o ii @sddlZddlZddlmZzddlZWn eyYnwdadddZddZddZ d d Z d d Z d dZ e dkrEe e dSdS)N) find_binarycCstd|dgdgddadS)NtadmTADMzhttp://tadm.sf.net)env_vars binary_namesurl)r _tadm_bin)binr M/var/www/edux/Edux_v2/venv/lib/python3.10/site-packages/nltk/classify/tadm.py config_tadms r c Csz|}|D]4\}}dt|}|||D]"}|||}dt||kt|ddd|Df} || qqdS)aT Generate an input file for ``tadm`` based on the given corpus of classified tokens. :type train_toks: list(tuple(dict, str)) :param train_toks: Training data, represented as a list of pairs, the first member of which is a feature dictionary, and the second of which is a classification label. :type encoding: TadmEventMaxentFeatureEncoding :param encoding: A feature encoding, used to convert featuresets into feature vectors. :type stream: stream :param stream: The stream to which the ``tadm`` input file should be written. z%d z %d %d %s  css|]}d|VqdS)z%d %dNr ).0ur r r 9sz"write_tadm_file..N)labelslenwriteencodeintjoin) train_toksencodingstreamr featuresetlabel length_line known_labelvliner r r write_tadm_files      r cCs,g}|D] }|t|qt|dS)z Given the stdout output generated by ``tadm`` when training a model, return a ``numpy`` array containing the corresponding weight vector. d)appendfloatstripnumpyarray) paramfileweightsrr r r parse_tadm_weights>s r)cCsjt|tr tdtdurttg|}tj|tjd}| \}}|j dkr3t t |t ddS)z< Call the ``tadm`` binary with the given arguments. z args should be a list of stringsN)stdoutrztadm command failed!) isinstancestr TypeErrorrr subprocessPopensysr* communicate returncodeprintOSError)argscmdpr*stderrr r r call_tadmJs    r9cCs&ddlm}ddlm}||j}dS)Nr)TadmMaxentClassifier) names_demo)nltk.classify.maxentr:nltk.classify.utilr;train)r:r; classifierr r r r;_s  r;cCsddl}ddlm}dddddfdddddfddddd dfg}||}t|||jtt|D] }td | ||fq7tdS) Nr)TadmEventMaxentFeatureEncoding)f0f1f3A)rBf2f4B)rBrFrDrGz %s --> %d) r0r<r@r>r r*r3rangelengthdescribe)r0r@tokensrir r r encoding_demofs   rO__main__)N)r.r0nltk.internalsrr% ImportErrorrr r r)r9r;rO__name__r r r r s&    "