KoPI-NLLB.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.
"""Cleaned Indonesian split of the KoPI corpus."""
import json
import glob
import gzip
from posixpath import split
import textwrap
import datasets
import zstandard as zstd
logger = datasets.logging.get_logger(__name__)

_CITATION = """
"""
_DESCRIPTION = """\
"""
_TYPE = ['raw','dedup','neardup']
_CONF_LANG = ['ace_Latn','ban_Latn','bjn_Latn','ind_Latn','jav_Latn','min_Latn','sun_Latn']
_CONFIGS = []
for j in _CONF_LANG:
    for m in _TYPE:
        _CONFIGS.append(j+'-'+m)
_ALL_CONFIG = ["all-raw", "all-dedup", "all-neardup"] + _CONFIGS
_HOMEPAGE = "https://huggingface.co/datasets/munggok/KoPI-NLLB"
_LICENSE = "ODC_C"
_BASE_URL = 'https://huggingface.co/datasets/munggok/KoPI-NLLB/resolve/main/{tipe}/{lang}.json.zst'

def kopi_nllb_constructor(nam):
    return KoPINLLBConfig(
            name=nam,
            version=datasets.Version("1.0.0"),
        )

class KoPINLLBConfig(datasets.BuilderConfig):
    """BuilderConfig for the Clean KoPI corpus."""
    def __init__(self, **kwargs):
        """BuilderConfig for Clean KoPI corpus.
        Args:
            **kwargs: keyword arguments forwarded to super.
        """
        super().__init__(**kwargs)
class KoPINLLB(datasets.GeneratorBasedBuilder):
    """KoPI corpus."""
    BUILDER_CONFIGS = [kopi_nllb_constructor(m) for m in _ALL_CONFIG ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "url": datasets.Value("string"),
                    "score": datasets.Value("float32"),
                    "source": datasets.Value("string"),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )
    def _split_generators(self, dl_manager):
        name = self.config.name.split("-")
        if name[0] == "all":
            train = [_BASE_URL.format(tipe=name[1],lang=m) for m in _CONF_LANG]
        else:
            train = [_BASE_URL.format(tipe=name[1],lang=name[0])]
        train_downloaded_files = dl_manager.download(train)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files})
        ]
    def _generate_examples(self, filepaths):
        """This function returns the examples in the raw (text) form by iterating on all the files."""
        id_ = 0
        for filepath in filepaths:
            logger.info(f"Generating examples from {filepath}")
            with zstd.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
                for line in f:
                    if line:
                        example = json.loads(line)
                        if line:
                            example = json.loads(line)
                            yield id_, {'text':example['text'],'url':example['url'],'source':example['source'],'score': float(example['score'])}
                            id_ += 1