Hi Per

It's probably as easy to filter and binarise the input yourself before 
tuning using the filter-model-given-input.pl script in Moses, and using 
the -Binarizer argument to pass it the path to the processPhraseTable 
binary.

By default, mert-moses.pl will filter (so the command below will filter) 
and this may reduce the size of the phrase table sufficiently for you. 
You can add binarisation to mert-moses.pl by using the --filtercmd to 
give it the filter script with its binariser argument,

cheers - Barry

On 11/03/13 15:27, Per Tunedal wrote:
> Hi,
> thanks for your kind advice. I plan to use the tuning command displayed
> at the Baseline page:
> nohup nice ~/mosesdecoder/scripts/training/mert-moses.pl
> ~/corpus/news-test2008.true.fr ~/corpus/news-test2008.true.en \
>    ~/mosesdecoder/bin/moses  train/model/moses.ini --mertdir
>    ~/mosesdecoder/bin/ &> mert.out &
> with my own "small" tuning-corpus (10% of the training-corpus size).
>
> Will this "give [the tuning script] a binariser" ? If not, what shall I
> add to the command?
>
> Yours,
> Per Tunedal
>
> On Mon, Mar 11, 2013, at 16:00, Barry Haddow wrote:
>> Hi Per
>>
>> The tuning script will filter the phrase table (leaving only the entries
>> required for the tuning set) and then binarise it (if you give it a
>> binariser) before running the actual tuning. So no, the whole table
>> doesn't need to be loaded into memory during tuning.
>>
>> You could prune before tuning, and I don't know how this will compare to
>> pruning after tuning. I'm not sure if anyone has tried it. The
>> signifcance filtering (in advanced features) works (afaik), although
>> there are a few steps involved in building the code. The relent
>> filtering has bit-rotted a bit, but you can run it with Moses v0.91.
>>
>> cheers - Barry
>>
>> On 11/03/13 14:37, Per Tunedal wrote:
>>> Hi Barry,
>>> Binarise, yes. But before that I plan to prune the translation table
>>> (Advanced features). Any hints?
>>>
>>> Back to my original question, can pruning be done before tuning? Is it
>>> possible to binarise too, before tuning? (The base-line page suggests
>>> binarisiation after tuning.)  I fear that the tuning might be an
>>> overwhelming task for my poor computer.
>>>
>>> Yours,
>>> Per Tunedal
>>>
>>> BTW What is actually done when tuning? Has all the tables to be loaded
>>> into memory?
>>>
>>> On Mon, Mar 11, 2013, at 10:42, Barry Haddow wrote:
>>>> Hi Per
>>>>
>>>> You need to binarise the models (phrase table, reordering table and
>>>> language model) before running Moses
>>>> http://www.statmt.org/moses/?n=Moses.AdvancedFeatures#ntoc3
>>>> If you don't binarise then Moses will load all the tables into memory,
>>>> so the memory requirement will be at least as large as the on-disk size,
>>>> in fact a lot more since it doesn't store them efficiently.
>>>>
>>>> The complexity of training is not easy to calculate since there are a
>>>> number of steps, but since one step involves sorting the list of
>>>> extracted phrases the complexity must be at least as bad as that.
>>>>
>>>> cheers - Barry
>>>>
>>>> On 11/03/13 08:24, Per Tunedal wrote:
>>>>> Hi Barry,
>>>>> it turns out that me too have succeeded to build my model in one day. I
>>>>> forced a restart and checked the log and the working directory. All is
>>>>> fine! The moses.ini file was created only 7 hours after submitting the
>>>>> command to build the model. I don't understand why the computer didn't
>>>>> respond, though.
>>>>>
>>>>> How does the time to build a model vary with the size of the corpus?
>>>>> Linearly? Or quadratic? Or what?
>>>>>
>>>>> I've now tried to do a test translation, without any tuning. I soon ran
>>>>> out of memory: even the virtual memory was exhausted after a while. Any
>>>>> way to predict the memory needed?
>>>>>
>>>>> Yours,
>>>>> Per Tunedal
>>>>>
>>>>>
>>>>> On Sun, Mar 10, 2013, at 11:39, Barry Haddow wrote:
>>>>>> Hi Per
>>>>>>
>>>>>> I would suggest starting from a smallish corpus, then building up to a
>>>>>> larger one, to get experience with the process. Using the news commentary
>>>>>> corpus described in the Moses baseline page, I was able to train and tune
>>>>>> in an evening on my laptop.
>>>>>>
>>>>>> There have been papers on predicting quality given corpus size, but
>>>>>> there's not an easy answer. Look for Marco Turchi at last year's EAMT, or
>>>>>> (I think) one by Xerox Grenoble from last year.
>>>>>>
>>>>>> As regards europarl, yes there's noise, but the models are quite robust
>>>>>> to it
>>>>>>
>>>>>> Cheers - Barry
>>>>>>
>>>>>> Per Tunedal <[email protected]> wrote:
