:sparkles: Add the builder scritp

janli.py

@@ -0,0 +1,75 @@
+import pandas as pd
+
+import datasets as ds
+
+_CITATION = """\
+@InProceedings{yanaka-EtAl:2021:blackbox,
+    author    = {Yanaka, Hitomi and Mineshima, Koji},
+    title     = {Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language Inference},
+    booktitle = {Proceedings of the 2021 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP2021)},
+    year      = {2021},
+}
+"""
+
+_DESCRIPTION = """\
+
+"""
+
+_HOMEPAGE = "https://github.com/verypluming/JaNLI"
+
+_LICENSE = "CC BY-SA 4.0"
+
+_DOWNLOAD_URL = "https://raw.githubusercontent.com/verypluming/JaNLI/main/janli.tsv"
+
+
+class JaNLIDataset(ds.GeneratorBasedBuilder):
+    VERSION = ds.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        ds.BuilderConfig(
+            name="default",
+            version=VERSION,
+            description=_DESCRIPTION,
+        ),
+    ]
+
+    def _info(self) -> ds.DatasetInfo:
+        features = ds.Features(
+            {
+                "id": ds.Value("int64"),
+                "sentence_A_Ja": ds.Value("string"),
+                "sentence_B_Ja": ds.Value("string"),
+                "entailment_label_Ja": ds.ClassLabel(names=["entailment", "non-entailment"]),
+                "heuristics": ds.Value("string"),
+                "number_of_NPs": ds.Value("int32"),
+                "semtag": ds.Value("string"),
+            }
+        )
+        return ds.DatasetInfo(
+            description=_DESCRIPTION,
+            citation=_CITATION,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            features=features,
+        )
+
+    def _split_generators(self, dl_manager: ds.DownloadManager):
+        data_path = dl_manager.download_and_extract(_DOWNLOAD_URL)
+        df: pd.DataFrame = pd.read_table(data_path, header=0, sep="\t", index_col=0)
+        df["id"] = df.index
+
+        return [
+            ds.SplitGenerator(
+                name=ds.Split.TRAIN,
+                gen_kwargs={"df": df[df["split"] == "train"]},
+            ),
+            ds.SplitGenerator(
+                name=ds.Split.TEST,
+                gen_kwargs={"df": df[df["split"] == "test"]},
+            ),
+        ]
+
+    def _generate_examples(self, df: pd.DataFrame):
+        df = df.drop("split", axis=1)
+        for i, row in enumerate(df.to_dict("records")):
+            yield i, row

pyproject.toml

@@ -0,0 +1,23 @@
+[tool.poetry]
+name = "datasets-janli"
+version = "0.1.0"
+description = ""
+authors = ["hppRC <hpp.ricecake@gmail.com>"]
+readme = "README.md"
+packages = []
+
+[tool.poetry.dependencies]
+python = "^3.8.1"
+datasets = "^2.11.0"
+
+
+[tool.poetry.group.dev.dependencies]
+black = "^22.12.0"
+isort = "^5.11.4"
+flake8 = "^6.0.0"
+mypy = "^0.991"
+pytest = "^7.2.0"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"