Update parquet files

.gitattributes

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+default/jsnli-train.parquet filter=lfs diff=lfs merge=lfs -text

.github/workflows/ci.yaml

@@ -1,47 +0,0 @@
-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

@@ -1,26 +0,0 @@
-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

@@ -1,171 +0,0 @@
-# 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

@@ -1,33 +0,0 @@
----
-language:
-- ja
-
-license: 
-- cc-by-sa-4.0
-
-multilinguality:
-- monolingual
-
-task_categories:
-- text-classification
-
-task_ids:
-- natural-language-inference
-- multi-input-text-classification
-
-tags:
-- natural-language-inference
-- nli
-- jsnli
-
-datasets:
-- without-filtering
-- with-filtering
-
-metrics:
-- accuracy
----
-
-# 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)

default/jsnli-train.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:090e9a46e99de1f43a48e0a139b1dba6be1f74a401ada985744d3980ed74ec73
+size 44382398

jsnli.py

@@ -1,111 +0,0 @@
-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 = "with-filtering"  # type: ignore
-    BUILDER_CONFIG = [
-        ds.BuilderConfig(
-            name="with-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="without-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 "without-filtering" in self.config.name:
-            tng_path = train_wo_filtering_path
-        else:
-            # use `with-filtering` dataset as default setting
-            tng_path = train_w_filtering_path
-
-        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

@@ -1,23 +0,0 @@
-[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

@@ -1,35 +0,0 @@
-import datasets as ds
-import pytest
-
-
-@pytest.fixture
-def dataset_path() -> str:
-    return "jsnli.py"
-
-
-@pytest.mark.parametrize(
-    "dataset_name, expected_num_train,",
-    (
-        ("without-filtering", 548014),
-        ("with-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
-
-
-def test_load_dataset_default(
-    dataset_path: str, expected_num_train: int = 533005, expected_num_valid: int = 3916
-):
-
-    dataset = ds.load_dataset(path=dataset_path)
-    assert dataset["train"].num_rows == expected_num_train  # type: ignore
-    assert dataset["validation"].num_rows == expected_num_valid  # type: ignore