Example #1
0
    def init_cfg_training(self, grammar=None):
        from utils.oracle.OracleCfg import OracleCfg
        oracle = OracleCfg(sequence_length=self.sequence_length,
                           cfg_grammar=grammar)
        self.set_oracle(oracle)
        self.oracle.generate_oracle()
        self.vocab_size = self.oracle.vocab_size + 1

        generator = Generator(num_vocabulary=self.vocab_size,
                              batch_size=self.batch_size,
                              emb_dim=self.emb_dim,
                              hidden_dim=self.hidden_dim,
                              sequence_length=self.sequence_length,
                              start_token=self.start_token)
        self.set_generator(generator)

        discriminator = Discriminator(sequence_length=self.sequence_length,
                                      num_classes=2,
                                      vocab_size=self.vocab_size,
                                      emd_dim=self.emb_dim,
                                      filter_sizes=self.filter_size,
                                      num_filters=self.num_filters,
                                      l2_reg_lambda=self.l2_reg_lambda)
        self.set_discriminator(discriminator)

        gen_dataloader = DataLoader(batch_size=self.batch_size,
                                    seq_length=self.sequence_length)
        oracle_dataloader = DataLoader(batch_size=self.batch_size,
                                       seq_length=self.sequence_length)
        dis_dataloader = DisDataloader(batch_size=self.batch_size,
                                       seq_length=self.sequence_length)
        self.set_data_loader(gen_loader=gen_dataloader,
                             dis_loader=dis_dataloader,
                             oracle_loader=oracle_dataloader)
        return oracle.wi_dict, oracle.iw_dict
Example #2
0
    def init_real_trainng(self, data_loc=None):
        from utils.text_process import text_precess, text_to_code
        from utils.text_process import get_tokenlized, get_word_list, get_dict
        if data_loc is None:
            data_loc = 'data/image_coco.txt'
        self.sequence_length, self.vocab_size = text_precess(data_loc)

        generator = Generator(num_vocabulary=self.vocab_size, batch_size=self.batch_size, emb_dim=self.emb_dim,
                              hidden_dim=self.hidden_dim, sequence_length=self.sequence_length,
                              start_token=self.start_token)
        self.set_generator(generator)

        discriminator = Discriminator(sequence_length=self.sequence_length, num_classes=2, vocab_size=self.vocab_size,
                                      emd_dim=self.emb_dim, filter_sizes=self.filter_size, num_filters=self.num_filters,
                                      l2_reg_lambda=self.l2_reg_lambda)
        self.set_discriminator(discriminator)

        gen_dataloader = DataLoader(batch_size=self.batch_size, seq_length=self.sequence_length)
        oracle_dataloader = None
        dis_dataloader = DisDataloader(batch_size=self.batch_size, seq_length=self.sequence_length)

        self.set_data_loader(gen_loader=gen_dataloader, dis_loader=dis_dataloader, oracle_loader=oracle_dataloader)
        tokens = get_tokenlized(data_loc)
        word_set = get_word_list(tokens)
        [word_index_dict, index_word_dict] = get_dict(word_set)
        with open(self.oracle_file, 'w') as outfile:
            outfile.write(text_to_code(tokens, word_index_dict, self.sequence_length))
        return word_index_dict, index_word_dict
Example #3
0
    def init_oracle_trainng(self, oracle=None):
        if oracle is None:
            oracle = OracleLstm(num_vocabulary=self.vocab_size, batch_size=self.batch_size, emb_dim=self.emb_dim,
                                hidden_dim=self.hidden_dim, sequence_length=self.sequence_length,
                                start_token=self.start_token)
        self.set_oracle(oracle)

        generator = Generator(num_vocabulary=self.vocab_size, batch_size=self.batch_size, emb_dim=self.emb_dim,
                              hidden_dim=self.hidden_dim, sequence_length=self.sequence_length,
                              start_token=self.start_token)
        self.set_generator(generator)

        discriminator = Discriminator(sequence_length=self.sequence_length, num_classes=2, vocab_size=self.vocab_size,
                                      emd_dim=self.emb_dim, filter_sizes=self.filter_size, num_filters=self.num_filters,
                                      l2_reg_lambda=self.l2_reg_lambda)
        self.set_discriminator(discriminator)

        gen_dataloader = DataLoader(batch_size=self.batch_size, seq_length=self.sequence_length)
        oracle_dataloader = DataLoader(batch_size=self.batch_size, seq_length=self.sequence_length)
        dis_dataloader = DisDataloader(batch_size=self.batch_size, seq_length=self.sequence_length)

        self.set_data_loader(gen_loader=gen_dataloader, dis_loader=dis_dataloader, oracle_loader=oracle_dataloader)