def vectorize_files(fileroot,savepath):
data = ftools.read_dir_lines_dict(fileroot)
auto = AutoCoder()
count = 0
print(len(data.keys()))
for key in data.keys():
text = '。'.join(data[key])
sens, sens_words, sens_tags = auto.preprocess(text)
start = time.time()
sens_vector,essay_vector = auto.vectorize(sens_words, sens_tags)
end = time.time()
key_text =''.join([''.join(var) for var in sens_words])
save_key = tools.md5(key_text)
tmp =[list(var) for var in sens_vector]
save_object = [tmp,list(essay_vector)]
tools.save_object(save_object,Dir.res + "/encoder/cleandata_8700/"+save_key)
count+=1
print(count,len(data.keys()),end-start)
def __init__(self,corpus,corpus_ref,reprocess = True,parall = False,cpu = 4):
self.file = corpus
self.file_ref = corpus_ref
self.data = tools.read_dir_lines_dict(self.file)
self.rouge= src.evaluation.PythonROUGE
self.word_index={}
self.dir_path = corpus[:corpus.rindex("/")]
self.ref_processed = self.dir_path + "/ref_processed/"
self.ref_seperate = self.dir_path + "/ref_seperate/"
self.indexlize_data(reprocess=reprocess)
self.start =0
self.parall = parall
self.cpu = 4
