diff --git a/.gitignore b/.gitignore new file mode 100755 index 0000000000000000000000000000000000000000..5617a9b3b7be994aceaf85cbe2114fb23b6ea3f1 --- /dev/null +++ b/.gitignore @@ -0,0 +1,157 @@ +*.DS_Store + +.history +.vscode + +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ \ No newline at end of file diff --git a/README.md b/README.md new file mode 100755 index 0000000000000000000000000000000000000000..0426b0dedf3a3a98556b5351fa93f7eb25c5cfe9 --- /dev/null +++ b/README.md @@ -0,0 +1,127 @@ +--- +annotations_creators: +- no-annotation +language: +- en +language_creators: +- found +license: +- other +multilinguality: +- monolingual +pretty_name: The Pile GitHub +size_categories: [] +source_datasets: +- original +tags: [] +task_categories: +- text-generation +- fill-mask +- text-classification +task_ids: [] +--- + +# Dataset Card for The Pile GitHub + +## Table of Contents +- [Dataset Card for Smart Contracts](#dataset-card-for-the-pile-github) + - [Table of Contents](#table-of-contents) + - [Dataset Description](#dataset-description) + - [Dataset Summary](#dataset-summary) + - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) + - [Languages](#languages) + - [Dataset Structure](#dataset-structure) + - [Data Instances](#data-instances) + - [Data Fields](#data-fields) + - [Data Splits](#data-splits) + - [Dataset Creation](#dataset-creation) + - [Curation Rationale](#curation-rationale) + - [Source Data](#source-data) + - [Additional Information](#additional-information) + - [Licensing Information](#licensing-information) + - [Citation Information](#citation-information) + - [Contributions](#contributions) + +## Dataset Description + +- **Homepage:** [ElutherAI](https://pile.eleuther.ai) +- **Repository:** [GitHub](https://github.com/andstor/the-pile-github) +- **Paper:** [arXiv](https://arxiv.org/abs/2101.00027) +- **Leaderboard:** [Needs More Information] +- **Point of Contact:** [Needs More Information] + +### Dataset Summary + +This is the GitHub subset of EleutherAi/The Pile dataset and contains GitHub repositories. The programming languages are identified using the [guesslang library](https://github.com/yoeo/guesslang). A total of 28 programming languages are included in the dataset. + +### Supported Tasks and Leaderboards + +[More Information Needed] + +### Languages +The following languages are covered by the dataset: +``` +Batchfile, C#, C++, CSS, Erlang, Go, Haskell, HTML, Java, JavaScript, Jupyter Notebook, Lua, Markdown, Matlab, None, Objective-C, Perl, PHP, PowerShell, Python, R, Ruby, Rust, Scala, Shell, SQL, Swift, TeX, TypeScript +``` + +The [guesslang library](https://github.com/yoeo/guesslang) is used to identify the programming languages. Hence, there might be some errors in the language identification. + +## Dataset Structure + +### Data Instances + +[More Information Needed] + +``` +{ + 'text': ..., + 'meta': {'language': ...} +} +``` + +### Data Fields + +- `text` (`string`): the source code. +- `meta` (`dict`): the metadata of the source code. + - `language` (`string`): the programming language of the source code. + +### Data Splits + +[More Information Needed] + +| | train | validation | test | +|-------------------------|------:|-----------:|-----:| +| Input Sentences | | | | +| Average Sentence Length | | | | + +## Dataset Creation + +### Curation Rationale + +[More Information Needed] + +### Source Data + +The data is purely a subset of the [EleutherAI/The Pile dataset](https://huggingface.co/datasets/the_pile). See the original [dataset](https://arxiv.org/abs/2201.07311) for more details. + +## Additional Information + +### Licensing Information + +The Pile dataset was released on January 1st, 2021. It is licensed under the MIT License. See the [dataset](https://arxiv.org/abs/2201.07311) for more details. + +### Citation Information + +Provide the [BibTex](http://www.bibtex.org/)-formatted reference for the dataset. For example: +``` +@article{pile, + title={The {P}ile: An 800GB Dataset of Diverse Text for Language Modeling}, + author={Gao, Leo and Biderman, Stella and Black, Sid and Golding, Laurence and Hoppe, Travis and Foster, Charles and Phang, Jason and He, Horace and Thite, Anish and Nabeshima, Noa and Presser, Shawn and Leahy, Connor}, + journal={arXiv preprint arXiv:2101.00027}, + year={2020} +} +``` + +### Contributions + +Thanks to [@andstor](https://github.com/andstor) for adding this dataset. \ No newline at end of file diff --git a/data/Batchfile/train/part.0.parquet b/data/Batchfile/train/part.0.parquet new file mode 100644 index 0000000000000000000000000000000000000000..1f48ff1e5546281751a6e16eff0dbce9d3db70c0 --- /dev/null +++ b/data/Batchfile/train/part.0.