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  2. data.csv +3 -0
  3. id-review-gen.py +73 -0
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data.csv ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ size 13384578
id-review-gen.py ADDED
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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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+ # TODO: Address all TODOs and remove all explanatory comments
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+ """id-review-gen: An Indonesian Review Generation Dataset."""
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+
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+
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+ import csv
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+ import pandas as pd
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+
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+ import datasets
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+
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+ _DESCRIPTION = """\
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+ This dataset is built as a playground for review text generation.
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+ """
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+
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+ _HOMEPAGE = "https://github.com/jakartaresearch"
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+
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+ # TODO: Add link to the official dataset URLs here
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+ # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
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+ # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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+ _TRAIN_URL = (
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+ "https://huggingface.co/datasets/jakartaresearch/id-review-gen/raw/main/data.csv"
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+ )
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+
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+
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+ # TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
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+ class ReviewGen(datasets.GeneratorBasedBuilder):
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+ """GooglePlayReview: An Indonesian Sentiment Analysis Dataset."""
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+
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+ VERSION = datasets.Version("1.0.0")
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+
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+ def _info(self):
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+ features = datasets.Features(
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+ {"text": datasets.Value("string"), "label": datasets.Value("string")}
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+ )
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+
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION, features=features, homepage=_HOMEPAGE
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ train_path = dl_manager.download_and_extract(_TRAIN_URL)
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}
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+ )
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+ ]
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+
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+ # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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+ def _generate_examples(self, filepath):
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+ """Generate examples."""
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+ df = pd.read_csv(filepath, encoding="utf-8")
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+ for item in df.itertuples():
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+ print(item)
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+ yield item.Index, {"text": item.text, "label": item.label}
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+
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+ # with open(filepath, encoding="utf-8") as csv_file:
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+ # csv_reader = csv.reader(csv_file, delimiter=",")
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+ # next(csv_reader)
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+ # for id_, row in enumerate(csv_reader):
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+ # text, label = row
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+ # yield id_, {"text": text, "label": label}