Initialize (#1)

* add python files

* add poetry files

* add settings for CI

* add .gitignore

* add README.md

* update CI

* add CI settings

.github/workflows/ci.yaml

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+name: CI
+
+on:
+  push:
+    branches: [main]
+    paths-ignore:
+      - 'README.md'
+  pull_request:
+    branches: [main]
+    paths-ignore:
+      - 'README.md'
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.8', '3.9', '3.10']
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: |
+          pip install -U pip setuptools wheel poetry
+          poetry install
+      - name: Format
+        run: |
+          poetry run black --check .
+      - name: Lint
+        run: |
+          poetry run flake8 . --ignore=E501,W503,E203
+      - name: Type check
+        run: |
+          poetry run mypy . \
+            --ignore-missing-imports \
+            --no-strict-optional \
+            --no-site-packages \
+            --cache-dir=/dev/null
+            
+      - name: Run tests
+        run: |
+          poetry run pytest --color=yes -rf

.github/workflows/push_to_hub.yaml

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+name: Sync to Hugging Face Hub
+
+on:
+  workflow_run:
+    workflows:
+      - CI
+    branches:
+      - main
+    types: 
+      - completed
+
+jobs:
+  push_to_hub:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v2
+        
+      - name: Push to Huggingface hub
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_USERNAME: ${{ secrets.HF_USERNAME }}
+        run: |
+          git fetch --unshallow
+          git push --force https://${HF_USERNAME}:${HF_TOKEN}@huggingface.co/datasets/${HF_USERNAME}/jsnli main

.gitignore

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+# Created by https://www.toptal.com/developers/gitignore/api/python
+# Edit at https://www.toptal.com/developers/gitignore?templates=python
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+### Python Patch ###
+# Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration
+poetry.toml
+
+
+# End of https://www.toptal.com/developers/gitignore/api/python

README.md

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+# Dataset Card for JSNLI
+
+[![CI](https://github.com/shunk031/huggingface-datasets_jsnli/actions/workflows/ci.yaml/badge.svg)](https://github.com/shunk031/huggingface-datasets_jsnli/actions/workflows/ci.yaml)

