lsat_qa.py

# 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.
"""Covid Dialog dataset in English and Chinese"""


import copy
import os
import re
import textwrap
import json

import datasets


# BibTeX citation
_CITATION = """
"""

# Official description of the dataset
_DESCRIPTION = textwrap.dedent(
    """
    """
)

# Link to an official homepage for the dataset here
_HOMEPAGE = ""

_LICENSE = ""


import datasets
import os
import json

names = ["all", "assignment", "grouping", "miscellaneous", "ordering"]

class LsatQA(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIGS = [datasets.BuilderConfig(name=name, version=datasets.Version("1.0.0"), description=_DESCRIPTION) for name in names]

    def _info(self):
        features = datasets.Features(
            {
                "passage": datasets.Value("string"),
                "question": datasets.Value("string"),
                "references": datasets.Sequence(datasets.Value("string")),
                "gold_index": datasets.Value("int64"),
            }
        )
        return datasets.DatasetInfo(
            description=f"LSAT QA dataset, as preprocessed and shuffled in HELM",
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        test = dl_manager.download(os.path.join(self.config.name, "test.jsonl"))
        train = dl_manager.download(os.path.join(self.config.name, "train.jsonl"))
        val = dl_manager.download(os.path.join(self.config.name, "valid.jsonl"))
        
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"file": train},
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={"file": val},
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={"file": test},
            ),
        ]

    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
    def _generate_examples(self, file):
        with open(file, encoding="utf-8") as f:
            for ix, line in enumerate(f):
                yield ix, json.loads(line)