>>>>>>
>>>>>>> Hi,
>>>>>>> Is there any way to predict the time for training and/or tuning, given
>>>>>>> the corpus size and the computer specifications? It would be nice to
>>>>>>> know  what would be a reasonable time for accomplishing the tasks. Now
>>>>>>> my computer has been running for 3 days and nights and doesn't respond
>>>>>>> any more: I cannot "wake it" to see what's going on. I don't know if
>>>>>>> it's normal or if something has gone havoc.
>>>>>>>
>>>>>>> I agree with Ken Fasano, that it would be very useful to know how big a
>>>>>>> corpus is needed to get meaningful results. I would like to be able to
>>>>>>> judge the quality of the translation, to see if it would be useful to
>>>>>>> continue with Moses in some more serious manner.
>>>>>>>
>>>>>>> I'm a bit puzzled by the parameter limiting sentence length to, say 80
>>>>>>> (characters?), giving that e.g. the Europarl corpus contains mainly VERY
>>>>>>> long sentences. Skipping long sentences probably implicates that many
>>>>>>> typical expressions are lost in the model. Wouldn't it be more sensible
>>>>>>> to skip short sentences? Or to make a representative sample of the
>>>>>>> corpus, by doing a random sample of a sufficient size or something?
>>>>>>> Yours,
>>>>>>> Per Tunedal
>>>>>>>
>>>>>>> PS I've noticed that the Europarl corpus contains some very bad,
>>>>>>> completely incomprehensible, translations. That makes me question the
>>>>>>> quality of that corpus. How are the translations actually done? By
>>>>>>> humans relying heavily on machine translation? Sometimes letting some
>>>>>>> strange MT-translation pass?
>>>>>>>
>>>>>>> On Sat, Mar 9, 2013, at 18:43, Ken Fasano wrote:
>>>>>>>> I'd like to respond to this thread. I, too, have limited resources (at
>>>>>>>> work, at least) - a 3 GB RAM 32-bit Windows i5 machine with Linux 
>>>>>>>> running
>>>>>>>> on VMWare with 2.5 GB RAM. Training and tuning take many hours; the
>>>>>>>> machine is running BitParl over the weekend and may be done with
>>>>>>>> NewsCommentary de-en (DE) on Monday when I get back to work. I'm afraid
>>>>>>>> after all that I won't be able to subsequently run Collins on the
>>>>>>>> English, train, tune, and decode all that and, even if it takes 
>>>>>>>> forever,
>>>>>>>> expect it to run with the limited memory resources available.
>>>>>>>> What I think I need to do is trim the corpora according to some 
>>>>>>>> criteria
>>>>>>>> that isn't too complicated. Is it enough for learning purposes (we are 
>>>>>>>> a
>>>>>>>> long way from any sort of real comparison of results, let alone
>>>>>>>> production - this will receive proper hardware) to take the first n
>>>>>>>> sentences, or every nth sentence? The result is simply to get a feel 
>>>>>>>> for
>>>>>>>> the various modes of tree-based SMT, run hierarchical phrase,
>>>>>>>> string-to-tree, tree-to-string and tree-to-tree without worrying which
>>>>>>>> one is the best - the idea is just to get some experience with it.What
>>>>>>>> would be a good number of sentences to take so that it runs relatively
>>>>>>>> quickly, without killing RAM, but produces results that aren't useless?
>>>>>>>> Thanks - and I'd like to thank everyone on the group for their eager
>>>>>>>> helpfulness, and for discussing things that I as a newbie find very
>>>>>>>> useful!
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>> Date: Sat, 9 Mar 2013 11:25:45 -0500
>>>>>>>>> From: [email protected]
>>>>>>>>> To: [email protected]
>>>>>>>>> Subject: Re: [Moses-support] Accelerate the tuning
>>>>>>>>>
>>>>>>>>> Hi,
>>>>>>>>>
>>>>>>>>>       It won't fix everything, but there is a long-term TODO to 
>>>>>>>>> rewrite
>>>>>>>>> phrase table scoring to use binary files with vocabulary ids instead 
>>>>>>>>> of
>>>>>>>>> text files.
>>>>>>>>>
>>>>>>>>> Kenneth
>>>>>>>>>
>>>>>>>>> On 03/09/13 08:30, Per Tunedal wrote:
>>>>>>>>>> Hi,
>>>>>>>>>> the training seems to be an overwhelming task for my computer. If it
>>>>>>>>>> ever succeeds, I will have to undertake the even more demanding task 
>>>>>>>>>> of
>>>>>>>>>> tuning. Can anything be done to accelerate it?
>>>>>>>>>>
>>>>>>>>>> Specifically, I wonder if it's feasible to prune the translation 
>>>>>>>>>> table
>>>>>>>>>> before doing the tuning.
>>>>>>>>>>
>>>>>>>>>> Yours,
>>>>>>>>>> Per Tunedal
>>>>>>>>>>
>>>>>>>>>> PS I've abandoned the idea of building a Hierarchical phrase model, 
>>>>>>>>>> I'm
>>>>>>>>>> now trying to make a phrase-based system. I suppose that would use 
>>>>>>>>>> less
>>>>>>>>>> resources.
>>>>>>>>>>
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