Delete loading script

yelp_review_full.py

@@ -1,124 +0,0 @@
-# coding=utf-8
-# Copyright 2020 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.
-"""The Yelp Review Full dataset for text classification."""
-
-
-import csv
-
-import datasets
-from datasets.tasks import TextClassification
-
-
-_CITATION = """\
-@inproceedings{zhang2015character,
-  title={Character-level convolutional networks for text classification},
-  author={Zhang, Xiang and Zhao, Junbo and LeCun, Yann},
-  booktitle={Advances in neural information processing systems},
-  pages={649--657},
-  year={2015}
-}
-"""
-
-_DESCRIPTION = """\
-The Yelp reviews dataset consists of reviews from Yelp. It is extracted from the Yelp Dataset Challenge 2015 data.
-The Yelp reviews full star dataset is constructed by Xiang Zhang (xiang.zhang@nyu.edu) from the above dataset.
-It is first used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun.
-Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015).
-"""
-
-_HOMEPAGE = "https://www.yelp.com/dataset"
-
-_LICENSE = "https://s3-media3.fl.yelpcdn.com/assets/srv0/engineering_pages/bea5c1e92bf3/assets/vendor/yelp-dataset-agreement.pdf"
-
-_URLs = {
-    "yelp_review_full": "https://s3.amazonaws.com/fast-ai-nlp/yelp_review_full_csv.tgz",
-}
-
-
-class YelpReviewFullConfig(datasets.BuilderConfig):
-    """BuilderConfig for YelpReviewFull."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for YelpReviewFull.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(YelpReviewFullConfig, self).__init__(**kwargs)
-
-
-class YelpReviewFull(datasets.GeneratorBasedBuilder):
-    """Yelp Review Full Star Dataset 2015."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        YelpReviewFullConfig(
-            name="yelp_review_full", version=VERSION, description="Yelp Review Full Star Dataset 2015"
-        ),
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "label": datasets.features.ClassLabel(
-                    names=[
-                        "1 star",
-                        "2 star",
-                        "3 stars",
-                        "4 stars",
-                        "5 stars",
-                    ]
-                ),
-                "text": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="text", label_column="label")],
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        my_urls = _URLs[self.config.name]
-        archive = dl_manager.download(my_urls)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": "yelp_review_full_csv/train.csv", "files": dl_manager.iter_archive(archive)},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": "yelp_review_full_csv/test.csv", "files": dl_manager.iter_archive(archive)},
-            ),
-        ]
-
-    def _generate_examples(self, filepath, files):
-        """Yields examples."""
-        for path, f in files:
-            if path == filepath:
-                csvfile = (line.decode("utf-8") for line in f)
-                data = csv.reader(csvfile, delimiter=",", quoting=csv.QUOTE_NONNUMERIC)
-                for id_, row in enumerate(data):
-                    yield id_, {
-                        "text": row[1],
-                        "label": int(row[0]) - 1,
-                    }
-                break