def train_mulit_model(self): """ Call the Dialogue Training for multi model """ trace('initializing ...') train_path = APP_ROOT + "/../twitter/data/" file_list = os.listdir(train_path) twitter_source_dict = {} twitter_replay_dict = {} for file in file_list: word_class = re.sub("_replay_twitter_data\.txt|_source_twitter_data\.txt", "", file.strip()) if word_class not in twitter_source_dict: twitter_source_dict.update({word_class: file.strip()}) if word_class not in twitter_replay_dict: twitter_replay_dict.update({word_class: file.strip()}) for word_class in twitter_source_dict.keys(): self.parameter_dict["source"] = train_path + word_class + "_source_twitter_data.txt" print(self.parameter_dict["source"]) self.parameter_dict["target"] = train_path + word_class + "_replay_twitter_data.txt" print(self.parameter_dict["target"]) self.parameter_dict["model"] = "ChainerDialogue_" + word_class encoderDecoderModel = EncoderDecoderModelAttention(self.parameter_dict) encoderDecoderModel.train()