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sampiran.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
+from nusacrowd.utils.constants import Tasks
+from nusacrowd.utils import schemas
+
+import datasets
+
+from nusacrowd.utils.configs import NusantaraConfig
+
+# TODO: Add BibTeX citation
+_CITATION = """\
+@inproceedings{siallagan2022sampiran,
+  title={Poetry Generation for Indonesian Pantun: Comparison Between SeqGAN and GPT-2},
+  author={Emmanuella Anggi Siallagan and Ika Alfina},
+  booktitle={Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information) Vol 1x No x February 2023 (Minor Revision)},
+  year={2023},
+}
+"""
+
+_DATASETNAME = "sampiran"
+
+
+_DESCRIPTION = """\
+Sampiran is a dataset for pantun generation. It consists of 7.8K Indonesian pantun, collected from various sources (online). 
+Pantun is a traditional Malay poem consisting of four lines: two lines of deliverance and two lines of message. 
+This dataset filtered the gathered Pantun to follow the general rules of Pantun; four lines with ABAB rhyme and eight to twelve syllables per line.
+"""
+
+_LANGUAGES = ["ind"]
+_LOCAL = False
+_HOMEPAGE = "https://github.com/ir-nlp-csui/sampiran"
+_LICENSE = "AGPL-3.0"
+
+_URLS = "https://raw.githubusercontent.com/ir-nlp-csui/sampiran/main/sampiran.txt"
+
+_SUPPORTED_TASKS = [Tasks.SELF_SUPERVISED_PRETRAINING]
+
+_SOURCE_VERSION = "1.0.0"
+
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class SampiranDataset(datasets.GeneratorBasedBuilder):
+    """Sampiran is a dataset for pantun generation. It consists of 7.8K Indonesian pantun,
+    collected from various sources (online)."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="sampiran_source",
+            version=SOURCE_VERSION,
+            description="sampiran source schema",
+            schema="source",
+            subset_id="sampiran",
+        ),
+        NusantaraConfig(
+            name="sampiran_nusantara_ssp",
+            version=NUSANTARA_VERSION,
+            description="sampiran Nusantara schema",
+            schema="nusantara_ssp",
+            subset_id="sampiran",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "sampiran_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "pantun": datasets.Value("string"),
+                }
+            )
+        elif self.config.schema == "nusantara_ssp":
+            # e.g. features = schemas.kb_features
+            # TODO: Choose your nusantara schema here
+            features = schemas.self_supervised_pretraining.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."""
+        filepath = Path(dl_manager.download(_URLS))
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": filepath},
+            ),
+        ]
+
+    def _read_data(self, filepath: Path) -> List[Dict]:
+        """Reads the data from the source file and returns a list of dicts."""
+
+    def _generate_examples(self, filepath: Path, split: str = None) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+        if self.config.schema != "source" and self.config.schema != "nusantara_ssp":
+            raise ValueError(f"Invalid config schema: {self.config.schema}")
+
+        # Read the file line by line
+
+        if self.config.name == "sampiran_source":
+            with open(filepath, encoding="utf-8") as f:
+                for id_, row in enumerate(f):
+                    ex = {
+                        "id": str(id_),
+                        "pantun": str(row).rstrip(),
+                    }
+                    yield id_, ex
+
+        elif self.config.name == "sampiran_nusantara_ssp":
+            with open(filepath, encoding="utf-8") as f:
+                for id_, row in enumerate(f):
+                    ex = {"id": str(id_), "text": str(row).rstrip()}
+                    yield id_, ex