) just download new LPs >> > >> > >> > b) eventually fine tune with their own data >> > >> > >> > >> > >> > >> > I am looking forward to start this new phase of research on >> Joshua. >> > >> > >> > >> > >> > >> > Regards, >> > >> > >> > Tommaso >> > >> > >> > >> > >> > >> > On Tue, 6 Oct 2020 at 18:30, Jeff Zemerick < >> jzemer...@apache.org> >> > >> > >> wrote: >> > >> > >> > >> > >> > >> > > I haven't contributed to this point but I would like to see >> > >> Apache >> > >> > >> Joshua >> > >> > >> > > remain an active project so I am volunteering to help. I >> may not >> > >> be >> > >> > a >> > >> > >> lot >> > >> > >> > > of help with code for a bit but I will help out with >> > >> documentation, >> > >> > >> > > releases, etc. >> > >> > >> > > >> > >> > >> > > I do agree that NMT is the best path forward but I will >> leave the >> > >> > >> choice >> > >> > >> > of >> > >> > >> > > integrating an existing library into Joshua versus a new NMT >> > >> > >> > implementation >> > >> > >> > > in Joshua to those more familiar with the code and what they >> > >> think >> > >> > is >> > >> > >> > best >> > >> > >> > > for the project. >> > >> > >> > > >> > >> > >> > > Jeff >> > >> > >> > > >> > >> > >> > > >> > >> > >> > > On Tue, Oct 6, 2020 at 2:28 AM Thamme Gowda < >> tgow...@gmail.com> >> > >> > >> wrote: >> > >> > >> > > >> > >> > >> > > > Hi Tomasso, and others >> > >> > >> > > > >> > >> > >> > > > *1. I support the addition of neural MT decoder. * >> > >> > >> > > > The world has moved on, and NMT is clearly the way to go >> > >> forward. >> > >> > >> > > > If you dont believe my words, read what Matt Post himself >> said >> > >> [1] >> > >> > >> > three >> > >> > >> > > > years ago! >> > >> > >> > > > >> > >> > >> > > > I have spent the past three years focusing on NMT as >> part of >> > >> my >> > >> > job >> > >> > >> > and >> > >> > >> > > > Ph.D -- I'd be glad to contribute in that direction. >> > >> > >> > > > There are many NMT toolkits out there today. (Fairseq, >> sockeye, >> > >> > >> > > > tensor2tensor, ....) >> > >> > >> > > > >> > >> > >> > > > The right thing to do, IMHO, is simply merge one of the >> NMT >> > >> > toolkits >> > >> > >> > with >> > >> > >> > > > Joshua project. We can do that as long as it's Apache >> License >> > >> > >> right? >> > >> > >> > > > We will now have to move towards python land as most >> toolkits >> > >> are >> > >> > in >> > >> > >> > > > python. On the positive side, we will be losing the >> ancient >> > >> perl >> > >> > >> > scripts >> > >> > >> > > > that many are not fan of. >> > >> > >> > > > >> > >> > >> > > > I have been working on my own NMT toolkit for my work and >> > >> research >> > >> > >> -- >> > >> > >> > > RTG >> > >> > >> > > > https://isi-nlp.github.io/rtg/#conf >> > >> > >> > > > I had worked on Joshua in the past, mainly, I improved >> the code >> > >> > >> quality >> > >> > >> > > > [2]. So you can tell my new code'd be upto Apache's >> standards >> > >> ;) >> > >> > >> > > > >> > >> > >> > > > *2. Pretrained MT models for lots of languages* >> > >> > >> > > > I have been working on a lib to retrieve parallel data >> from >> > >> many >> > >> > >> > sources >> > >> > >> > > -- >> > >> > >> > > > MTData [3] >> > >> > >> > > > There is so much parallel data out their for hundreds of >> > >> > languages. >> > >> > >> > > > My recent estimate is over a billion lines of parallel >> > >> sentences >> > >> > for >> > >> > >> > over >> > >> > >> > > > 500 languages is freely and publicly available for >> download >> > >> using >> > >> > >> > MTData >> > >> > >> > > > tool. >> > >> > >> > > > If we find some sponsors to lend us some resources, we >> could >> > >> train >> > >> > >> > better >> > >> > >> > > > MT models and update the Language Packs section [4]. >> > >> > >> > > > Perhaps, one massively multilingual NMT model that >> supports >> > >> many >> > >> > >> > > > translation directions (I know its possible with NMT; I >> tested >> > >> it >> > >> > >> > > recently >> > >> > >> > > > with RTG) >> > >> > >> > > > >> > >> > >> > > > I am interested in hearing what others are thinking. >> > >> > >> > > > >> > >> > >> > > > [1] >> > >> > >> > > > >> > >> > >> > > > >> > >> > >> > > >> > >> > >> > >> > >> > >> >> > >> > >> > >> >> https://mail-archives.apache.org/mod_mbox/joshua-dev/201709.mbox/%3CA481E867-A845-4BC0-B5AF-5CEAAB3D0B7D%40cs.jhu.edu%3E >> > >> > >> > > > [2] - >> > >> > >> https://github.com/apache/joshua/pulls?q=author%3Athammegowda+ >> > >> > >> > > > [3] - https://github.com/thammegowda/mtdata >> > >> > >> > > > [4] - >> > >> > >> > >> https://cwiki.apache.org/confluence/display/JOSHUA/Language+Packs >> > >> > >> > > > >> > >> > >> > > > >> > >> > >> > > > Cheers, >> > >> > >> > > > TG >> > >> > >> > > > >> > >> > >> > > > -- >> > >> > >> > > > *Thamme Gowda * >> > >> > >> > > > @thammegowda <https://twitter.com/thammegowda> | >> > >> > >> https://isi.edu/~tg >> > >> > >> > > > ~Sent via somebody's Webmail server >> > >> > >> > > > >> > >> > >> > > > >> > >> > >> > > > ಸೋಮ, ಅಕ್ಟೋ 5, 2020 ರಂದು 12:16 ಪೂರ್ವಾಹ್ನ ಸಮಯಕ್ಕೆ ರಂದು >> Tommaso >> > >> > >> Teofili < >> > >> > >> > > > tommaso.teof...@gmail.com> ಅವರು ಬರೆದಿದ್ದಾರೆ: >> > >> > >> > > > >> > >> > >> > > > > Hi all, >> > >> > >> > > > > >> > >> > >> > > > > This is a roll call for people interested in >> contributing to >> > >> > >> Apache >> > >> > >> > > > Joshua >> > >> > >> > > > > going forward. >> > >> > >> > > > > Contributing could be not just code, but anything that >> may >> > >> help >> > >> > >> the >> > >> > >> > > > project >> > >> > >> > > > > or serve the community. >> > >> > >> > > > > >> > >> > >> > > > > In case you're interested in helping out please speak >> up :-) >> > >> > >> > > > > >> > >> > >> > > > > Code-wise Joshua has not evolved much in the latest >> months, >> > >> > >> there's >> > >> > >> > > room >> > >> > >> > > > > for both improvements to the current code (make a new >> minor >> > >> > >> release) >> > >> > >> > > and >> > >> > >> > > > > new ideas / code branches (e.g. neural MT based Joshua >> > >> Decoder). >> > >> > >> > > > > >> > >> > >> > > > > Regards, >> > >> > >> > > > > Tommaso >> > >> > >> > > > > >> > >> > >> > > > >> > >> > >> > > >> > >> > >> > >> > >> > >> >> > >> > > >> > >> > >> > >> >> > > >> >
