FeedRef2022.py

# coding=utf-8
# Copyright 2020 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
"""Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition"""

import os

import json
import datasets


logger = datasets.logging.get_logger(__name__)


_CITATION = """\

"""

_DESCRIPTION = """\

"""

_URL = "https://huggingface.co/datasets/cynthiachan/feedref2022/resolve/main/FeedRef2022.zip"
_TRAINING_FILE = "train.json"
_DEV_FILE = "valid.json"
_TEST_FILE = "test.json"


class FeedRef2022Config(datasets.BuilderConfig):
    """BuilderConfig for FeedRef2022"""

    def __init__(self, **kwargs):
        """BuilderConfig for FeedRef2022.

        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(FeedRef2022Config, self).__init__(**kwargs)


class FeedRef2022(datasets.GeneratorBasedBuilder):
    """FeedRef2022 dataset."""

    BUILDER_CONFIGS = [
        FeedRef2022Config(name="FeedRef2022", version=datasets.Version("1.0.0"), description="FeedRef2022 dataset"),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "id": datasets.Value("string"),
                    "tokens": datasets.Sequence(datasets.Value("string")),
                    "ner_tags": datasets.Sequence(
                        datasets.features.ClassLabel(
                            names=[
                                "O",
                                "B-attackID",
                                "I-attackID",
                                "B-bitcoinAddr",
                                "I-bitcoinAddr",
                                "B-cve",
                                "I-cve",
                                "B-defenderThreat",
                                "I-defenderThreat",
                                "B-domain",
                                "I-domain",
                                "B-email",
                                "I-email",
                                "B-md5",
                                "I-md5",
                                "B-sha1",
                                "I-sha1",
                                "B-sha256",
                                "I-sha256",
                                "B-filepath",
                                "I-filepath",
                                "B-hostname",
                                "I-hostname",
                                "B-ipv4",
                                "I-ipv4",
                                "B-ipv6",
                                "I-ipv6",
                                "B-fingerprint",
                                "I-fingerprint",
                                "B-uri",
                                "I-uri",
                                "B-url",
                                "I-url",
                                "B-yara",
                                "I-yara"
                            ]
                        )
                    ),
                }
            ),
            # supervised_keys=None,
            # homepage="https://www.aclweb.org/anthology/W03-0419/",
            # citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        downloaded_file = dl_manager.download_and_extract(_URL)
        data_files = {
            "train": os.path.join(downloaded_file, _TRAINING_FILE),
            "dev": os.path.join(downloaded_file, _DEV_FILE),
            "test": os.path.join(downloaded_file, _TEST_FILE),
        }

        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["dev"]}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}),
        ]

    def _generate_examples(self, filepath):
        logger.info("⏳ Generating examples from = %s", filepath)
        id = 0
        with open(filepath, encoding="utf-8") as f:
            data = json.load(f)
            for sentence in data["data"]:
                yield id, {
                    "id": id,
                    "tokens": sentence["tokens"],
                    "ner_tags": sentence["ner_tags"]
                }
                id+=1