def __judge_print(self):
"""
judge slack call for chainer
Example:
chainer:{your sentence}
chainer return the sentence
chainer_train:{your sentence}
start train
"""
if len(self.data) >= 1 and "text" in self.data[0]:
print(self.data[0]["text"])
if "chainer:" in self.data[0]["text"]:
# input sentence
src_batch = self.__input_sentence()
# predict
hyp_batch = self.__predict_sentence(src_batch)
# show predict word
word = ''.join(hyp_batch[0]).replace("</s>", "")
print(
self.slack_channel.api_call("chat.postMessage",
user=self.usr,
channel=self.chan,
text=word))
if "chainer_train" in self.data[0]["text"]:
self.__setting_parameter()
model = AttentionDialogue.load_spec(self.model_name + '.spec',
self.XP)
dialogue = EncoderDecoderModelAttention(self.parameter)
serializers.load_hdf5(self.model_name + '.weights', model)
dialogue.attention_dialogue = model
dialogue.word2vecFlag = False
dialogue.train()
def __judge_print(self):
"""
judge slack call for chainer
Example:
chainer:{your sentence}
chainer return the sentence
chainer_train:{your sentence}
start train
"""
if len(self.data) >= 1 and "text" in self.data[0]:
print(self.data[0]["text"])
if "chainer:" in self.data[0]["text"]:
# input sentence
src_batch = self.__input_sentence()
# predict
hyp_batch = self.__predict_sentence(src_batch)
# show predict word
word = ''.join(hyp_batch[0]).replace("</s>", "")
print(self.slack_channel.api_call("chat.postMessage", user=self.usr, channel=self.chan, text=word))
if "chainer_train" in self.data[0]["text"]:
self.__setting_parameter()
model = AttentionDialogue.load_spec(self.model_name + '.spec', self.XP)
dialogue = EncoderDecoderModelAttention(self.parameter)
serializers.load_hdf5(self.model_name + '.weights', model)
dialogue.attention_dialogue = model
dialogue.word2vecFlag = False
dialogue.train()
