# -*- coding: utf-8 -*- ''' Created on 2013-04-28 15:53 @summary: test case for MlpBigram @author: egg ''' from nlpdict.NlpDict import NlpDict from pylm.MlpBigram import MlpBigram import numpy import time import theano.sandbox.cuda nlpdict = NlpDict() nlpdict.buildfromfile('./data/pku_train_nw.ltxt') ############# # Trainging # ############# # text f = file('./data/pku_train_nw.ltxt') text = unicode(f.read(), 'utf-8') text = text.replace(" ", "") f.close() len_text = len(text) print "Train size is: %s" % len_text theano.sandbox.cuda.use('gpu0')
# -*- coding: utf-8 -*- ''' Created on 2013-05-05 23:00 @summary: Test case on RnnLM @author: Playcoin ''' from nlpdict.NlpDict import NlpDict from pylm.RnnLM import RnnLM import numpy import time import theano.sandbox.cuda theano.sandbox.cuda.use('gpu0') nlpdict = NlpDict() nlpdict.buildfromfile('./data/text.txt') ############# # Trainging # ############# # text f = file('./data/text.txt') text = unicode(f.read(), 'utf-8') text = text.replace(" ", "") f.close() len_text = len(text) print "Train size is: %s" % len_text
# -*- coding: utf-8 -*- ''' Created on 2013-04-12 23:01 @summary: 测试用例 @author: Playcoin ''' from nlpdict.NlpDict import NlpDict from pylm.Ngram import Ngram import numpy nlpdict = NlpDict() nlpdict.buildfromfile('./data/pku_train_nw.ltxt') # text f = file('./data/pku_train_nw.ltxt') text = unicode(f.read(), 'utf-8') text = text.replace(" ", "") f.close() len_text = len(text) print "Train size is: %s" % len_text # ngram_file_path = "./data/ngram.model.obj" ngram = Ngram(nlpdict, 2) ngram.traintext(text) # print "Save N-gram model" # # ngram.savemodel(ngram_file_path)
# -*- coding: utf-8 -*- ''' Created on 2013-05-05 23:00 @summary: Test case on RnnLM @author: Playcoin ''' from nlpdict.NlpDict import NlpDict from pylm.RnnLM import RnnLM import numpy import time import theano.sandbox.cuda nlpdict = NlpDict() nlpdict.buildfromfile('./data/text.txt') ############# # Trainging # ############# # text f = file('./data/text.txt') text = unicode(f.read(), 'utf-8') text = text.replace(" ", "") f.close() len_text = len(text) print "Train size is: %s" % len_text rnnlm = RnnLM(nlpdict, n_hidden=30, lr=0.09, batch_size=50)