| import os |
| from pathlib import Path |
| from typing import Dict, List, Tuple |
|
|
| import datasets |
|
|
| from seacrowd.utils.configs import SEACrowdConfig |
| from seacrowd.utils.constants import Tasks |
| from seacrowd.utils import schemas |
| import pandas as pd |
|
|
| _CITATION = """\ |
| @inproceedings{wongso2021causal, |
| title={Causal and masked language modeling of Javanese language using transformer-based architectures}, |
| author={Wongso, Wilson and Setiawan, David Samuel and Suhartono, Derwin}, |
| booktitle={2021 International Conference on Advanced Computer Science and Information Systems (ICACSIS)}, |
| pages={1--7}, |
| year={2021}, |
| organization={IEEE} |
| } |
| """ |
|
|
| _DATASETNAME = "imdb_jv" |
|
|
| _DESCRIPTION = """\ |
| Javanese Imdb Movie Reviews Dataset is a Javanese version of the IMDb Movie Reviews dataset by translating the original English dataset to Javanese. |
| """ |
|
|
| _HOMEPAGE = "https://huggingface.co/datasets/w11wo/imdb-javanese" |
|
|
| _LANGUAGES = ["ind"] |
| _LOCAL = False |
|
|
| _LICENSE = "Unknown" |
|
|
| _URLS = { |
| _DATASETNAME: "https://huggingface.co/datasets/w11wo/imdb-javanese/resolve/main/javanese_imdb_csv.zip", |
| } |
|
|
| _SUPPORTED_TASKS = [Tasks.SENTIMENT_ANALYSIS] |
|
|
| _SOURCE_VERSION = "1.0.0" |
|
|
| _SEACROWD_VERSION = "2024.06.20" |
|
|
| class IMDbJv(datasets.GeneratorBasedBuilder): |
| """Javanese Imdb Movie Reviews Dataset is a Javanese version of the IMDb Movie Reviews dataset by translating the original English dataset to Javanese.""" |
|
|
| SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) |
| SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION) |
|
|
| BUILDER_CONFIGS = [ |
| SEACrowdConfig( |
| name="imdb_jv_source", |
| version=datasets.Version(_SOURCE_VERSION), |
| description="imdb_jv source schema", |
| schema="source", |
| subset_id="imdb_jv", |
| ), |
| SEACrowdConfig( |
| name="imdb_jv_seacrowd_text", |
| version=datasets.Version(_SEACROWD_VERSION), |
| description="imdb_jv Nusantara schema", |
| schema="seacrowd_text", |
| subset_id="imdb_jv", |
| ), |
| ] |
|
|
| DEFAULT_CONFIG_NAME = "imdb_jv_source" |
|
|
| def _info(self) -> datasets.DatasetInfo: |
| if self.config.schema == "source": |
| features = datasets.Features( |
| { |
| "id": datasets.Value("string"), |
| "text": datasets.Value("string"), |
| "label": datasets.Value("string") |
| } |
| ) |
| elif self.config.schema == "seacrowd_text": |
| features = schemas.text_features(['1', '0', '-1']) |
|
|
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=features, |
| homepage=_HOMEPAGE, |
| license=_LICENSE, |
| citation=_CITATION, |
| ) |
|
|
|
|
| def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
| data_dir = Path(dl_manager.download_and_extract(_URLS[_DATASETNAME])) |
|
|
| data_files = { |
| "train": "javanese_imdb_train.csv", |
| "unsupervised": "javanese_imdb_unsup.csv", |
| "test": "javanese_imdb_test.csv", |
| } |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
|
|
| gen_kwargs={ |
| "filepath": os.path.join(data_dir, data_files["train"]), |
| "split": "train", |
| }, |
| ), |
| datasets.SplitGenerator( |
| name="unsupervised", |
| gen_kwargs={ |
| "filepath": os.path.join(data_dir, data_files["unsupervised"]), |
| "split": "unsupervised", |
| }, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.TEST, |
| gen_kwargs={ |
| "filepath": os.path.join(data_dir, data_files["test"]), |
| "split": "test", |
| }, |
| ), |
| ] |
|
|
| def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]: |
| if self.config.schema == "source": |
| data = pd.read_csv(filepath) |
| length = len(data['label']) |
| for id in range(length): |
| ex = { |
| "id": str(id), |
| "text": data['text'][id], |
| "label": data['label'][id], |
| } |
| yield id, ex |
|
|
| elif self.config.schema == "seacrowd_text": |
| data = pd.read_csv(filepath) |
| length = len(data['label']) |
| for id in range(length): |
| ex = { |
| "id": str(id), |
| "text": data['text'][id], |
| "label": data['label'][id], |
| } |
| yield id, ex |
| else: |
| raise ValueError(f"Invalid config: {self.config.name}") |
|
|
