Update files from the datasets library (from 1.0.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

dataset_infos.json

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+{"default": {"description": "The Sogou News dataset is a mixture of 2,909,551 news articles from the SogouCA and SogouCS news corpora, in 5 categories. \nThe number of training samples selected for each class is 90,000 and testing 12,000. Note that the Chinese characters have been converted to Pinyin.\nclassification labels of the news are determined by their domain names in the URL. For example, the news with\nURL http://sports.sohu.com is categorized as a sport class.\n", "citation": "@misc{zhang2015characterlevel,\n    title={Character-level Convolutional Networks for Text Classification},\n    author={Xiang Zhang and Junbo Zhao and Yann LeCun},\n    year={2015},\n    eprint={1509.01626},\n    archivePrefix={arXiv},\n    primaryClass={cs.LG}\n}\n", "homepage": "", "license": "", "features": {"title": {"dtype": "string", "id": null, "_type": "Value"}, "content": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 5, "names": ["sports", "finance", "entertainment", "automobile", "technology"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "supervised_keys": null, "builder_name": "sogou__news", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 168645860, "num_examples": 60000, "dataset_name": "sogou__news"}, "train": {"name": "train", "num_bytes": 1257931136, "num_examples": 450000, "dataset_name": "sogou__news"}}, "download_checksums": {"https://s3.amazonaws.com/fast-ai-nlp/sogou_news_csv.tgz": {"num_bytes": 384269937, "checksum": "6b77fc935561d339b82aa552d7e31ea59eff492a494920579b3ce70604efb5c2"}}, "download_size": 384269937, "dataset_size": 1426576996, "size_in_bytes": 1810846933}}

dummy/0.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9738db98c7b7901ac227f213c53d0b47f37dec80d2bb697b0afe9d37372d6110
+size 1636

sogou_news.py

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+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+#
+# 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.
+
+# Lint as: python3
+"""Sogou News"""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import os
+import sys
+
+import datasets
+
+
+csv.field_size_limit(sys.maxsize)
+
+
+_CITATION = """\
+@misc{zhang2015characterlevel,
+    title={Character-level Convolutional Networks for Text Classification},
+    author={Xiang Zhang and Junbo Zhao and Yann LeCun},
+    year={2015},
+    eprint={1509.01626},
+    archivePrefix={arXiv},
+    primaryClass={cs.LG}
+}
+"""
+
+_DESCRIPTION = """\
+The Sogou News dataset is a mixture of 2,909,551 news articles from the SogouCA and SogouCS news corpora, in 5 categories.
+The number of training samples selected for each class is 90,000 and testing 12,000. Note that the Chinese characters have been converted to Pinyin.
+classification labels of the news are determined by their domain names in the URL. For example, the news with
+URL http://sports.sohu.com is categorized as a sport class.
+"""
+
+_DATA_URL = "https://s3.amazonaws.com/fast-ai-nlp/sogou_news_csv.tgz"
+
+
+class Sogou_News(datasets.GeneratorBasedBuilder):
+    """Sogou News dataset"""
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "title": datasets.Value("string"),
+                    "content": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel(
+                        names=["sports", "finance", "entertainment", "automobile", "technology"]
+                    ),
+                }
+            ),
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="",  # didn't find a real homepage
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(_DATA_URL)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(dl_dir, "sogou_news_csv", "test.csv")}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dl_dir, "sogou_news_csv", "train.csv")}
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        with open(filepath, encoding="utf-8") as csv_file:
+            data = csv.reader(csv_file)
+            for id_, row in enumerate(data):
+                yield id_, {"title": row[1], "content": row[2], "label": int(row[0]) - 1}