def interactive_shell(self, tags, processing_word):
idx_to_tag = {idx: tag for tag, idx in tags.items()}
saver = tf.train.Saver()
with tf.Session() as sess:
saver.restore(sess, self.config.model_output)
self.logger.info(
"Interactive Shell Started\nType 'quit' to quit the shell")
while True:
try:
sentence = input("input> ")
words_raw = sentence.strip().split(" ")
if words_raw == ["quit"]:
break
words = [processing_word(w) for w in words_raw]
if type(words[0]) == tuple:
words = zip(*words)
pred_ids, _ = self.predict_batch(sess, [words])
preds = [idx_to_tag[idx] for idx in list(pred_ids[0])]
print_sentence(logger=self.logger,
data={
"x": words_raw,
"y": preds
})
except Exception:
pass
def interactive_shell(self, tags, processing_word):
idx_to_tag = {idx: tag for tag, idx in tags.items()}
saver = tf.train.Saver()
with tf.Session() as sess:
saver.restore(sess, self.config.model_output)
self.logger.info("""
This is an interactive mode.
To exit, enter 'exit'.
You can enter a sentence like
input> I love Paris""")
while True:
try:
try:
# for python 2
sentence = raw_input("input> ")
except NameError:
# for python 3
sentence = input("input> ")
words_raw = sentence.strip().split(" ")
if words_raw == ["exit"]:
break
words = [processing_word(w) for w in words_raw]
if type(words[0]) == tuple:
words = zip(*words)
pred_ids, _ = self.predict_batch(sess, [words])
preds = [idx_to_tag[idx] for idx in list(pred_ids[0])]
print_sentence(self.logger, {"x": words_raw, "y": preds})
except Exception:
pass
def interactive_shell_multiline(self, tags, processing_word):
idx_to_tag = {idx: tag for tag, idx in tags.items()}
saver = tf.train.Saver()
with tf.Session() as sess:
saver.restore(sess, self.config.model_output)
stopword = "PREDICT!"
while True:
try:
self.logger.info("This is an interactive mode. Enter an email, then type \"PREDICT!\" and hit enter:")
text = ""
while True:
line = input()
if line.strip() == stopword:
break
text += line + "\n"
text_list = list(filter(None, text.split("\n")))
text_list = filter(lambda line: line.strip(), text_list)
for line in text_list:
words_raw = line.split()
words = list(map(processing_word, words_raw))
if type(words[0]) == tuple:
words = list(zip(*words))
pred_ids, _ = self.predict_batch(sess, [words])
preds = [idx_to_tag[idx] for idx in list(pred_ids[0])]
print_sentence(self.logger, {"x": words_raw, "y": preds})
except EOFError:
print("Closing session.")
break
def interactive(self, tags, processing_word):
idx_to_tag = {idx: tag for tag, idx in tags.items()}
saver = tf.train.Saver()
with tf.Session() as sess:
saver.restore(sess, self.config.model_output)
self.logger.info("This is an interactive mode, enter a sentence:")
while True:
try:
sentence = raw_input("input> ")
#words_raw = sentence.strip().split(" ") english words seperated by space
# words_raw = list(sentence.encode("utf-8"))
words_raw = character_separation(sentence)[0].split(' ')
words_raw = [unicode(word, 'utf-8') for word in words_raw]
words = map(processing_word, words_raw)
words = list(words)
#if type(words[0]) == tuple:
# words = zip(*words)
pred_ids, _ = self.predict_batch(sess, [words])
preds = map(lambda idx: idx_to_tag[idx], list(pred_ids[0]))
# print(list(preds))
print_sentence(self.logger, {"x": words_raw, "y": preds})
return list(preds)
except EOFError:
print("Closing session.")
break
def interactive_shell(self, tags, processing_word):
idx_to_tag = {idx: tag for tag, idx in tags.items()}
saver = tf.train.Saver()
with tf.Session() as sess:
saver.restore(sess, self.config.model_output)
self.logger.info("""
This is an interactive mode.
To exit, enter 'exit'.
