def __init__(self, name):
print("Starting new Tensorflow session...")
self.session = tf.Session()
print("Loading pipeline modules...")
self.tokenizer = segmenter.load_model(name)
self.tagger_pos = pos_tagger.load_model(name) # class tagger_pos
self.tagger_ner = ner_tagger.load_model(name) # class tagger_ner
deepnlp.download(module='segment', name='zh_entertainment')
deepnlp.download(module='pos', name='en')
deepnlp.download(module='ner', name='zh_o2o')
# Download module
deepnlp.download('segment')
deepnlp.download('pos')
deepnlp.download('ner')
deepnlp.download('parse')
# deepnlp.download()
## 测试 load model
from deepnlp import segmenter
try:
tokenizer = segmenter.load_model(name='zh')
tokenizer = segmenter.load_model(name='zh_o2o')
tokenizer = segmenter.load_model(name='zh_entertainment')
except Exception as e:
print("DEBUG: ERROR Found...")
print(e)
## pos
from deepnlp import pos_tagger
try:
tagger = pos_tagger.load_model(
name='en') # Loading English model, lang code 'en'
tagger = pos_tagger.load_model(
name='zh') # Loading English model, lang code 'en'
except Exception as e:
print("DEBUG: ERROR Found...")
#coding:utf-8
from __future__ import unicode_literals # compatible with python3 unicode
from deepnlp import segmenter
from deepnlp import pos_tagger
# Load Model
tokenizer = segmenter.load_model(name='zh')
tagger = pos_tagger.load_model(name='zh')
#Segmentation
text = "我爱吃北京烤鸭" # unicode coding, py2 and py3 compatible
words = tokenizer.seg(text)
print(" ".join(words))
#POS Tagging
tagging = tagger.predict(words)
for (w, t) in tagging:
pair = w + "/" + t
print(pair)
#Results
#我/r
#爱/v
#吃/v
#北京/ns
#烤鸭/n
#!/usr/bin/python
# -*- coding:utf-8 -*-
import deepnlp
from deepnlp import segmenter
try:
deepnlp.download("segment", "zh_finance")
except Exception as e:
print (e)
deepnlp.register_model("segment", "zh_finance")
deepnlp.download("segment", "zh_finance")
try:
seg_tagger = segmenter.load_model("zh_finance")
except Exception as e:
print (e)
from deepnlp import pos_tagger
try:
deepnlp.download("pos", "zh_finance")
except Exception as e:
print (e)
deepnlp.register_model("pos", "zh_finance")
deepnlp.download("pos", "zh_finance")
try:
pos_tagger.load_model("zh_finance")
except Exception as e:
print (e)