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lr_sum.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 typing import Dict, List, Tuple
+
+import datasets
+
+from seacrowd.utils import schemas
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import Licenses, Tasks
+
+_CITATION = """
+@inproceedings{palen-michel-lignos-2023-lr,
+  author    = {Palen-Michel, Chester and Lignos, Constantine},
+  title     = {LR - Sum: Summarization for Less-Resourced Languages},
+  booktitle = {Findings of the Association for Computational Linguistics: ACL 2023},
+  year      = {2023},
+  publisher = {Association for Computational Linguistics},
+  address   = {Toronto, Canada},
+  doi       = {10.18653/v1/2023.findings-acl.427},
+  pages     = {6829--6844},
+}
+"""
+
+_LOCAL = False
+_LANGUAGES = ["ind", "khm", "lao", "mya", "tha", "vie"]
+
+_DATASETNAME = "lr_sum"
+_DESCRIPTION = """
+LR-Sum is a news abstractive summarization dataset focused on low-resource languages. It contains human-written summaries
+for 39 languages and the data is based on the Multilingual Open Text corpus
+(ultimately derived from the Voice of America website).
+"""
+
+_HOMEPAGE = "https://huggingface.co/datasets/bltlab/lr-sum"
+_LICENSE = Licenses.CC_BY_4_0.value
+_URL = "https://huggingface.co/datasets/bltlab/lr-sum"
+
+_SUPPORTED_TASKS = [Tasks.SUMMARIZATION]
+_SOURCE_VERSION = "1.0.0"
+_SEACROWD_VERSION = "2024.06.20"
+
+
+class LRSumDataset(datasets.GeneratorBasedBuilder):
+    """Dataset of article-summary pairs for different low-resource languages."""
+
+    # Config to load individual datasets per language
+    BUILDER_CONFIGS = [
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_{lang}_source",
+            version=datasets.Version(_SOURCE_VERSION),
+            description=f"{_DATASETNAME} source schema for {lang} language",
+            schema="source",
+            subset_id=f"{_DATASETNAME}_{lang}",
+        )
+        for lang in _LANGUAGES
+    ] + [
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_{lang}_seacrowd_t2t",
+            version=datasets.Version(_SEACROWD_VERSION),
+            description=f"{_DATASETNAME} SEACrowd schema for {lang} language",
+            schema="seacrowd_t2t",
+            subset_id=f"{_DATASETNAME}_{lang}",
+        )
+        for lang in _LANGUAGES
+    ]
+
+    # Config to load all datasets
+    BUILDER_CONFIGS.extend(
+        [
+            SEACrowdConfig(
+                name=f"{_DATASETNAME}_source",
+                version=datasets.Version(_SOURCE_VERSION),
+                description=f"{_DATASETNAME} source schema for all languages",
+                schema="source",
+                subset_id=_DATASETNAME,
+            ),
+            SEACrowdConfig(
+                name=f"{_DATASETNAME}_seacrowd_t2t",
+                version=datasets.Version(_SEACROWD_VERSION),
+                description=f"{_DATASETNAME} SEACrowd schema for all languages",
+                schema="seacrowd_t2t",
+                subset_id=_DATASETNAME,
+            ),
+        ]
+    )
+
+    DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "url": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "summary": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                }
+            )
+        elif self.config.schema == "seacrowd_t2t":
+            features = schemas.text2text_features
+
+        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."""
+        # dl_manager not used since dataloader uses HF 'load_dataset'
+        return [
+            datasets.SplitGenerator(name=split, gen_kwargs={"split": split._name})
+            for split in (
+                datasets.Split.TRAIN,
+                datasets.Split.VALIDATION,
+                datasets.Split.TEST,
+            )
+        ]
+
+    def _load_hf_data_from_remote(self, lang: str, split: str) -> datasets.DatasetDict:
+        """Load dataset from HuggingFace."""
+        hf_remote_ref = "/".join(_URL.split("/")[-2:])
+        return datasets.load_dataset(hf_remote_ref, lang, split=split)
+
+    def _generate_examples(self, split: str) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+        lr_sum_datasets = []
+
+        lang = self.config.subset_id.split("_")[-1]
+        if lang in _LANGUAGES:
+            lr_sum_datasets.append(self._load_hf_data_from_remote(lang, split))
+        else:
+            for lang in _LANGUAGES:
+                lr_sum_datasets.append(self._load_hf_data_from_remote(lang, split))
+
+        index = 0
+        for lang_subset in lr_sum_datasets:
+            for row in lang_subset:
+                if self.config.schema == "source":
+                    example = row
+
+                elif self.config.schema == "seacrowd_t2t":
+                    example = {
+                        "id": str(index),
+                        "text_1": row["text"],
+                        "text_2": row["summary"],
+                        "text_1_name": "document",
+                        "text_2_name": "summary",
+                    }
+                yield index, example
+                index += 1