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udhr_lid.py

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+# coding=utf-8
+# Copyright 2022 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
+# limitations under the License.
+
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+import pandas as pd
+
+from seacrowd.utils import schemas
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import Licenses, Tasks
+
+_CITATION = r"""\
+@inproceedings{
+  kargaran2023glotlid,
+  title={{GlotLID}: Language Identification for Low-Resource Languages},
+  author={Kargaran, Amir Hossein and Imani, Ayyoob and Yvon, Fran{\c{c}}ois and Sch{\"u}tze, Hinrich},
+  booktitle={The 2023 Conference on Empirical Methods in Natural Language Processing},
+  year={2023},
+  url={https://openreview.net/forum?id=dl4e3EBz5j}
+}
+"""
+
+_LANGUAGES = [
+    "sun",
+    "ace",
+    "mad",
+    "lao",
+    "cfm",
+    "hnj",
+    "min",
+    "zlm",
+    "tha",
+    "blt",
+    "hni",
+    "jav",
+    "tdt",
+    "cnh",
+    "khm",
+    "ban",
+    "ind",
+    "mya",
+    "ccp",
+    "duu",
+    "tet",
+    "kkh",
+    "bug",
+    "vie",
+]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+_LOCAL = False
+
+_DATASETNAME = "udhr_lid"
+
+_DESCRIPTION = """\
+The UDHR-LID dataset is a refined version of the Universal Declaration of Human Rights, tailored for language identification tasks.
+It removes filler texts, repeated phrases, and inaccuracies from the original UDHR, focusing only on cleaned paragraphs.
+Each entry in the dataset is associated with a specific language, providing long, linguistically rich content.
+This dataset is particularly useful for non-parallel, language-specific text analysis in natural language processing.
+"""
+
+_HOMEPAGE = "https://huggingface.co/datasets/cis-lmu/udhr-lid"
+
+_LICENSE = Licenses.CC0_1_0.value
+
+_URL = "https://huggingface.co/datasets/cis-lmu/udhr-lid/raw/main/udhr-lid.csv"
+
+_SUPPORTED_TASKS = [Tasks.LANGUAGE_IDENTIFICATION]
+
+_SOURCE_VERSION = "1.0.0"
+
+_SEACROWD_VERSION = "2024.06.20"
+
+
+class UDHRLID(datasets.GeneratorBasedBuilder):
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
+
+    BUILDER_CONFIGS = [
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_source",
+            version=SOURCE_VERSION,
+            description=f"{_DATASETNAME} source schema",
+            schema="source",
+            subset_id=f"{_DATASETNAME}",
+        ),
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_seacrowd_text",
+            version=SEACROWD_VERSION,
+            description=f"{_DATASETNAME} SEACrowd Schema",
+            schema="seacrowd_text",
+            subset_id=f"{_DATASETNAME}",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "sentence": datasets.Value("string"),
+                    "iso639-3": datasets.Value("string"),
+                    "iso15924": datasets.Value("string"),
+                    "language": datasets.Value("string"),
+                }
+            )
+        elif self.config.schema == "seacrowd_text":
+            features = schemas.text_features(_LANGUAGES)
+
+        else:
+            raise NotImplementedError(f"Schema '{self.config.schema}' is not defined.")
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        """Returns SplitGenerators."""
+        data_path = dl_manager.download(_URL)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": data_path,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
+
+        datas = pd.read_csv(filepath)
+
+        for i, row in datas.iterrows():
+            if row["iso639-3"] in _LANGUAGES:
+                if self.config.schema == "source":
+                    yield i, {"id": str(i), "sentence": row["sentence"], "iso639-3": row["iso639-3"], "iso15924": row["iso15924"], "language": row["language"]}
+                elif self.config.schema == "seacrowd_text":
+                    yield i, {"id": str(i), "text": row["sentence"], "label": row["iso639-3"]}
+                else:
+                    raise ValueError(f"Invalid config: {self.config.name}")