Datasets:
ArXiv:
License:
| # coding=utf-8 | |
| # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
| # | |
| # 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. | |
| """Demo for pretrain""" | |
| import os | |
| import json | |
| import datasets | |
| _CITATION = """\ | |
| """ | |
| _DESCRIPTION = """\ | |
| """ | |
| _LICENSE = "apache-license-2.0" | |
| _HOMEPAGE = "https://github.com/IDEA-CCNL/Fengshenbang-LM" | |
| class Config(datasets.BuilderConfig): | |
| """BuilderConfig for Demo""" | |
| def __init__(self, **kwargs): | |
| super().__init__(**kwargs) | |
| """ | |
| Args: | |
| **kwargs: keyword arguments forwarded to super. | |
| """ | |
| class PretrainCorpusDemo(datasets.GeneratorBasedBuilder): | |
| VERSION = datasets.Version("1.0.0") | |
| BUILDER_CONFIG_CLASS = Config | |
| BUILDER_CONFIGS = [ | |
| Config(description=_DESCRIPTION) | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features({ | |
| "text": datasets.Value("string"), | |
| }), | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| license=_LICENSE | |
| ) | |
| def _split_generators(self, dl_manager): | |
| files = { | |
| "test": os.path.join("data", f"train.json"), | |
| "validation": os.path.join("data", f"train.json"), | |
| "train": os.path.join("data", f"train.json"), | |
| } | |
| data_dir = dl_manager.download_and_extract(files) | |
| output = [] | |
| test = datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": data_dir["test"] | |
| } | |
| ) | |
| output.append(test) | |
| # if os.path.exists(data_dir["validation"]): | |
| valid = datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={ | |
| "filepath": data_dir["validation"] | |
| } | |
| ) | |
| output.append(valid) | |
| train = datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": data_dir["train"] | |
| } | |
| ) | |
| output.append(train) | |
| return output | |
| def _generate_examples(self, filepath): | |
| """Yields examples.""" | |
| with open(filepath, encoding="utf-8") as f: | |
| lines = f.readlines() | |
| for id_, line in enumerate(lines): | |
| data = json.loads(line) | |
| s = { | |
| 'text': data['text'], | |
| } | |
| yield id_, s | |