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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
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