You can enter a sentence like
input> I love Paris""")
while True:
try:
try:
# for python 2
sentence = raw_input("input> ")
except NameError:
# for python 3
sentence = input("input> ")
words_raw = sentence.strip().split(" ")
if words_raw == ["exit"]:
break
words = [processing_word(w) for w in words_raw]
if type(words[0]) == tuple:
words = zip(*words)
pred_ids, _ = self.predict_batch(sess, [words])
preds = [idx_to_tag[idx] for idx in list(pred_ids[0])]
print_sentence(self.logger, {"x": words_raw, "y": preds})
except Exception:
pass
def rec(sentence):
try:
processing_word = get_processing_word(nlu.vocab_words,
lowercase=config.lowercase)
# print character_separation(sentence)[0]
words_raw = character_separation(sentence)[0].split(' ')
# for word in words_raw:
# if type(word)==str:
words_raw = [unicode(word, 'utf-8') for word in words_raw]
# words_raw = [word.decode('utf-8') for word in words_raw]
# else:
# words_raw = [unicode(word, 'utf-8') for word in words_raw]
words = map(processing_word, words_raw)
words = list(words)
pred_ids, _ = nlu.model.predict_batch(nlu.sess, [words])
preds = map(lambda idx: nlu.idx_to_tag[idx], list(pred_ids[0]))
# print(list(preds))
print_sentence(nlu.model.logger, {"x": words_raw, "y": preds})
return list(preds)
except EOFError:
print("Closing session.")
# nlu.rec('请播放电视剧三生三世十里桃花')
# nlu.rec('请播放电视剧三生三世十里桃花')
# nlu.rec('请播放电视剧三生三世十里桃花')
def interactive_shell(self, tags, processing_word):
kkma = Komoran()
idx_to_tag = {idx: tag for tag, idx in tags.items()}
saver = tf.train.Saver()
with tf.Session() as sess:
saver.restore(sess, self.config.model_output)
self.logger.info("""
This is an interactive mode.
To exit, enter 'exit'.
You can enter a sentence like
input> I love Paris""")
while True:
try:
try:
# for python 2
sentence = raw_input("input> ")
except NameError:
# for python 3
sentence = input("input> ")
if "exit" in sentence:
break
print(sentence)
sentence = sentence.split(" ")
print(sentence)
words_raw = []
words_list = []
positions = []
for i, sen in enumerate(sentence):
if sen is None:
continue
poses = kkma.pos(sen)
for pos in poses:
words_raw.append(pos[0] + "/" + pos[1])
words_list.append(pos[0])
positions.append(i + 1)
print(words_raw)
words = [processing_word(w) for w in words_raw]
for w in words:
print(w)
if type(words[0]) == tuple:
words = zip(*words)
print("go batch")
pred_ids, _ = self.predict_batch(sess, [words],
[positions])
preds = [idx_to_tag[idx] for idx in list(pred_ids[0])]
print_sentence(self.logger, {"x": words_list, "y": preds})
except Exception:
pass
def interactive_shell(self, tags, processing_word):
idx_to_tag = {idx: tag for tag, idx in tags.iteritems()}
saver = tf.train.Saver()
with tf.Session() as sess:
saver.restore(sess, self.config.model_output)
self.logger.info("This is an interactive mode, enter a sentence:")
while True:
try:
sentence = raw_input("input> ")
words_raw = sentence.strip().split(" ")
words = map(processing_word, words_raw)
if type(words[0]) == tuple:
words = zip(*words)
pred_ids, _ = self.predict_batch(sess, [words])
preds = map(lambda idx: idx_to_tag[idx], list(pred_ids[0]))
print_sentence(self.logger, {"x": words_raw, "y": preds})
except EOFError:
print("Closing session.")
break
def interactive_shell(self, tags, processing_word):
idx_to_tag = {idx: tag for tag, idx in tags.iteritems()}
saver = tf.train.Saver()
with tf.Session() as sess:
saver.restore(sess, self.config.model_output)
self.logger.info("This is an interactive mode, enter a sentence:")
while True:
try:
sentence = raw_input("input> ")
words_raw = sentence.strip().split(" ")
words = map(processing_word, words_raw)
if type(words[0]) == tuple:
words = zip(*words)
pred_ids, _ = self.predict_batch(sess, [words])
preds = map(lambda idx: idx_to_tag[idx], list(pred_ids[0]))
print_sentence(self.logger, {"x": words_raw, "y": preds})
except EOFError:
print("Closing session.")
break