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                Instructions to BUILD a NMT system
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1) Create a data directory (/home/data) with the following files:
    train.src
    train.trg
    dev.src
    dev.trg

2) Copy the configuration file from /hltsrv1/software/nematus-master/config.cfg to /home/data

3) Edit the config file (/home/data/config.cfg) to set all relevant parameters 

4) Login to a gpu machine: (if your system runs as expected then you can submit the job with qsub)
       qlogin -q gpgpu.q -l mf=500G,gpu=1

5) Start training
       /hltsrv1/software/nematus-master/train.sh /home/data/config.cfg gpuID
       (where gpuID: {gpu0, gpu1,gpu2,gpu3})


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              Instructions to RESTART the training of an existing NMT system

1) set the flag reload_=True in the configuration file (/home/data/config.cfg)
2) Follow steps 4 and 5 mentioned above (i.e. qlogin and then start training)

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              Instructions to DECODE a test file with an existing NMT model

/hltsrv1/software/nematus-master/translate.sh {path-to-model.npz} {test.src} {reference} {gpuID}

1) The decoder uses a beam search size of 12
2) This command will generate 
       1) hypothesis file (the MT output) {test.src.ouput}
       2) word alignment probability file {test.src.output.align}
       3) clean hypothesis file (the MT output is post-processed to combine the subwords) {test.src.output.postprocessed}
3) BLEU score is computed between the reference and test.src.output.postprocessed

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              Instructions on setting up the shell environment

export PYTHONPATH=/hltsrv0/chatterjee/.local/lib/python2.7/site-packages

(This part is in progress)

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