o Ni@sddlZddlZddlZddlZddlZddlZddlmZddl m Z ddl m Z ddl m Z dgZdd Zdd d Z  dddZddZdddZddZddZddZdS)N)xrange) OneHotEncoder ngram_context)StructuredPerceptronrcCs dd}tj|r!tjd|||}|rd||fn|}t|td|d}t |j |Wdn1s?wYt d||jgt d||jt jgt d ||jt jt d ||jt jt d ||jt jdS) Ncs|d\}}|r |nt}t|}fdd|D}dd|D}dd|D}d}|r@t|td}|r>t|dn|}t|S)N/csg|] }|r|qS) startswith.0dr model_dirr M/home/ubuntu/.local/lib/python3.10/site-packages/indictrans/trunk/__init__.py s z0save_models..get_uid..cSsg|] }|ddqS)-)rsplitr r r rrscSsg|]}|r|qSr )isdigit)r uidr r rrr)key) rpartitionosgetcwdlistdirmaxintstr)out_dir parent_dir_existing_modelsuidsmax_idr rrget_uids  zsave_models..get_uidzPUserWarnning: Output directory `{0}` already exists. Renaming output directory. z%s-%sz %s/sparse.vecwz %s/classesz%s/coefz%s/intercept_initz%s/intercept_transz%s/intercept_final)rpathisdirsysstderrwriteformatmakedirsopenjsondump unique_featsnpsaveclasses_coef_astypefloat16intercept_init_intercept_trans_intercept_final_)clfencr r&rj_fpr r r save_modelss.        r?c st|\}}fdd|D}||}td|d(}tt|D]} |ddddt|| || Dq#WddS1sGwYdS)Ncsg|] }t|dqS)n) transformrr xr=ngramr rr9sztest_sp..z%s.outr'z%s  cSsg|]}d|qS) )join)r str r rr>) load_datapredictr/rlenr,rJzip) r<r= test_filerGXyX_y_outfpir rFrtest_sp7s    "rX 皙?%cCst|||d}||||S)N) random_staten_iterverbose)rfit)rRrSr]lr_expr\r^r<r r rtrain_spAs  racs0tt|fdd|D}|fS)Ncsg|]}|qSr )rCrDr=r rrLrLzfit_encoder..)rr_r3vstack)rRr rbr fit_encoderIsrdcsfdd|D}|S)Ncsg|]}t|dqSrArrDrGr rrQrz!build_context..r )rRrGr rer build_contextPsrfc Csgg}}gg}}tj|dd4}|D]&}|s*||||gg}}q|\}}||||qWd||fS1sHwY||fS)Nzutf-8)encoding)ior/stripappendsplit) data_filerRrS input_seq output_seqrVlinestr r rrMUs           rMc Cstjddd}|jddddd|jd d d td d dd|jdddtd d dd|jdddtdd dd|jdddtdd dd|jdd d!td"d d#d|jd$d%d&td'd d(d|jd)d*d+td,d d-d|jd.d/d0td d1d2||}|S)3Nrz2Structured perceptron for sequence classification.)prog descriptionz-vz --versionversionz %(prog)s 1.0)actionrtz-dz --data-filerlTz$training data-file: set of sequences)desttyperequiredmetavarhelpz-oz --output-dirr z'output directory to dump trained modelsz-nz--ngramsrGr@z/ngram context for feature extraction: default 4)rwrxdefaultrzr{z-ez--lr-expr`rZzBThe Exponent used for inverse scaling oflearning rate: default 0.1z-mz --max-iterr]z5Maximum number of iterations for training: default 15z-rz--random-stater\z:Random seed for shuffling sequences within each iteration.z-lz --verbosityr^rz&Verbosity level: default 0 (quiet moe)z-tz --test-filerQzGtesting data-file: optional: stores output sequences in `test_file.out`)rwrxrzr{)argparseArgumentParser add_argumentrrfloat parse_args)argsparserr r rrfs rcCsttjdd}t|j\}}t||jd}t|\}}t|||j |j |j |j }t |||j|jrFtjdt|||j|jddSdS)Nrrez Testing ... )rr*argvrMrlrfrGrdrar]r`r\r^r?r rQr+r,rX)rrRrSr=r<r r rmains  r)r@)rYrZr[r)rhrr*r0rnumpyr3 six.movesrindictrans._utilsrr perceptronr__all__r?rXrardrfrMrrr r r rs*     #    I