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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.
"""
This template serves as a starting point for contributing a dataset to the SEACrowd Datahub repo.
Full documentation on writing dataset loading scripts can be found here:
https://huggingface.co/docs/datasets/add_dataset.html
To create a dataset loading script you will create a class and implement 3 methods:
* `_info`: Establishes the schema for the dataset, and returns a datasets.DatasetInfo object.
* `_split_generators`: Downloads and extracts data for each split (e.g. train/val/test) or associate local data with each split.
* `_generate_examples`: Creates examples from data on disk that conform to each schema defined in `_info`.
"""
import json
import os
from pathlib import Path
from typing import Dict, List, Tuple
import datasets
from seacrowd.utils import schemas
from seacrowd.utils.configs import SEACrowdConfig
from seacrowd.utils.constants import (DEFAULT_SEACROWD_VIEW_NAME,
DEFAULT_SOURCE_VIEW_NAME, Tasks)
_CITATION = """\
@misc{MALINDO-parallel,
title = "MALINDO-parallel",
howpublished = "https://github.com/matbahasa/MALINDO_Parallel/blob/master/README.md",
note = "Accessed: 2023-01-27",
}
"""
_DATASETNAME = "malindo_parallel"
_DESCRIPTION = """\
Teks ini adalah skrip video untuk Kampus Terbuka Universiti Bahasa Asing Tokyo pada tahun 2020. Tersedia parallel sentences dalam Bahasa Melayu/Indonesia dan Bahasa Jepang
"""
_HOMEPAGE = "https://github.com/matbahasa/MALINDO_Parallel/tree/master/OpenCampusTUFS"
_LANGUAGES = ["zlm", "jpn"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
_LICENSE = "Creative Commons Attribution 4.0 (cc-by-4.0)"
_LOCAL = False
_URLS = {
_DATASETNAME: "https://raw.githubusercontent.com/matbahasa/MALINDO_Parallel/master/OpenCampusTUFS/OCTUFS2020.txt",
}
_SUPPORTED_TASKS = [Tasks.MACHINE_TRANSLATION] # example: [Tasks.TRANSLATION, Tasks.NAMED_ENTITY_RECOGNITION, Tasks.RELATION_EXTRACTION]
_SOURCE_VERSION = "1.0.0"
_SEACROWD_VERSION = "2024.06.20"
class MalindoParallelDataset(datasets.GeneratorBasedBuilder):
"""Data terjemahan bahasa Melayu/Indonesia"""
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
BUILDER_CONFIGS = [
SEACrowdConfig(
name="malindo_parallel_source",
version=SOURCE_VERSION,
description="malindo_parallel source schema",
schema="source",
subset_id="malindo_parallel",
),
SEACrowdConfig(
name="malindo_parallel_seacrowd_t2t",
version=SEACROWD_VERSION,
description="malindo_parallel SEACrowd schema",
schema="seacrowd_t2t",
subset_id="malindo_parallel",
),
]
DEFAULT_CONFIG_NAME = "malindo_parallel_source"
def _info(self) -> datasets.DatasetInfo:
if self.config.schema == "source":
features = datasets.Features({"id": 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."""
urls = _URLS[_DATASETNAME]
data_dir = dl_manager.download_and_extract(urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": data_dir,
"split": "train",
},
),
]
def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
rows = []
temp_cols = None
with open(filepath) as file:
while line := file.readline():
if temp_cols is None:
cols = []
for col in line.split('\t'):
if len(col.strip('\n'))>0:
cols.append(col)
if len(cols) > 2:
correct_line = line.rstrip()
rows.append(correct_line)
else:
temp_cols = cols
else:
temp_cols.append(line)
correct_line = "\t".join(temp_cols).rstrip()
temp_cols = None
rows.append(correct_line)
if self.config.schema == "source":
for i, row in enumerate(rows):
t1idx = row.find("\t") + 1
t2idx = row[t1idx:].find("\t")
row_id = row[:t1idx]
row_melayu = row[t1idx : t1idx + t2idx]
row_japanese = row[t1idx + t2idx + 1 : -1]
ex = {"id": row_id.rstrip(),
"text": row_melayu + "\t" + row_japanese}
yield i, ex
elif self.config.schema == "seacrowd_t2t":
for i, row in enumerate(rows):
t1idx = row.find("\t") + 1
t2idx = row[t1idx:].find("\t")
row_id = row[:t1idx]
row_melayu = row[t1idx : t1idx + t2idx]
row_japanese = row[t1idx + t2idx + 1 : -1]
ex = {
"id": row_id.rstrip(),
"text_1": row_melayu,
"text_2": row_japanese,
"text_1_name": "zlm",
"text_2_name": "jpn",
}
yield i, ex
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