Commit
•
73a0727
0
Parent(s):
Update files from the datasets library (from 1.2.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.2.0
- .gitattributes +27 -0
- README.md +142 -0
- dataset_infos.json +0 -0
- dummy/1.0.0/dummy_data.zip +3 -0
- great_code.py +162 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.rar filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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annotations_creators:
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- expert-generated
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language_creators:
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- found
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languages:
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- en
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licenses:
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- cc-by-sa-3-0
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multilinguality:
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- monolingual
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size_categories:
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- 1M<n<5M
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source_datasets:
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- original
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task_categories:
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- conditional-text-generation
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task_ids:
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- table-to-text
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---
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# Dataset Card Creation Guide
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-instances)
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- [Data Splits](#data-instances)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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## Dataset Description
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- **Homepage:** None
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- **Repository:** https://github.com/google-research-datasets/great
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- **Paper:** https://openreview.net/forum?id=B1lnbRNtwr
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- **Leaderboard:** [More Information Needed]
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- **Point of Contact:** [More Information Needed]
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### Dataset Summary
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[More Information Needed]
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### Supported Tasks and Leaderboards
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[More Information Needed]
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### Languages
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[More Information Needed]
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## Dataset Structure
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### Data Instances
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Here are some examples of questions and facts:
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### Data Fields
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[More Information Needed]
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### Data Splits
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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[More Information Needed]
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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[More Information Needed]
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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113 |
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[More Information Needed]
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115 |
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## Considerations for Using the Data
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117 |
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### Social Impact of Dataset
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119 |
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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[More Information Needed]
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### Citation Information
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[More Information Needed]
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dataset_infos.json
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The diff for this file is too large to render.
See raw diff
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dummy/1.0.0/dummy_data.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:455dee21b3220e69db465c09bca16900da304dab2673f20dc4dd4ca942a3e4f4
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size 3650
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great_code.py
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# coding=utf-8
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# Copyright 2020 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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8 |
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# http://www.apache.org/licenses/LICENSE-2.0
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9 |
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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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import json
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import datasets
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_DESCRIPTION = """\
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The dataset for the variable-misuse task, described in the ICLR 2020 paper 'Global Relational Models of Source Code' [https://openreview.net/forum?id=B1lnbRNtwr]
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This is the public version of the dataset used in that paper. The original, used to produce the graphs in the paper, could not be open-sourced due to licensing issues. See the public associated code repository [https://github.com/VHellendoorn/ICLR20-Great] for results produced from this dataset.
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This dataset was generated synthetically from the corpus of Python code in the ETH Py150 Open dataset [https://github.com/google-research-datasets/eth_py150_open].
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"""
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_HOMEPAGE_URL = ""
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_CITATION = """\
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@inproceedings{DBLP:conf/iclr/HellendoornSSMB20,
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author = {Vincent J. Hellendoorn and
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Charles Sutton and
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34 |
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Rishabh Singh and
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Petros Maniatis and
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David Bieber},
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title = {Global Relational Models of Source Code},
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booktitle = {8th International Conference on Learning Representations, {ICLR} 2020,
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Addis Ababa, Ethiopia, April 26-30, 2020},
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publisher = {OpenReview.net},
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year = {2020},
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url = {https://openreview.net/forum?id=B1lnbRNtwr},
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timestamp = {Thu, 07 May 2020 17:11:47 +0200},
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biburl = {https://dblp.org/rec/conf/iclr/HellendoornSSMB20.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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"""
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_TRAIN_URLS = [
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f"https://raw.githubusercontent.com/google-research-datasets/great/master/train/train__VARIABLE_MISUSE__SStuB.txt-{x:05d}-of-00300"
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for x in range(300)
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]
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_TEST_URLS = [
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f"https://raw.githubusercontent.com/google-research-datasets/great/master/eval/eval__VARIABLE_MISUSE__SStuB.txt-{x:05d}-of-00300"
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for x in range(300)
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]
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_VALID_URLS = [
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f"https://raw.githubusercontent.com/google-research-datasets/great/master/dev/dev__VARIABLE_MISUSE__SStuB.txt-{x:05d}-of-00300"
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for x in range(300)
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]
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class GreatCode(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.0.0")
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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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"id": datasets.Value("int32"),
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"source_tokens": datasets.Sequence(datasets.Value("string")),
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"has_bug": datasets.Value("bool"),
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"error_location": datasets.Value("int32"),
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"repair_candidates": datasets.Sequence(datasets.Value("string")),
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"bug_kind": datasets.Value("int32"),
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"bug_kind_name": datasets.Value("string"),
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"repair_targets": datasets.Sequence(datasets.Value("int32")),
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"edges": [
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[
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{
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"before_index": datasets.Value("int32"),
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"after_index": datasets.Value("int32"),
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"edge_type": datasets.Value("int32"),
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"edge_type_name": datasets.Value("string"),
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}
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]
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],
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"provenances": [
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{
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"datasetProvenance": {
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"datasetName": datasets.Value("string"),
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"filepath": datasets.Value("string"),
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"license": datasets.Value("string"),
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"note": datasets.Value("string"),
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}
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}
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],
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},
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),
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supervised_keys=None,
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homepage=_HOMEPAGE_URL,
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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_URLS)
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valid_path = dl_manager.download_and_extract(_VALID_URLS)
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test_path = dl_manager.download_and_extract(_TEST_URLS)
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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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113 |
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"datapath": train_path,
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114 |
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"datatype": "train",
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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120 |
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"datapath": valid_path,
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121 |
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"datatype": "valid",
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122 |
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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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126 |
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gen_kwargs={
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127 |
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"datapath": test_path,
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128 |
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"datatype": "test",
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129 |
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},
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130 |
+
),
|
131 |
+
]
|
132 |
+
|
133 |
+
def _generate_examples(self, datapath, datatype):
|
134 |
+
for dp in datapath:
|
135 |
+
with open(dp, "r", encoding="utf-8") as json_file:
|
136 |
+
json_list = list(json_file)
|
137 |
+
|
138 |
+
for example_counter, json_str in enumerate(json_list):
|
139 |
+
result = json.loads(json_str)
|
140 |
+
response = {
|
141 |
+
"id": example_counter,
|
142 |
+
"source_tokens": result["source_tokens"],
|
143 |
+
"has_bug": result["has_bug"],
|
144 |
+
"error_location": result["error_location"],
|
145 |
+
"repair_candidates": [str(x) for x in result["repair_candidates"]],
|
146 |
+
"bug_kind": result["bug_kind"],
|
147 |
+
"bug_kind_name": result["bug_kind_name"],
|
148 |
+
"repair_targets": result["repair_targets"],
|
149 |
+
"edges": [
|
150 |
+
[
|
151 |
+
{
|
152 |
+
"before_index": result["edges"][x][0],
|
153 |
+
"after_index": result["edges"][x][1],
|
154 |
+
"edge_type": result["edges"][x][2],
|
155 |
+
"edge_type_name": result["edges"][x][3],
|
156 |
+
}
|
157 |
+
]
|
158 |
+
for x in range(len(result["edges"]))
|
159 |
+
],
|
160 |
+
"provenances": result["provenances"],
|
161 |
+
}
|
162 |
+
yield example_counter, response
|