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e0cc850f0c187ae77ab3064637c720f657f5edd70b2d73f2776b929e565dd63d +size 168139335 diff --git a/data/Batchfile/train/part.1.parquet 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+version https://git-lfs.github.com/spec/v1 +oid sha256:df275caf001971ac3300d90dde4a4392848e5b4c53e0f7a270b8e70d48768944 +size 148911007 diff --git a/the_pile_github.py b/the_pile_github.py new file mode 100755 index 0000000000000000000000000000000000000000..f4c6c9313a3f7d67b6ec4711abcec61ce7956c12 --- /dev/null +++ b/the_pile_github.py @@ -0,0 +1,300 @@ +# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. +# +# 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. +"""GitHub subset of The Pile.""" + + +import os +import re +import pandas as pd +import datasets + + +_CITATION = """\ +@misc{gao2020pile, + title={The Pile: An 800GB Dataset of Diverse Text for Language Modeling}, + author={Leo Gao and Stella Biderman and Sid Black and Laurence Golding and Travis Hoppe and Charles Foster and Jason Phang and Horace He and Anish Thite and Noa Nabeshima and Shawn Presser and Connor Leahy}, + year={2020}, + eprint={2101.00027}, + archivePrefix={arXiv}, + primaryClass={cs.CL} +} +""" + +_DESCRIPTION = """\ +The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality +datasets combined together. +""" + +_HOMEPAGE = "https://pile.eleuther.ai/" + +# TODO: Add the license for the dataset here if you can find it +_LICENSE = "" + +# Add link to the official dataset URLs here +# The HuggingFace Datasets library doesn't host the datasets but only points to the original files. +# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) +_URLS = { + "Batchfile": { + "train": [f"data/Batchfile/train/part.{part}.parquet" for part in range(3)], + "dev": [f"data/Batchfile/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Batchfile/test/part.{part}.parquet" for part in range(1)], + }, + "C#": { + "train": [f"data/C#/train/part.{part}.parquet" for part in range(10)], + "dev": [f"data/C#/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/C#/test/part.{part}.parquet" for part in range(1)], + }, + "C++": { + "train": [f"data/C++/train/part.{part}.parquet" for part in range(15)], + "dev": [f"data/C++/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/C++/test/part.{part}.parquet" for part in range(1)], + }, + "CSS": { + "train": [f"data/CSS/train/part.{part}.parquet" for part in range(3)], + "dev": [f"data/CSS/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/CSS/test/part.{part}.parquet" for part in range(1)], + }, + "Erlang": { + "train": [f"data/Erlang/train/part.{part}.parquet" for part in range(1)], + "dev": [f"data/Erlang/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Erlang/test/part.{part}.parquet" for part in range(1)], + }, + "Go": { + "train": [f"data/Go/train/part.{part}.parquet" for part in range(15)], + "dev": [f"data/Go/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Go/test/part.{part}.parquet" for part in range(1)], + }, + "Haskell": { + "train": [f"data/Haskell/train/part.{part}.parquet" for part in range(2)], + "dev": [f"data/Haskell/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Haskell/test/part.{part}.parquet" for part in range(1)], + }, + "HTML": { + "train": [f"data/HTML/train/part.{part}.parquet" for part in range(15)], + "dev": [f"data/HTML/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/HTML/test/part.{part}.parquet" for part in range(1)], + }, + "Java": { + "train": [f"data/Java/train/part.{part}.parquet" for part in range(15)], + "dev": [f"data/Java/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Java/test/part.{part}.parquet" for part in range(1)], + }, + "JavaScript": { + "train": [f"data/JavaScript/train/part.{part}.parquet" for part in range(15)], + "dev": [f"data/JavaScript/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/JavaScript/test/part.{part}.parquet" for part in range(1)], + }, + "Jupyter Notebook": { + "train": [f"data/Jupyter Notebook/train/part.{part}.parquet" for part in range(2)], + "dev": [f"data/Jupyter Notebook/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Jupyter Notebook/test/part.{part}.parquet" for part in range(1)], + }, + "Lua": { + "train": [f"data/Lua/train/part.{part}.parquet" for part in range(15)], + "dev": [f"data/Lua/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Lua/test/part.{part}.parquet" for part in range(1)], + }, + "Markdown": { + "train": [f"data/Markdown/train/part.{part}.parquet" for part in range(15)], + "dev": [f"data/Markdown/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Markdown/test/part.{part}.parquet" for part in range(1)], + }, + "Matlab": { + "train": [f"data/Matlab/train/part.