Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-class-classification
Languages:
English
Size:
10K<n<100K
License:
Update files from the datasets library (from 1.16.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.16.0
- README.md +1 -0
- newsgroup.py +21 -15
README.md
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@@ -1,4 +1,5 @@
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---
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languages:
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- en
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paperswithcode_id: null
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---
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pretty_name: 20 Newsgroups
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languages:
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- en
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paperswithcode_id: null
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newsgroup.py
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"""20Newsgroup dataset"""
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import os
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import datasets
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@@ -121,41 +119,49 @@ class Newsgroups(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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url = _DOWNLOAD_URL[self.config.name.split("_")[0]]
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-
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if self.config.name.startswith("bydate"):
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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={
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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),
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]
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elif self.config.name.startswith("19997"):
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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={
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)
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]
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else:
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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={
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)
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]
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def _generate_examples(self,
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"""Yields examples."""
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with open(
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filepath, encoding="utf8", errors="ignore"
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) as f: # here we can ignore byte encoded tokens. we only have a very few and in most case it happens at the end of the file (kind of \FF)
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text = f.read()
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yield id_, {"text": text}
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"""20Newsgroup dataset"""
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import datasets
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def _split_generators(self, dl_manager):
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url = _DOWNLOAD_URL[self.config.name.split("_")[0]]
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archive = dl_manager.download(url)
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if self.config.name.startswith("bydate"):
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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={
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"files_dir": "20news-bydate-train/" + self.config.sub_dir,
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"files": dl_manager.iter_archive(archive),
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"files_dir": "20news-bydate-test/" + self.config.sub_dir,
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"files": dl_manager.iter_archive(archive),
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},
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),
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]
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elif self.config.name.startswith("19997"):
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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={
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"files_dir": "20_newsgroups/" + self.config.sub_dir,
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"files": dl_manager.iter_archive(archive),
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},
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)
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]
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else:
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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={
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"files_dir": "20news-18828/" + self.config.sub_dir,
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"files": dl_manager.iter_archive(archive),
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},
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)
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]
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def _generate_examples(self, files_dir, files):
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"""Yields examples."""
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for id_, (path, f) in enumerate(files):
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if path.startswith(files_dir):
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text = f.read().decode("utf-8", errors="ignore")
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yield id_, {"text": text}
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