def load_data(self, debug=False): """Loads train/valid/test data and sentence encoding""" #num_supp_facts: not used (Strong supervised training) #note: word_embedding returned by load_babi is not used - instead we define it using TF's functions if self.config.train_mode: self.train_or_test_data, self.valid_data, _, self.config.max_words_per_question, self.config.max_sentences_per_input, \ self.config.max_words_per_sentence, self.config.num_supp_facts, self.config.vocab_size \ = babi_input.load_babi(self.config, split_sentences=True) else: self.train_or_test_data, _, self.config.max_words_per_question, self.config.max_sentences_per_input, \ self.config.max_words_per_sentence, self.config.num_supp_facts, self.config.vocab_size \ = babi_input.load_babi(self.config, split_sentences=True)
def load_data(self, debug=False): """Loads train/valid/test data and sentence encoding""" if self.config.train_mode: self.train, self.valid, self.word_embedding, self.max_q_len, self.max_input_len, self.max_sen_len, self.num_supporting_facts, self.vocab_size = babi_input.load_babi(self.config, split_sentences=True) else: self.test, self.word_embedding, self.max_q_len, self.max_input_len, self.max_sen_len, self.num_supporting_facts, self.vocab_size = babi_input.load_babi(self.config, split_sentences=True) self.encoding = _position_encoding(self.max_sen_len, self.config.embed_size)
def load_data(self): if self.config.train_mode: self.train, self.valid, self.word_embedding, self.max_q_len, self.max_sentences, self.max_sen_len, self.vocab_size = babi_input.load_babi( self.config, split_sentences=True) else: self.test, self.word_embedding, self.max_q_len, self.max_sentences, self.max_sen_len, self.vocab_size = babi_input.load_babi( self.config, split_sentences=True) self.encoding = position_encoding(self.max_sen_len, self.config.embed_size)
def load_data(self, debug=False): """Loads train/valid/test data and sentence encoding""" #In DMN_test, ... it changes config.mode if self.config.train_mode: self.train, self.valid, self.word_embedding, self.max_q_len, self.max_sentences, self.max_sen_len, self.vocab_size = babi_input.load_babi(self.config, split_sentences=True) else: self.test, self.word_embedding, self.max_q_len, self.max_sentences, self.max_sen_len, self.vocab_size = babi_input.load_babi(self.config, split_sentences=True) self.encoding = _position_encoding(self.max_sen_len, self.config.embed_size)