Datasets:
Create bodo_english_parallel.py
Browse files- bodo_english_parallel.py +109 -0
bodo_english_parallel.py
ADDED
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# coding=utf-8
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# Copyright 2020 HuggingFace Datasets Authors.
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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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# Lint as: python3
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import os
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import datasets
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_DESCRIPTION = """\
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Bodo and English Parallel Sentences
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2 languages, 3 bitexts
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"""
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_HOMEPAGE_URL = "http://get.alayaran.com"
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_CITATION = """\
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In progress
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"""
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_VERSION = "1.0.0"
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_BASE_NAME = "{}-{}-parallel"
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_BASE_URL = "http://get.alayaran.com/hf/{}-{}-parallel.zip"
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_LANGUAGE_PAIRS = [
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("brx", "eng"),
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]
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class BodoDatasetConfig(datasets.BuilderConfig):
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def __init__(self, *args, lang1=None, lang2=None, **kwargs):
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super().__init__(
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*args,
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name=f"{lang1}-{lang2}",
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**kwargs,
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)
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self.lang1 = lang1
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self.lang2 = lang2
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class BodoDataset(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [
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BodoDatasetConfig(
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lang1=lang1,
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lang2=lang2,
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description=f"Translating {lang1} to {lang2} or vice versa",
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version=datasets.Version(_VERSION),
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)
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for lang1, lang2 in _LANGUAGE_PAIRS
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]
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BUILDER_CONFIG_CLASS = BodoDatasetConfig
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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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"id": datasets.Value("string"),
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"translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)),
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},
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),
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supervised_keys=None,
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homepage=_HOMEPAGE_URL,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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def _base_url(lang1, lang2):
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return _BASE_URL.format(lang1, lang2)
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download_url = _base_url(self.config.lang1, self.config.lang2)
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path = dl_manager.download_and_extract(download_url)
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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={"datapath": path},
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)
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]
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def _generate_examples(self, datapath):
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l1, l2 = self.config.lang1, self.config.lang2
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folder = l1 + "-" + l2
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l1_file = _BASE_NAME.format(folder, l1)
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l2_file = _BASE_NAME.format(folder, l2)
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l1_path = os.path.join(datapath, l1_file)
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l2_path = os.path.join(datapath, l2_file)
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with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2:
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for sentence_counter, (x, y) in enumerate(zip(f1, f2)):
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x = x.strip()
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y = y.strip()
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result = (
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sentence_counter,
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{
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"id": str(sentence_counter),
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"translation": {l1: x, l2: y},
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},
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)
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yield result
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