jsnli.py

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+import logging
+import os
+
+import datasets as ds
+
+logger = logging.getLogger(__name__)
+
+_CITATION = """\
+- 吉越 卓見, 河原 大輔, 黒橋 禎夫: 機械翻訳を用いた自然言語推論データセットの多言語化, 第244回自然言語処理研究会, (2020.7.3).
+- Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015. A large annotated corpus for learning natural language inference. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP).
+- Peter Young, Alice Lai, Micah Hodosh, and Julia Hockenmaier. "From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions." Transactions of the Association for Computational Linguistics 2 (2014): 67-78.
+"""
+
+_DESCRIPTION = """\
+== 日本語SNLI(JSNLI)データセット ==
+
+SNLI コーパスを日本語に翻訳した自然言語推論データセット
+学習データは元データを翻訳し、計算機によるフィルタリングによって作成
+評価データは日本語として意味が通るか、翻訳後のラベルが元のラベルと一致しているかどうかの2段階のクラウドソーシングによりデータをフィルタリング
+"""
+
+_HOMEPAGE = "https://nlp.ist.i.kyoto-u.ac.jp/?%E6%97%A5%E6%9C%AC%E8%AA%9ESNLI%28JSNLI%29%E3%83%87%E3%83%BC%E3%82%BF%E3%82%BB%E3%83%83%E3%83%88"
+
+_LICENSE = """\
+CC BY-SA 4.0
+"""
+
+_URL = "https://nlp.ist.i.kyoto-u.ac.jp/DLcounter/lime.cgi?down=https://nlp.ist.i.kyoto-u.ac.jp/nl-resource/JSNLI/jsnli_1.1.zip&name=JSNLI.zip"
+
+
+class JSNLIDataset(ds.GeneratorBasedBuilder):
+    VERSION = ds.Version("1.1.0")  # type: ignore
+    DEFAULT_CONFIG_NAME: str = "w_filtering"  # type: ignore
+    BUILDER_CONFIG = [
+        ds.BuilderConfig(
+            name="w_filtering",
+            version=VERSION,  # type: ignore
+            description="SNLIの学習データに機械翻訳を適用した後、BLEUスコアの閾値0.1でフィルタリングを施したもの。BERTにこの学習データを学習させることにより、93.0%の精度を記録した。(533,005ペア)",
+        ),
+        ds.BuilderConfig(
+            name="wo_filtering",
+            version=VERSION,  # type: ignore
+            description="SNLIの学習データに機械翻訳を適用したもの。フィルタリングは行っていない。(548,014ペア)",
+        ),
+    ]
+
+    def _info(self) -> ds.DatasetInfo:
+        features = ds.Features(
+            {
+                "label": ds.Value("string"),
+                "premise": ds.Value("string"),
+                "hypothesis": ds.Value("string"),
+            }
+        )
+        return ds.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: ds.DownloadManager):
+        jsnli_base_dir = dl_manager.download_and_extract(_URL)
+        jsnli_dir = os.path.join(
+            jsnli_base_dir, f"jsnli_{self.VERSION.major}.{self.VERSION.minor}"  # type: ignore
+        )
+
+        train_w_filtering_path = os.path.join(jsnli_dir, "train_w_filtering.tsv")
+        train_wo_filtering_path = os.path.join(jsnli_dir, "train_wo_filtering.tsv")
+
+        dev_path = os.path.join(jsnli_dir, "dev.tsv")
+        if "w_filtering" in self.config.name:
+            tng_path = train_w_filtering_path
+        elif "wo_filtering" in self.config.name:
+            tng_path = train_wo_filtering_path
+        else:
+            raise ValueError(f"Invalid config name: {self.config.name}")
+
+        tng_gen_kwargs = {
+            "tsv_path": tng_path,
+        }
+        val_gen_kwargs = {
+            "tsv_path": dev_path,
+        }
+
+        return [
+            ds.SplitGenerator(
+                name=ds.Split.TRAIN,  # type: ignore
+                gen_kwargs=tng_gen_kwargs,  # type: ignore
+            ),
+            ds.SplitGenerator(
+                name=ds.Split.VALIDATION,  # type: ignore
+                gen_kwargs=val_gen_kwargs,  # type: ignore
+            ),
+        ]
+
+    def _generate_examples(  # type: ignore
+        self,
+        tsv_path: str,
+    ):
+        with open(tsv_path, "r") as rf:
+            for sentence_id, line in enumerate(rf):
+                label, premise, hypothesis = line.replace("\n", "").split("\t")
+
+                example_dict = {
+                    "label": label,
+                    "premise": premise,
+                    "hypothesis": hypothesis,
+                }
+                yield sentence_id, example_dict

pyproject.toml

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+[tool.poetry]
+name = "huggingface-datasets-jsnli"
+version = "0.1.0"
+description = ""
+authors = ["Shunsuke KITADA <[email protected]>"]
+readme = "README.md"
+packages = []
+
+[tool.poetry.dependencies]
+python = ">=3.8.1,<4.0"
+datasets = "^2.7.1"
+
+
+[tool.poetry.group.dev.dependencies]
+black = "^22.10.0"
+isort = "^5.10.1"
+flake8 = "^6.0.0"
+mypy = "^0.991"
+pytest = "^7.2.0"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

tests/jsnli_test.py

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+import datasets as ds
+import pytest
+
+
+@pytest.fixture
+def dataset_path() -> str:
+    return "jsnli.py"
+
+
+@pytest.mark.parametrize(
+    "dataset_name, expected_num_train,",
+    (
+        ("wo_filtering", 548014),
+        ("w_filtering", 533005),
+    ),
+)
+def test_load_dataset(
+    dataset_path: str,
+    dataset_name: str,
+    expected_num_train: int,
+    expected_num_valid: int = 3916,
+):
+    dataset = ds.load_dataset(path=dataset_path, name=dataset_name)
+
+    assert dataset["train"].num_rows == expected_num_train  # type: ignore
+    assert dataset["validation"].num_rows == expected_num_valid  # type: ignore