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indocollex.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 itertools import chain
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import Tasks
+
+_CITATION = """\
+@inproceedings{wibowo-etal-2021-indocollex,
+    title = "{I}ndo{C}ollex: A Testbed for Morphological Transformation of {I}ndonesian Word Colloquialism",
+    author = {Wibowo, Haryo Akbarianto  and Nityasya, Made Nindyatama  and Aky{\"u}rek, Afra Feyza  and Fitriany, Suci  and Aji, Alham Fikri  and Prasojo, Radityo Eko  and Wijaya, Derry Tanti},
+    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
+    month = aug,
+    year = "2021",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2021.findings-acl.280",
+    doi = "10.18653/v1/2021.findings-acl.280",
+    pages = "3170--3183",
+}"""
+
+_LANGUAGES = ["ind"]
+_LOCAL = False
+
+_DATASETNAME = "indocollex"
+
+_DESCRIPTION = """\
+IndoCollex: A Testbed for Morphological Transformation of Indonesian Colloquial Words
+"""
+
+_HOMEPAGE = "https://github.com/haryoa/indo-collex"
+
+_LICENSE = "CC BY-SA 4.0"
+
+_URLS = {
+    _DATASETNAME: {
+        "train": "https://github.com/haryoa/indo-collex/raw/main/data/full.csv",
+    },
+    f"{_DATASETNAME}_f2i": {
+        "train": "https://github.com/haryoa/indo-collex/raw/main/data/formal_to_informal/train.csv",
+        "dev": "https://github.com/haryoa/indo-collex/raw/main/data/formal_to_informal/dev.csv",
+        "test": "https://github.com/haryoa/indo-collex/raw/main/data/formal_to_informal/test.csv",
+    },
+    f"{_DATASETNAME}_i2f": {
+        "train": "https://github.com/haryoa/indo-collex/raw/main/data/informal_to_formal/train.csv",
+        "dev": "https://github.com/haryoa/indo-collex/raw/main/data/informal_to_formal/dev.csv",
+        "test": "https://github.com/haryoa/indo-collex/raw/main/data/informal_to_formal/test.csv",
+    },
+}
+
+_SUPPORTED_TASKS = [Tasks.MORPHOLOGICAL_INFLECTION]
+
+_SOURCE_VERSION = "1.0.0"
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class NewDataset(datasets.GeneratorBasedBuilder):
+    """IndoCollex: A Testbed for Morphological Transformation of Indonesian Colloquial Words"""
+
+    label_classes = ["acronym", "affixation", "disemvoweling", "rev", "shorten", "sound-alter", "space-dash"]
+
+    BUILDER_CONFIGS = list(
+        chain(
+            *[
+                [
+                    NusantaraConfig(
+                        name=f"{_DATASETNAME}{suffix}_source",
+                        version=datasets.Version(_SOURCE_VERSION),
+                        description=f"{_DATASETNAME} source schema",
+                        schema="source",
+                        subset_id=f"{_DATASETNAME}{suffix}",
+                    ),
+                    NusantaraConfig(
+                        name=f"{_DATASETNAME}{suffix}_nusantara_pairs_multi",
+                        version=datasets.Version(_NUSANTARA_VERSION),
+                        description=f"{_DATASETNAME} Nusantara schema",
+                        schema="nusantara_pairs_multi",
+                        subset_id=f"{_DATASETNAME}{suffix}",
+                    ),
+                ]
+                for suffix in ["", "_f2i", "_i2f"]
+            ]
+        )
+    )
+
+    DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "no": datasets.Value("string"),
+                    "transformed": datasets.Value("string"),
+                    "original-for": datasets.Value("string"),
+                    "transformation": datasets.Value("string"),
+                }
+            )
+
+        elif self.config.schema == "nusantara_pairs_multi":
+            features = schemas.pairs_multi_features(self.label_classes)
+
+        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."""
+
+        urls = _URLS[self.config.subset_id]
+        data_paths = dl_manager.download(urls)
+
+        ret = [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": data_paths["train"]},
+            )
+        ]
+
+        if len(data_paths) > 1:
+            ret.extend(
+                [
+                    datasets.SplitGenerator(
+                        name=datasets.Split.TEST,
+                        gen_kwargs={"filepath": data_paths["test"]},
+                    ),
+                    datasets.SplitGenerator(
+                        name=datasets.Split.VALIDATION,
+                        gen_kwargs={"filepath": data_paths["dev"]},
+                    ),
+                ]
+            )
+
+        return ret
+
+    def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+
+        with open(filepath, "r", encoding="utf8") as f:
+            dataset = list(map(lambda l: l.rstrip("\r\n").split(","), f))
+
+        _assert = set(map(len, dataset))
+        if _assert != {4}:
+            raise AssertionError(f"Expecting exactly 4 fields (no, transformed, base, label), but found: {_assert}")
+
+        _assert = dataset[0]
+        source_columns = ["no", "transformed", "original-for", "transformation"]
+        if _assert != source_columns:
+            raise AssertionError(f"The expected header is not found. {_assert}")
+
+        dataset = dataset[1:]
+
+        if self.config.schema == "source":
+            for key, ex in enumerate(dataset):
+                yield key, dict(zip(source_columns, ex))
+
+        elif self.config.schema == "nusantara_pairs_multi":
+            for key, ex in enumerate(dataset):
+                yield key, {
+                    "id": str(key),
+                    "text_1": ex[2],
+                    "text_2": ex[1],
+                    "label": [ex[3]],
+                }