nli_datasets.py

# 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.
import json

import datasets

logger = datasets.logging.get_logger(__name__)

_DESCRIPTION = """\
Data for NLI task annotated manually
"""

_BASE_URL = "https://huggingface.co./datasets/clarin-knext/nli_datasets/resolve/main/data/"

_DATASET_NAME = [
    "snli_pl",
    "snli_en",
    "wnli_pl",
    "wnli_en",
]

_URLS = {
    f"{dataset}_{lang}": f"{_BASE_URL}{dataset}_nli_{lang}.jsonl"
    for dataset, lang in (dataset_name.split('_') for dataset_name in _DATASET_NAME)
}


class NLIDatasetBuilderConfig(datasets.BuilderConfig):
    def __init__(
        self,
        data_url: str,
        name: str,
        **kwargs,
    ):
        super(NLIDatasetBuilderConfig, self).__init__(
            name=name,
            version=datasets.Version("1.0.0"),
            **kwargs,
        )

        self.name = name
        self.data_url = data_url
        if self.name not in _DATASET_NAME:
            raise ValueError(
                f"Config name `{self.name}` is not available. Enter one of: {_DATASET_NAME}"
            )


class NLIDataset(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        NLIDatasetBuilderConfig(
            name=dataset,
            data_url=_URLS[dataset],
            description=f"Dataset {dataset} with NLI annotation.",
        )
        for dataset in _DATASET_NAME
    ]

    DEFAULT_CONFIG_NAME = "wnli_en"

    def _info(self) -> datasets.DatasetInfo:
        features = {
            "id": datasets.Value("int32"),
            "sentence_1": datasets.Value("string"),
            "sentence_2": datasets.Value("string"),
            "label": datasets.Value("string"),
        }

        if self.config.name.startswith('snli'):
            features["origin_label"] = datasets.Value("string")

        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(features),
            supervised_keys=None,
            # license=_LICENSE,
            # citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        filepath = dl_manager.download_and_extract(self.config.data_url)

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": filepath,
                },
            ),
        ]

    def _generate_examples(self, filepath: str):
        key_iter = 0
        with open(filepath, encoding="utf-8") as f:
            for data in (json.loads(line) for line in f):
                yield key_iter, data
                key_iter += 1