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| # coding=utf-8 | |
| # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. | |
| # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # Lint as: python3 | |
| import json | |
| import os | |
| import datasets | |
| from datasets.tasks import QuestionAnsweringExtractive | |
| logger = datasets.logging.get_logger(__name__) | |
| _DESCRIPTION = """\ | |
| Duconv is a chinese conversation \ | |
| dataset, designed to evaluate the dialogue models. | |
| """ | |
| _URL = "https://bj.bcebos.com/paddlenlp/datasets/DuConv.zip" | |
| class DuconvConfig(datasets.BuilderConfig): | |
| """BuilderConfig for Duconv.""" | |
| def __init__(self, **kwargs): | |
| """BuilderConfig for Duconv. | |
| Args: | |
| **kwargs: keyword arguments forwarded to super. | |
| """ | |
| super(DuconvConfig, self).__init__(**kwargs) | |
| class Duconv(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [ | |
| DuconvConfig( | |
| name="DuConv", | |
| version=datasets.Version("1.0.0", ""), | |
| description=_DESCRIPTION, | |
| ), | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features({ | |
| "id": | |
| datasets.Value("string"), | |
| "goal": | |
| datasets.Sequence(datasets.Sequence(datasets.Value("string"))), | |
| "knowledge": | |
| datasets.Sequence(datasets.Sequence(datasets.Value("string"))), | |
| "conversation": | |
| datasets.Sequence(datasets.Value("string")), | |
| "history": | |
| datasets.Sequence(datasets.Value("string")), | |
| "response": | |
| datasets.Value("string"), | |
| }), | |
| # No default supervised_keys (as we have to pass both question | |
| # and context as input). | |
| supervised_keys=None, | |
| homepage="https://arxiv.org/pdf/1906.05572.pdf", | |
| ) | |
| def _split_generators(self, dl_manager): | |
| dl_dir = dl_manager.download_and_extract(_URL) | |
| return [ | |
| datasets.SplitGenerator(name="train", | |
| gen_kwargs={ | |
| "filepath": | |
| os.path.join(dl_dir, 'DuConv', | |
| 'train.txt'), | |
| }), | |
| datasets.SplitGenerator(name="dev", | |
| gen_kwargs={ | |
| "filepath": | |
| os.path.join(dl_dir, 'DuConv', | |
| 'dev.txt'), | |
| }), | |
| datasets.SplitGenerator(name="test_1", | |
| gen_kwargs={ | |
| "filepath": | |
| os.path.join(dl_dir, 'DuConv', | |
| 'test_1.txt'), | |
| }), | |
| datasets.SplitGenerator(name="test_2", | |
| gen_kwargs={ | |
| "filepath": | |
| os.path.join(dl_dir, 'DuConv', | |
| 'test_2.txt'), | |
| }), | |
| ] | |
| def _generate_examples(self, filepath): | |
| """This function returns the examples in the raw (text) form.""" | |
| logger.info("generating examples from = %s", filepath) | |
| key = 0 | |
| with open(filepath, 'r', encoding="utf-8") as fin: | |
| for line in fin: | |
| duconv = json.loads(line) | |
| goal = duconv["goal"] if "goal" in duconv.keys() else [[]] | |
| knowledge = duconv["knowledge"] if "knowledge" in duconv.keys( | |
| ) else [[]] | |
| conversation = duconv[ | |
| "conversation"] if "conversation" in duconv.keys() else [] | |
| history = duconv["history"] if "history" in duconv.keys( | |
| ) else [] | |
| response = duconv["response"] if "response" in duconv.keys( | |
| ) else "" | |
| yield key, { | |
| "id": str(key), | |
| "goal": goal, | |
| "knowledge": knowledge, | |
| "conversation": conversation, | |
| "history": history, | |
| "response": response, | |
| } | |
| key += 1 | |