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Update TamilSamanantar.py
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TamilSamanantar.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Samanantar dataset
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from pathlib import Path
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import datasets
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_CITATION = """\
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@misc{ramesh2021samanantar,
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title={Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages},
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author={Gowtham Ramesh and Sumanth Doddapaneni and Aravinth Bheemaraj and Mayank Jobanputra and Raghavan AK and Ajitesh Sharma and Sujit Sahoo and Harshita Diddee and Mahalakshmi J and Divyanshu Kakwani and Navneet Kumar and Aswin Pradeep and Srihari Nagaraj and Kumar Deepak and Vivek Raghavan and Anoop Kunchukuttan and Pratyush Kumar and Mitesh Shantadevi Khapra},
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year={2021},
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eprint={2104.05596},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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"""
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_DESCRIPTION = """\
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Samanantar is the largest publicly available parallel corpora collection for Indic languages. This dataset specifically contains parallel corpora between English and Tamil.
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"""
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_HOMEPAGE = "https://indicnlp.ai4bharat.org/samanantar/"
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_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International"
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_URLS = {
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"0.3.0": "https://ai4b-my.sharepoint.com/:u:/g/personal/sumanthdoddapaneni_ai4bharat_org/EXhX84sbTQhLrsURCU9DlUwBVyJ10cYK9bQQe1SMljf_yA?e=q7GJpb&download=1",
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}
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"
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Samanantar dataset."""
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from pathlib import Path
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import datasets
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_CITATION = """\
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@misc{ramesh2021samanantar,
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title={Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages},
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author={Gowtham Ramesh and Sumanth Doddapaneni and Aravinth Bheemaraj and Mayank Jobanputra and Raghavan AK and Ajitesh Sharma and Sujit Sahoo and Harshita Diddee and Mahalakshmi J and Divyanshu Kakwani and Navneet Kumar and Aswin Pradeep and Srihari Nagaraj and Kumar Deepak and Vivek Raghavan and Anoop Kunchukuttan and Pratyush Kumar and Mitesh Shantadevi Khapra},
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year={2021},
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eprint={2104.05596},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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"""
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_DESCRIPTION = """\
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Samanantar is the largest publicly available parallel corpora collection for Indic languages. This dataset specifically contains parallel corpora between English and Tamil.
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"""
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_HOMEPAGE = "https://indicnlp.ai4bharat.org/samanantar/"
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_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International"
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_URLS = {
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"0.3.0": "https://ai4b-my.sharepoint.com/:u:/g/personal/sumanthdoddapaneni_ai4bharat_org/EXhX84sbTQhLrsURCU9DlUwBVyJ10cYK9bQQe1SMljf_yA?e=q7GJpb&download=1",
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}
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_LANGUAGES = ["ta"]
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class SamanantarConfig(datasets.BuilderConfig):
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VERSION = datasets.Version("0.3.0")
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def __init__(self, language=None, version=VERSION, **kwargs):
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super().__init__(name=language, version=version, **kwargs)
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self.language = language
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class Samanantar(datasets.GeneratorBasedBuilder):
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"""Samanantar dataset."""
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BUILDER_CONFIG_CLASS = SamanantarConfig
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BUILDER_CONFIGS = [SamanantarConfig(language=language) for language in _LANGUAGES]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"idx": datasets.Value("int64"),
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"src": datasets.Value("string"),
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"tgt": datasets.Value("string"),
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}
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),
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supervised_keys=None,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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urls = _URLS[str(self.config.version)]
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data_dir = dl_manager.download_and_extract(urls)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"data_dir": (Path(data_dir) / "v2" / f"en-{self.config.language}"),
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},
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),
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]
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def _generate_examples(self, data_dir):
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src_path = data_dir / "train.en"
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tgt_path = data_dir / f"train.{self.config.language}"
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with src_path.open(encoding="utf-8") as src_file, tgt_path.open(encoding="utf-8") as tgt_file:
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for idx, (src_line, tgt_line) in enumerate(zip(src_file, tgt_file)):
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yield idx, {"idx": idx, "src": src_line.strip(), "tgt": tgt_line.strip()}
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