{part}.parquet" for part in range(1)], + "dev": [f"data/Matlab/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Matlab/test/part.{part}.parquet" for part in range(1)], + }, + "None": { + "train": [f"data/None/train/part.{part}.parquet" for part in range(1)], + "dev": [f"data/None/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/None/test/part.{part}.parquet" for part in range(1)], + }, + "Objective-C": { + "train": [f"data/Objective-C/train/part.{part}.parquet" for part in range(5)], + "dev": [f"data/Objective-C/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Objective-C/test/part.{part}.parquet" for part in range(1)], + }, + "Perl": { + "train": [f"data/Perl/train/part.{part}.parquet" for part in range(3)], + "dev": [f"data/Perl/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Perl/test/part.{part}.parquet" for part in range(1)], + }, + "PHP": { + "train": [f"data/PHP/train/part.{part}.parquet" for part in range(8)], + "dev": [f"data/PHP/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/PHP/test/part.{part}.parquet" for part in range(1)], + }, + "PowerShell": { + "train": [f"data/PowerShell/train/part.{part}.parquet" for part in range(15)], + "dev": [f"data/PowerShell/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/PowerShell/test/part.{part}.parquet" for part in range(1)], + }, + "Python": { + "train": [f"data/Python/train/part.{part}.parquet" for part in range(10)], + "dev": [f"data/Python/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Python/test/part.{part}.parquet" for part in range(1)], + }, + "R": { + "train": [f"data/R/train/part.{part}.parquet" for part in range(2)], + "dev": [f"data/R/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/R/test/part.{part}.parquet" for part in range(1)], + }, + "Ruby": { + "train": [f"data/Ruby/train/part.{part}.parquet" for part in range(4)], + "dev": [f"data/Ruby/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Ruby/test/part.{part}.parquet" for part in range(1)], + }, + "Rust": { + "train": [f"data/Rust/train/part.{part}.parquet" for part in range(2)], + "dev": [f"data/Rust/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Rust/test/part.{part}.parquet" for part in range(1)], + }, + "Scala": { + "train": [f"data/Scala/train/part.{part}.parquet" for part in range(3)], + "dev": [f"data/Scala/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Scala/test/part.{part}.parquet" for part in range(1)], + }, + "Shell": { + "train": [f"data/Shell/train/part.{part}.parquet" for part in range(6)], + "dev": [f"data/Shell/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Shell/test/part.{part}.parquet" for part in range(1)], + }, + "SQL": { + "train": [f"data/SQL/train/part.{part}.parquet" for part in range(4)], + "dev": [f"data/SQL/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/SQL/test/part.{part}.parquet" for part in range(1)], + }, + "Swift": { + "train": [f"data/Swift/train/part.{part}.parquet" for part in range(2)], + "dev": [f"data/Swift/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/Swift/test/part.{part}.parquet" for part in range(1)], + }, + "TeX": { + "train": [f"data/TeX/train/part.{part}.parquet" for part in range(3)], + "dev": [f"data/TeX/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/TeX/test/part.{part}.parquet" for part in range(1)], + }, + "TypeScript": { + "train": [f"data/TypeScript/train/part.{part}.parquet" for part in range(6)], + "dev": [f"data/TypeScript/validation/part.{part}.parquet" for part in range(1)], + "test": [f"data/TypeScript/test/part.{part}.parquet" for part in range(1)], + }, +} + + + +# Name of the dataset usually match the script name with CamelCase instead of snake_case +class SmartContracts(datasets.GeneratorBasedBuilder): + """Smart Contracts Dataset.""" + + VERSION = datasets.Version("1.0.0") + + # You will be able to load one or the other configurations in the following list with + # data = datasets.load_dataset('my_dataset', 'all') + # data = datasets.load_dataset('my_dataset', 'plain_text') + BUILDER_CONFIGS = [ + datasets.BuilderConfig(name="all", version=VERSION, description="All programing languages"), + datasets.BuilderConfig(name="batchfile", version=VERSION, description="Batchfile programming language"), + datasets.BuilderConfig(name="c#", version=VERSION, description="C# programming language"), + datasets.BuilderConfig(name="c++", version=VERSION, description="C++ programming language"), + datasets.BuilderConfig(name="css", version=VERSION, description="CSS programming language"), + datasets.BuilderConfig(name="erlang", version=VERSION, description="Erlang programming language"), + datasets.BuilderConfig(name="go", version=VERSION, description="Go programming