sat.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
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"""SAT dataset."""

import json

import datasets

# TODO
_CITATION = """\
"""

_DESCRIPTION = """\
SAT (Style Augmented Translation) dataset contains roughly 3.3 million English-Vietnamese pairs of texts.
"""

_HOMEPAGE = "https://github.com/vietai/sat"

# TODO
_LICENSE = "Unknown"

_URL = {
    "train": "https://storage.googleapis.com/vietai_public/best_vi_translation/v1/train.en-vi.json",
    "test": "https://storage.googleapis.com/vietai_public/best_vi_translation/v1/test.en-vi.json",
}


class Sat(datasets.GeneratorBasedBuilder):
    """SAT dataset."""

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features({"translation": datasets.features.Translation(languages=["en", "vi"])}),
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        data_path = dl_manager.download(_URL)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "data_path": data_path["train"],
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "data_path": data_path["test"],
                },
            ),
        ]

    def _generate_examples(self, data_path):
        with open(data_path, encoding="utf-8") as f:
            for key, line in enumerate(f):
                yield key, json.loads(line)