o h@s dZddlmZddlZddlZddlZddlmZddlm Z ddl m Z m Z m Z ddlmZmZddlmmmZddlmmmZddlmZdd lmZmZmZed ZGd d d eZdddZ ddZ!dddZ"dddZ#e$dkre#dSdS)z A script to prepare all depparse datasets. Prepares each of train, dev, test. Example: python -m stanza.utils.datasets.prepare_depparse_treebank {TREEBANK} Example: python -m stanza.utils.datasets.prepare_depparse_treebank UD_English-EWT )EnumN)tagger)treebank_to_short_name)downloadDEFAULT_MODEL_DIRUnknownLanguageError)default_charlms pos_charlms) wordvec_args)add_charlm_argsbuild_charlm_args choose_charlmstanzac@seZdZdZdZdZdS)TagszTags parameter values.N)__name__ __module__ __qualname____doc__GOLD PREDICTEDrrj/var/www/html/env_mimamsha/lib/python3.10/site-packages/stanza/utils/datasets/prepare_depparse_treebank.pyrsrreturncCs|jdddtjtjdd|jdddtjdd|jd td d d |jd td dd |jdttjdddd |jddddddt|d S)zAdd specific args.z--gold tag_method store_constz,Use gold tags for building the depparse data)destactionconstdefaulthelpz --predictedz1Use predicted tags for building the depparse data)rrrr!--wordvec_pretrain_fileNz'Exact name of the pretrain file to read)typer r!z--tagger_modelzkTagger save file to use. If not specified, order searched will be saved/models, then $STANZA_RESOURCES_DIR --save_dir saved_modelsposz-Where to look for recently trained POS modelsz--no_download_taggerTdownload_tagger store_falsezDon't try to automatically download a tagger for retagging the dependencies. Will fail to make silver tags if there is no tagger model to be found)r rrr!) add_argumentrrrstrospathjoinr )parserrrradd_specific_args%s&    r/c s|r|Sttj|jd||f}t|dkr|dSt|dkrQdD]$fdd|D}t|dkr<|dSt|dkrItd|q%td||jsVdStjt |d |d }z t |dd |id W|St y}z td ||jf|d}~ww) zj Preferentially chooses a retrained tagger model, but tries to download one if that doesn't exist z %s_%s_*.ptrr)z_trans_tagger.ptz_charlm_tagger.ptz_nocharlm_tagger.ptcsg|] }|r|qSr)endswith).0xendingrr Bsz'choose_tagger_model..zWCould not choose among the candidate taggers... please pick one with --tagger_model: {}Nr&z.pt)langpackage processorsaThe language %s appears to be a language new to Stanza. Unfortunately, that means there are no taggers available for retagging the dependency dataset. Furthermore, there are no tagger models for this language found in %s. You can specify a different directory for already trained tagger models with --save_dir, specify an exact tagger model name with --tagger_model, or use gold tags with --gold) globr+r,r-save_dirlenFileNotFoundErrorformatr'rrr)short_languagedataset tagger_modelargs candidatesbest_candidatespos_patherr3rchoose_tagger_model6s0     rFc s.|jtjurt||||dd S|jtjurt|}|d\}}d|dd|d|ddgt|||j |}|d ur?t d t d |||t j|\}} d |d | g|jrbd|jg7nt||gt|||jtt} t|| } | fdd} t||||d| d Std|j)zProcess treebank.DEPPARSE_DATA_DIR_z --wordvec_dir WORDVEC_DIRz--langz --shorthandz--modepredictNzcCannot find a tagger for language %s, dataset %s - you can specify one with the --tagger_model flagz"Using tagger model in %s for %s_%sr$z --save_namer"csb|d|d|d}|d|d|d}d|d|g}|}td|||t|dS)N/.z.conlluz --eval_filez --output_filez+Running tagger to retag {} to {} Args: {})loggerinfor=rmain) tokenizer_dirtokenizer_filedest_dir dest_file short_nameoriginalretagged tagger_args base_argsrr retag_datasetysz'process_treebank..retag_datasetzUnknown tags method: {})rrrprepare_tokenizer_treebankcopy_conllu_treebankrrsplitrFr@r<rMrNr+r,wordvec_pretrain_filer r charlmrr r ValueErrorr=) treebank model_typepathsrArTr>r?r@ tagger_dir tagger_namer_ charlm_argsrZrrXrprocess_treebankUs2     rgcCstttjjtdS)zCall Process Treebank.N)commonrOrg ModelTypeDEPPARSEr/rrrrrOsrO__main__)rN)%renumrr9loggingr+ stanza.modelsrstanza.models.common.constantrstanza.resources.commonrrr!stanza.resources.default_packagesrr stanza.utils.datasets.commonutilsdatasetsrh0stanza.utils.datasets.prepare_tokenizer_treebankr[stanza.utils.training.run_posr stanza.utils.training.commonr r r getLoggerrMrr/rFrgrOrrrrrs,        4