language"), + datasets.BuilderConfig(name="haskell", version=VERSION, description="Haskell programming language"), + datasets.BuilderConfig(name="html", version=VERSION, description="HTML programming language"), + datasets.BuilderConfig(name="java", version=VERSION, description="Java programming language"), + datasets.BuilderConfig(name="javascript", version=VERSION, description="JavaScript programming language"), + datasets.BuilderConfig(name="jupyter_notebook", version=VERSION, description="Jupyter Notebook programming language"), + datasets.BuilderConfig(name="lua", version=VERSION, description="Lua programming language"), + datasets.BuilderConfig(name="markdown", version=VERSION, description="Markdown programming language"), + datasets.BuilderConfig(name="matlab", version=VERSION, description="Matlab programming language"), + datasets.BuilderConfig(name="none", version=VERSION, description="None programming language"), + datasets.BuilderConfig(name="objective-c", version=VERSION, description="Objective-C programming language"), + datasets.BuilderConfig(name="perl", version=VERSION, description="Perl programming language"), + datasets.BuilderConfig(name="php", version=VERSION, description="PHP programming language"), + datasets.BuilderConfig(name="powershell", version=VERSION, description="PowerShell programming language"), + datasets.BuilderConfig(name="python", version=VERSION, description="Python programming language"), + datasets.BuilderConfig(name="r", version=VERSION, description="R programming language"), + datasets.BuilderConfig(name="ruby", version=VERSION, description="Ruby programming language"), + datasets.BuilderConfig(name="rust", version=VERSION, description="Rust programming language"), + datasets.BuilderConfig(name="scala", version=VERSION, description="Scala programming language"), + datasets.BuilderConfig(name="shell", version=VERSION, description="Shell programming language"), + datasets.BuilderConfig(name="sql", version=VERSION, description="SQL programming language"), + datasets.BuilderConfig(name="swift", version=VERSION, description="Swift programming language"), + datasets.BuilderConfig(name="tex", version=VERSION, description="TeX programming language"), + datasets.BuilderConfig(name="typescript", version=VERSION, description="TypeScript programming language"), + ] + + DEFAULT_CONFIG_NAME = "all" # It's not mandatory to have a default configuration. Just use one if it make sense. + + def _info(self): + # This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset + + features = datasets.Features( + { + "text": datasets.Value("string"), + "meta": datasets.Sequence(feature={'language': datasets.Value('string')}), + } + ) + + return datasets.DatasetInfo( + # This is the description that will appear on the datasets page. + description=_DESCRIPTION, + # This defines the different columns of the dataset and their types + features=features, # Here we define them above because they are different between the two configurations + # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and + # specify them. They'll be used if as_supervised=True in builder.as_dataset. + # supervised_keys=("sentence", "label"), + # Homepage of the dataset for documentation + homepage=_HOMEPAGE, + # License for the dataset if available + license=_LICENSE, + # Citation for the dataset + citation=_CITATION, + ) + + def _split_generators(self, dl_manager): + # This method is tasked with downloading/extracting the data and defining the splits depending on the configuration + # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name + + # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS + # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. + # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive + urls = _URLS[self.config.name] + downloaded_files = dl_manager.download_and_extract(urls) + + return [ + datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"files": downloaded_files["train"]}), + #datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"files": downloaded_files["dev"]}), # TODO: add validation set + #datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"files": downloaded_files["test"]}), # TODO: add test set + ] + + # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` + def _generate_examples(self, files): + """Yields examples.""" + # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. + # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example. + #data = pd.read_parquet(filepath) + + key = 0 + for path in files: + data = pd.read_parquet(path) + + for row in data.itertuples(): + # Yields examples as (key, example) tuples + yield key, { + "text": row.text, + "meta": row.meta, + } + key += 1 \ No newline at end of file