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. | |
| """PsyQA dataset.""" | |
| import json | |
| import os | |
| import datasets | |
| _DESCRIPTION = """ FutureWarning | |
| """ | |
| _CITATION = """ null """ | |
| _URLs = { | |
| "train": "https://huggingface.co/datasets/siyangliu/PsyQA/resolve/main/train.json", | |
| "valid": "https://huggingface.co/datasets/siyangliu/PsyQA/resolve/main/valid.json", | |
| "test": "https://huggingface.co/datasets/siyangliu/PsyQA/resolve/main/test.json", | |
| "train_translated": "https://huggingface.co/datasets/siyangliu/PsyQA/resolve/main/train_translated.json", | |
| "valid_translated": "https://huggingface.co/datasets/siyangliu/PsyQA/resolve/main/valid_translated.json", | |
| "test_translated": "https://huggingface.co/datasets/siyangliu/PsyQA/resolve/main/test_translated.json" | |
| } | |
| _STRATEGY={"Approval and Reassurance": "[AR]", | |
| "Interpretation": "[IN]", | |
| "Self-disclosure": "[SELF]", | |
| "Direct Guidance": "[DG]", | |
| "Others": "[OT]", | |
| "Restatement": "[RES]", | |
| "Information": "[INFO]"} | |
| class PsyQA(datasets.GeneratorBasedBuilder): | |
| """PsyQA dataset.""" | |
| VERSION = datasets.Version("1.1.0") | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="wo strategy", | |
| description="", | |
| version=VERSION, | |
| ), | |
| datasets.BuilderConfig( | |
| name="w strategy", | |
| description="", | |
| version=VERSION, | |
| ), | |
| datasets.BuilderConfig( | |
| name="translated", | |
| description="", | |
| version=VERSION, | |
| ) | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "question": datasets.Value("string"), | |
| "questionID": datasets.Value("int16"), | |
| "description": datasets.Value("string"), | |
| "keywords": datasets.Value("string"), | |
| "answer": datasets.Value("string"), | |
| "has_label": datasets.Value("bool"), | |
| "reference":datasets.features.Sequence(datasets.Value("string")) | |
| # "labels_sequence":datasets.features.Sequence( | |
| # { | |
| # "start": datasets.Value("int16"), | |
| # "end": datasets.Value("int16"), | |
| # "type": datasets.Value("string"), | |
| # } | |
| # ), | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage="https://huggingface.co/datasets/siyangliu/PsyQA", | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| data_dir = dl_manager.download_and_extract(_URLs) | |
| if self.config.name != "translated": | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": data_dir["train"], | |
| "strategy": self.config.name == "w strategy" | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": data_dir["test"], | |
| "strategy": self.config.name == "w strategy" | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={ | |
| "filepath": data_dir["valid"], | |
| "strategy": self.config.name == "w strategy" | |
| }, | |
| ), | |
| ] | |
| else: | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": data_dir["train_translated"] | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": data_dir["test_translated"] | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={ | |
| "filepath": data_dir["valid_translated"] | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath, label_filepath=None, strategy=False): | |
| """Yields examples.""" | |
| with open(filepath, encoding="utf-8") as input_file: | |
| dataset = json.load(input_file) | |
| idx = 0 | |
| for meta_data in dataset: | |
| reference = [ans["answer_text"] for ans in meta_data["answers"]] | |
| for ans in meta_data["answers"]: | |
| if strategy and ans["labels_sequence"] is None: | |
| continue | |
| elif strategy and ans["labels_sequence"] is not None: | |
| pieces = [] | |
| for label in ans["labels_sequence"]: | |
| pieces.append(_STRATEGY[label["type"]]+ans["answer_text"][label["start"]:label["end"]]) | |
| ans_w_strategy = "".join(pieces) | |
| yield idx, {"question": meta_data["question"], "description": meta_data["description"], "keywords": meta_data["keywords"], "answer": ans_w_strategy, \ | |
| "questionID": meta_data["questionID"], "has_label": ans["has_label"], "reference": reference} | |
| else: | |
| yield idx, {"question": meta_data["question"], "description": meta_data["description"], "keywords": meta_data["keywords"], "answer": ans["answer_text"], \ | |
| "questionID": meta_data["questionID"], "has_label": ans["has_label"], "reference":reference} | |
| idx += 1 | |