92849315a08ac89243ef2613e28ff56efecd21cb,python/mead/tasks.py,EncoderDecoderTask,initialize,#EncoderDecoderTask#Any#,528

Before Change

        embeddings = read_config_file_or_json(embeddings, "embeddings")
        embeddings_set = index_by_label(embeddings)
        self.dataset = DataDownloader(self.dataset, self.data_download_cache, True).download()
        print("[train file]: {}\n[valid file]: {}\n[test file]: {}\n[vocab file]: {}".format(self.dataset["train_file"], self.dataset["valid_file"], self.dataset["test_file"], self.dataset.get("vocab_file","None")))
        vocab_file = self.dataset.get("vocab_file")
        if vocab_file is not None:
            vocab1, vocab2 = self.reader.build_vocabs([vocab_file], min_f=Task._get_min_f(self.config_params))
        else:

After Change

        embeddings = read_config_file_or_json(embeddings, "embeddings")
        embeddings_set = index_by_label(embeddings)
        self.dataset = DataDownloader(self.dataset, self.data_download_cache, True).download()
        print_dataset_info(self.dataset)
        vocab1, vocab2 = self.reader.build_vocabs(
            [self.dataset["train_file"], self.dataset["valid_file"], self.dataset["test_file"]],
            min_f=Task._get_min_f(self.config_params),
            vocab_file=self.dataset.get("vocab_file")

Instances