def get_piece_parsed_pack(nodel_l):#多个处理
resl=[]
tmp='tmp'#write feature file
while True:
indexl=[]
fts_all=[]
i=0
while i<len(nodel_l):
if len(nodel_l[i])<=1:
i+=1
continue
indexl.append(i)
fts=get_nodel_feature(nodel_l[i])
fts_all.extend(fts)
fts_all.append('')
i+=1
if len(indexl)==0:
break
write_file(tmp,fts_all)
tags_all=piece_parse_model_test_pack(tmp)#get result
i=0
for tags in tags_all:
nodel_l[indexl[i]]=change_nodel(nodel_l[indexl[i]],tags)
i+=1
####
for x in nodel_l:
if x=='':
resl.append('')
else:
resl.append(x[0])
return resl
def get_piece_parsed(nodel, tag_model, pcfg_model):#返回树节点结构
kbest=[(nodel,0)] #keep k best,(nodes, score)#diff:diff from last one
while True:
kbest,ktmp=get_undone(kbest,beam_size)
if len(ktmp)==0: #all finished
break#[0]
fts_l=[]
for ndl in ktmp:
fts=get_nodel_feature(ndl[0]) # get features
fts_l.extend(fts)
fts_l.append('')
#tmp='tmp'#write feature file
write_file(piece_parse_tmp,fts_l)
crftag_l=piece_parse_model_test(piece_parse_tmp)#get result
#print len(crftag_l),len(ktmp)
if len(crftag_l)!=len(ktmp):
#print crftag_l
print 'number not match?piece_parse.py#get_piece_parsed'
# new_ktmp=[]
# for i in xrange(len(crftag_l)):
# # return: [(nodel, diff_node_index, new_tag_features)]
# new_ndl_l=change_nodel(ktmp[i][0],crftag_l[i])
# for new_ndl in new_ndl_l:
# new_ktmp.append((new_ndl[0],
# ktmp[i][1]+count_score(new_ndl[1],pcfg_model)))
# #count_score(pcfg_model,new_ndl[1])),the diff, new node, add up it's score
new_ndl_l=[]
fts_l=[]
for i in xrange(len(crftag_l)): # pack the tag crf task to be faster
# return: [(nodel, diff_node_index, new_tag_features)]
new_ndl_tmp=change_nodel(ktmp[i][0],crftag_l[i])
new_ndl_l.append(new_ndl_tmp)
fts_l.extend([x[2] for x in new_ndl_tmp])
new_tag_l=get_new_tag_pack_main(fts_l)
tag_index=0
new_ktmp=[]
for i in xrange(len(crftag_l)):
for new_ndl in new_ndl_l[i]:
# new_ndl=(nodel, diff_node_index, new_tag_features)
new_ndl[0][new_ndl[1]].tag=new_tag_l[tag_index]
tag_index+=1
new_ktmp.append((new_ndl[0],
ktmp[i][1]+count_score(new_ndl[0][new_ndl[1]],pcfg_model)))
#count_score(pcfg_model,new_ndl[1])),the diff, new node, add up it's score
kbest.extend(new_ktmp)
#print nodel
kbest=[(x[0][0],x[1]) for x in kbest] #only the node left
return kbest#todo 每个子句都是前最佳然后拼在一起,不能只是单个子句最佳,done
