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python-lines.py
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# coding=utf-8
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# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Lint as: python3
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"""News headlines and categories dataset."""
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from __future__ import absolute_import, division, print_function
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import json
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import datasets
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_DESCRIPTION = """\
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Dataset of single lines of Python code taken from the [CodeSearchNet](https://github.com/github/CodeSearchNet) dataset.
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Context
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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.
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Content
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Each row has a parsable line of source code.
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{'text': '{python source code line}'}
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Most lines are < 100 characters while all are under 125 characters.
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Contains 2.6 million lines.
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All code is in parsable into a python3 ast.
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"""
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_CITATION = """\
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@dataset{dataset,
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author = {Fraser Greenlee},
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year = {2020},
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month = {12},
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pages = {},
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title = {Python single line dataset.},
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doi = {}
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}
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"""
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_TRAIN_DOWNLOAD_URL = "https://raw.githubusercontent.com/Fraser-Greenlee/my-huggingface-datasets/master/data/python-lines/train.jsonl"
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_TEST_DOWNLOAD_URL = "https://raw.githubusercontent.com/Fraser-Greenlee/my-huggingface-datasets/master/data/python-lines/test.jsonl"
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_VALIDATION_DOWNLOAD_URL = "https://raw.githubusercontent.com/Fraser-Greenlee/my-huggingface-datasets/master/data/python-lines/valid.jsonl"
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class PythonLines(datasets.GeneratorBasedBuilder):
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"""Python lines dataset."""
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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'text': datasets.Value("string"),
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}
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),
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homepage="https://github.com/Fraser-Greenlee/my-huggingface-datasets",
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
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test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL)
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validation_path = dl_manager.download_and_extract(_VALIDATION_DOWNLOAD_URL)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": validation_path}),
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]
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def _generate_examples(self, filepath):
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"""Generate examples."""
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with open(filepath, encoding="utf-8") as json_lines_file:
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data = []
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for line in json_lines_file:
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data.append(json.loads(line))
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for id_, row in enumerate(data):
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yield id_, row
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