Create modern_haiku.py

modern_haiku.py

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+import datasets as ds
+
+import json
+
+_SUBSET_NAMES = ["all", "spring", "summer", "autumn", "winter", "none", "kigo"]
+
+_COMMON_FEATURES = {
+    "id": ds.Value("int64"),
+    "haiku": ds.Value("string"),
+    "author": ds.Value("string"),
+    "foreword": ds.Value("string"),
+    "source": ds.Value("string"),
+    "comment": ds.Value("string"),
+    "reviewer": ds.Value("string"),
+    "note": ds.Value("string"),
+}
+_KIGO_FEATURES = {
+    "id": ds.Value("int64"),
+    "word": ds.Value("string"),
+    "kana": ds.Value("string"),
+    "old_kana": ds.Value("string"),
+    "season": ds.Value("string"),
+    "subtitle": ds.Sequence(ds.Value("string")),
+}
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = ""
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = ""
+
+_FEATURES = {
+    "all": ds.Features(
+        {**_COMMON_FEATURES, "season": ds.Value("string"), "kigo": _KIGO_FEATURES}
+    ),
+    "spring": ds.Features({**_COMMON_FEATURES, "kigo": _KIGO_FEATURES}),
+    "summer": ds.Features({**_COMMON_FEATURES, "kigo": _KIGO_FEATURES}),
+    "autumn": ds.Features({**_COMMON_FEATURES, "kigo": _KIGO_FEATURES}),
+    "winter": ds.Features({**_COMMON_FEATURES, "kigo": _KIGO_FEATURES}),
+    "none": ds.Features(_COMMON_FEATURES),
+    "kigo": ds.Features(_KIGO_FEATURES),
+}
+
+_DATA_URL = "https://pub-6dee886ee0a5425c8fb25fe18f3acc73.r2.dev/public/datasets/modern_haiku/data.json"
+
+
+class ModernHaikuDataset(ds.GeneratorBasedBuilder):
+    VERSION = ds.Version("0.0.1")
+
+    BUILDER_CONFIGS = [ds.BuilderConfig(name=subset) for subset in _SUBSET_NAMES]
+    DEFAULT_CONFIG_NAME = "all"
+
+    def _info(self):
+        return ds.DatasetInfo(
+            description=_DESCRIPTION,
+            features=_FEATURES.get(self.config.name),
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download(_DATA_URL)
+        return [
+            ds.SplitGenerator(
+                name=ds.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dir,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, "r", encoding="utf-8") as f:
+            data: list[dict] = json.load(f)
+
+        key = 0
+
+        if self.config.name == "all":
+            for row in data:
+                yield key, row
+                key += 1
+
+        elif self.config.name == "none":
+            data = [row for row in data if row["season"] == self.config.name]
+            for row in data:
+                row.pop("season")
+                row.pop("kigo")
+
+                yield key, row
+                key += 1
+
+        elif self.config.name != "kigo":
+            data = [row for row in data if row["season"] == self.config.name]
+            for row in data:
+                row.pop("season")
+
+                yield key, row
+                key += 1
+
+        else:
+            all_kigo = {}
+            for row in data:
+                if row["kigo"] is None:
+                    continue
+                kigo = row["kigo"]
+                id = kigo["id"]
+                if all_kigo.get(id) is None:
+                    all_kigo[id] = kigo
+                else:
+                    continue
+
+            for id, kigo in all_kigo.items():
+                yield key, kigo
+                key += 1