def __call__(self, annotion_list, back_word_list, p):
"""
Calculate the annotion and back word value
:param annotion_list:
:param back_word_list:
:param p: hidden value
:return:
"""
batch_size = p.data.shape[0]
exponential_list = []
sum_exponential = XP.fzeros((batch_size, 1))
# Calculate the total value list and total value
# Prepare the Convoluation
for annotion, back_word in zip(annotion_list, back_word_list):
weight = functions.tanh(
self.annotion_weight(annotion) + self.back_weight(back_word) +
self.pw(p))
exponential = functions.exp(self.weight_exponential(weight))
exponential_list.append(exponential)
sum_exponential += exponential
ZEROS = XP.fzeros((batch_size, self.hidden_size))
annotion_value = ZEROS
back_word_value = ZEROS
# Calculate the Convolution Value each annotion and back word
for annotion, back_word, exponential in zip(annotion_list,
back_word_list,
exponential_list):
exponential /= sum_exponential
annotion_value += functions.reshape(
functions.batch_matmul(annotion, exponential),
(batch_size, self.hidden_size))
back_word_value += functions.reshape(
functions.batch_matmul(back_word, exponential),
(batch_size, self.hidden_size))
return annotion_value, back_word_value
def __init__(self, data_model):
"""
Iniital Setting
:param data_model: Setting Slack Model. Slack Model has the a lot of paramater
"""
self.slack_channel = data_model.slack_channel
self.data = ""
self.parameter = data_model.parameter_dict
self.model_name = "../model_word_match/ChainerDialogue"
self.generation_limit = 200
"""
We confirm channel number
https://api.slack.com/methods/channels.list
"""
self.chan = data_model.chan
self.usr = data_model.user
self.mecab_dict = data_model.mecab_dict
self.Mecab = MeCab.Tagger("-Owakati -d %s" % self.mecab_dict)
XP.set_library(False, 0)
self.XP = XP
wn_summary_list = APP_ROOT + '/../Data/wn_total_summary_51519_limit05_out_put_list.txt'
self.input_module = InputFileCython(wn_summary_list)
self.input_module.input_special_format_file()
file_list = self.input_module.get_file_data()
self.class_word_vector = self.__make_class_word_vector(file_list)
self.sqlite_twitter_summary = SqliteTwitterSummary(
self.class_word_vector)
self.word_class_dict = self.sqlite_twitter_summary.make_class_word_dict(
)
self.word_class = ""
self.multi_train_execute = ExecuteAttentionDialogue()
self.elastic_search = GetAnswer()
def __call__(self, annotion_list, back_word_list, p):
"""
Calculate the annotion and back word value
:param annotion_list:
:param back_word_list:
:param p: hidden value
:return:
"""
batch_size = p.data.shape[0]
exponential_list = []
sum_exponential = XP.fzeros((batch_size, 1))
# Calculate the total value list and total value
# Prepare the Convoluation
for annotion, back_word in zip(annotion_list, back_word_list):
weight = functions.tanh(self.annotion_weight(annotion) + self.back_weight(back_word) + self.pw(p))
exponential = functions.exp(self.weight_exponential(weight))
exponential_list.append(exponential)
sum_exponential += exponential
ZEROS = XP.fzeros((batch_size, self.hidden_size))
annotion_value = ZEROS
back_word_value = ZEROS
# Calculate the Convolution Value each annotion and back word
for annotion, back_word, exponential in zip(annotion_list, back_word_list, exponential_list):
exponential /= sum_exponential
annotion_value += functions.reshape(functions.batch_matmul(annotion, exponential), (batch_size, self.hidden_size))
back_word_value += functions.reshape(functions.batch_matmul(back_word, exponential), (batch_size, self.hidden_size))
return annotion_value, back_word_value
def __init__(self, data_model):
"""
Iniital Setting
:param data_model: Setting Slack Model. Slack Model has the a lot of paramater
"""
self.slack_channel = data_model.slack_channel
self.data = ""
self.parameter = data_model.parameter_dict
self.model_name = "../model/ChainerDialogue"
self.generation_limit = 200
"""
We confirm channel number
https://api.slack.com/methods/channels.list
"""
self.chan = data_model.chan
self.usr = data_model.user
self.mecab_dict = data_model.mecab_dict
self.Mecab = MeCab.Tagger("-Owakati -d %s" % self.mecab_dict)
XP.set_library(False, 0)
self.XP = XP
def __init__(self, data_model):
"""
Iniital Setting
:param data_model: Setting Slack Model. Slack Model has the a lot of paramater
"""
self.slack_channel = data_model.slack_channel
self.data = ""
self.parameter = data_model.parameter_dict
self.model_name = "../model/ChainerDialogue"
self.generation_limit = 200
"""
We confirm channel number
https://api.slack.com/methods/channels.list
"""
self.chan = data_model.chan
self.usr = data_model.user
self.mecab_dict = data_model.mecab_dict
self.Mecab = MeCab.Tagger("-Owakati -d %s" % self.mecab_dict)
XP.set_library(False, 0)
self.XP = XP
def __init__(self, parameter_dict):
"""
Initial Paramater Setting
:param parameter_dict: setting the a varity of paramater
If you use gpu, you setting the bellow paramater
XP.set_library(True, {your gpu id})
"""
self.parameter_dict = parameter_dict
self.source = parameter_dict["source"]
self.target = parameter_dict["target"]
self.test_source = parameter_dict["test_source"]
self.test_target = parameter_dict["test_target"]
self.vocab = parameter_dict["vocab"]
self.embed = parameter_dict["embed"]
self.hidden = parameter_dict["hidden"]
self.epoch = parameter_dict["epoch"]
self.minibatch = parameter_dict["minibatch"]
self.generation_limit = parameter_dict["generation_limit"]
self.word2vec = parameter_dict["word2vec"]
self.word2vecFlag = parameter_dict["word2vecFlag"]
self.model = parameter_dict["model"]
self.attention_dialogue = parameter_dict["attention_dialogue"]
XP.set_library(False, 0)
self.XP = XP
def __init__(self, parameter_dict):
"""
Initial Paramater Setting
:param parameter_dict: setting the a varity of paramater
If you use gpu, you setting the bellow paramater
XP.set_library(True, {your gpu id})
"""
self.parameter_dict = parameter_dict
self.source = parameter_dict["source"]
self.target = parameter_dict["target"]
self.test_source = parameter_dict["test_source"]
self.test_target = parameter_dict["test_target"]
self.vocab = parameter_dict["vocab"]
self.embed = parameter_dict["embed"]
self.hidden = parameter_dict["hidden"]
self.epoch = parameter_dict["epoch"]
self.minibatch = parameter_dict["minibatch"]
self.generation_limit = parameter_dict["generation_limit"]
self.word2vec = parameter_dict["word2vec"]
self.word2vecFlag = parameter_dict["word2vecFlag"]
self.model = parameter_dict["model"]
self.attention_dialogue = parameter_dict["attention_dialogue"]
XP.set_library(False, 0)
self.XP = XP
