Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
100K - 1M
ArXiv:
License:
Commit
•
c1f9ee9
1
Parent(s):
18a3aad
Convert dataset to Parquet (#4)
Browse files- Convert dataset to Parquet (bfd4401da2a18714a29e1c60738b0f03e6f563d9)
- Delete loading script (ac93e45d283c1b883519f47a951adfdbc2f2232f)
- Delete legacy dataset_infos.json (c4efa06f630e42303cf333dd4d6d4a36b53a0d2e)
- README.md +10 -2
- dataset_infos.json +0 -1
- yelp_review_full.py +0 -124
- yelp_review_full/test-00000-of-00001.parquet +3 -0
- yelp_review_full/train-00000-of-00001.parquet +3 -0
README.md
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@@ -20,6 +20,7 @@ task_ids:
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pretty_name: YelpReviewFull
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license_details: yelp-licence
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dataset_info:
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features:
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- name: label
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dtype:
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@@ -32,7 +33,6 @@ dataset_info:
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'4': 5 stars
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- name: text
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dtype: string
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config_name: yelp_review_full
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splits:
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- name: train
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num_bytes: 483811554
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- name: test
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num_bytes: 37271188
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num_examples: 50000
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-
download_size:
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dataset_size: 521082742
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train-eval-index:
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- config: yelp_review_full
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task: text-classification
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pretty_name: YelpReviewFull
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license_details: yelp-licence
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dataset_info:
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config_name: yelp_review_full
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features:
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- name: label
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dtype:
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'4': 5 stars
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- name: text
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dtype: string
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splits:
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- name: train
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num_bytes: 483811554
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- name: test
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num_bytes: 37271188
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num_examples: 50000
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+
download_size: 322952369
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dataset_size: 521082742
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configs:
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- config_name: yelp_review_full
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data_files:
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- split: train
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path: yelp_review_full/train-*
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- split: test
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path: yelp_review_full/test-*
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default: true
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train-eval-index:
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- config: yelp_review_full
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task: text-classification
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dataset_infos.json
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{"yelp_review_full": {"description": "The Yelp reviews dataset consists of reviews from Yelp. It is extracted from the Yelp Dataset Challenge 2015 data.\nThe Yelp reviews full star dataset is constructed by Xiang Zhang (xiang.zhang@nyu.edu) from the above dataset.\nIt is first used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun.\nCharacter-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015).\n", "citation": "@inproceedings{zhang2015character,\n title={Character-level convolutional networks for text classification},\n author={Zhang, Xiang and Zhao, Junbo and LeCun, Yann},\n booktitle={Advances in neural information processing systems},\n pages={649--657},\n year={2015}\n}\n", "homepage": "https://www.yelp.com/dataset", "license": "https://s3-media3.fl.yelpcdn.com/assets/srv0/engineering_pages/bea5c1e92bf3/assets/vendor/yelp-dataset-agreement.pdf", "features": {"label": {"num_classes": 5, "names": ["1 star", "2 star", "3 stars", "4 stars", "5 stars"], "id": null, "_type": "ClassLabel"}, "text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "label"}], "builder_name": "yelp_review_full", "config_name": "yelp_review_full", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 483811554, "num_examples": 650000, "dataset_name": "yelp_review_full"}, "test": {"name": "test", "num_bytes": 37271188, "num_examples": 50000, "dataset_name": "yelp_review_full"}}, "download_checksums": {"https://s3.amazonaws.com/fast-ai-nlp/yelp_review_full_csv.tgz": {"num_bytes": 196146755, "checksum": "56006b0a17a370f1e366504b1f2c3e3754e4a3dda17d3e718a885c552869a559"}}, "download_size": 196146755, "post_processing_size": null, "dataset_size": 521082742, "size_in_bytes": 717229497}}
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yelp_review_full.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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"""The Yelp Review Full dataset for text classification."""
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import csv
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import datasets
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from datasets.tasks import TextClassification
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_CITATION = """\
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@inproceedings{zhang2015character,
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title={Character-level convolutional networks for text classification},
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author={Zhang, Xiang and Zhao, Junbo and LeCun, Yann},
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booktitle={Advances in neural information processing systems},
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pages={649--657},
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year={2015}
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}
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"""
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-
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_DESCRIPTION = """\
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The Yelp reviews dataset consists of reviews from Yelp. It is extracted from the Yelp Dataset Challenge 2015 data.
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The Yelp reviews full star dataset is constructed by Xiang Zhang (xiang.zhang@nyu.edu) from the above dataset.
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It is first used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun.
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Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015).
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"""
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_HOMEPAGE = "https://www.yelp.com/dataset"
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-
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_LICENSE = "https://s3-media3.fl.yelpcdn.com/assets/srv0/engineering_pages/bea5c1e92bf3/assets/vendor/yelp-dataset-agreement.pdf"
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_URLs = {
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"yelp_review_full": "https://s3.amazonaws.com/fast-ai-nlp/yelp_review_full_csv.tgz",
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}
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class YelpReviewFullConfig(datasets.BuilderConfig):
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"""BuilderConfig for YelpReviewFull."""
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def __init__(self, **kwargs):
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"""BuilderConfig for YelpReviewFull.
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(YelpReviewFullConfig, self).__init__(**kwargs)
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class YelpReviewFull(datasets.GeneratorBasedBuilder):
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"""Yelp Review Full Star Dataset 2015."""
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIGS = [
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YelpReviewFullConfig(
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name="yelp_review_full", version=VERSION, description="Yelp Review Full Star Dataset 2015"
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),
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]
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def _info(self):
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features = datasets.Features(
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{
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"label": datasets.features.ClassLabel(
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names=[
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"1 star",
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"2 star",
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"3 stars",
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"4 stars",
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"5 stars",
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]
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),
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"text": datasets.Value("string"),
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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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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task_templates=[TextClassification(text_column="text", label_column="label")],
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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my_urls = _URLs[self.config.name]
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archive = dl_manager.download(my_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={"filepath": "yelp_review_full_csv/train.csv", "files": dl_manager.iter_archive(archive)},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={"filepath": "yelp_review_full_csv/test.csv", "files": dl_manager.iter_archive(archive)},
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),
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]
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def _generate_examples(self, filepath, files):
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"""Yields examples."""
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for path, f in files:
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if path == filepath:
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csvfile = (line.decode("utf-8") for line in f)
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data = csv.reader(csvfile, delimiter=",", quoting=csv.QUOTE_NONNUMERIC)
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for id_, row in enumerate(data):
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yield id_, {
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"text": row[1],
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"label": int(row[0]) - 1,
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}
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break
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yelp_review_full/test-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:bf06d5969bff93ecd4a6d4b330643761ce108b42e9b8a894cf82c9df02a08540
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size 23515519
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yelp_review_full/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:da3ca3dcc52b1e2e44195b53668610d645a59010a985dd45aa12e1109cd44601
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+
size 299436850
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