def read(self, data_path: str,
             positive_samples=False,
             *args, **kwargs) -> Dict[str, List[Tuple[List[str], int]]]:
        """Read the Ubuntu V2 dataset from csv files.

        Args:
            data_path: A path to a folder with dataset csv files.
            positive_samples: if `True`, only positive context-response pairs will be taken for train
        """

        data_path = expand_path(data_path)
        dataset = {'train': None, 'valid': None, 'test': None}
        train_fname = Path(data_path) / 'train.csv'
        valid_fname = Path(data_path) / 'valid.csv'
        test_fname = Path(data_path) / 'test.csv'
        self.positive_samples = positive_samples
        self.sen2int_vocab = {}
        self.classes_vocab_train = {}
        self.classes_vocab_valid = {}
        self.classes_vocab_test = {}
        dataset["train"] = self.preprocess_data_train(train_fname)
        dataset["valid"] = self.preprocess_data_validation(valid_fname)
        dataset["test"] = self.preprocess_data_validation(test_fname)
        return dataset
Read the Ubuntu V2 dataset from csv files.

        Args:
            data_path: A path to a folder with dataset csv files.
            positive_samples: if `True`, only positive context-response pairs will be taken for train
        
deeppavlov/dataset_readers/ubuntu_v2_reader.py