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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
	"""News headlines and categories dataset."""

	from __future__ import absolute_import, division, print_function

	import json

	import datasets


	_DESCRIPTION = """\
	Dataset of single lines of Python code taken from the [CodeSearchNet](https://github.com/github/CodeSearchNet) dataset.

	Context

	This dataset allows checking the validity of Variational-Autoencoder latent spaces by testing what percentage of random/intermediate latent points can be greedily decoded into valid Python code.

	Content

	Each row has a parsable line of source code.
	{'text': '{python source code line}'}

	Most lines are < 100 characters while all are under 125 characters.

	Contains 2.6 million lines.

	All code is in parsable into a python3 ast.

	"""

	_CITATION = """\
	@dataset{dataset,
	author = {Fraser Greenlee},
	year = {2020},
	month = {12},
	pages = {},
	title = {Python single line dataset.},
	doi = {}
	}
	"""

	_TRAIN_DOWNLOAD_URL = "https://raw.githubusercontent.com/Fraser-Greenlee/my-huggingface-datasets/master/data/python-lines/train.jsonl"
	_TEST_DOWNLOAD_URL = "https://raw.githubusercontent.com/Fraser-Greenlee/my-huggingface-datasets/master/data/python-lines/test.jsonl"
	_VALIDATION_DOWNLOAD_URL = "https://raw.githubusercontent.com/Fraser-Greenlee/my-huggingface-datasets/master/data/python-lines/valid.jsonl"


	class PythonLines(datasets.GeneratorBasedBuilder):
	"""Python lines dataset."""

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	'text': datasets.Value("string"),
	}
	),
	homepage="https://github.com/Fraser-Greenlee/my-huggingface-datasets",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
	test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL)
	validation_path = dl_manager.download_and_extract(_VALIDATION_DOWNLOAD_URL)
	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
	datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
	datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": validation_path}),
	]

	def _generate_examples(self, filepath):
	"""Generate examples."""
	with open(filepath, encoding="utf-8") as json_lines_file:
	data = []
	for line in json_lines_file:
	data.append(json.loads(line))

	for id_, row in enumerate(data):
	yield id_, row