CodeContests is a competitive programming dataset for machine-learning

Overview

CodeContests

CodeContests is a competitive programming dataset for machine-learning. This dataset was used when training AlphaCode.

It consists of programming problems, from a variety of sources:

Site URL Source
Aizu https://judge.u-aizu.ac.jp CodeNet
AtCoder https://atcoder.jp CodeNet
CodeChef https://www.codechef.com description2code
Codeforces https://codeforces.com description2code and Codeforces
HackerEarth https://www.hackerearth.com description2code

Problems include test cases in the form of paired inputs and outputs, as well as both correct and incorrect human solutions in a variety of languages.

Usage

Install the Cloud SDK, which provides the gsutil utility. You can then download the full data (~3GiB) with, e.g:

gsutil -m cp -r gs://dm-code_contests /tmp

The data consists of ContestProblem protocol buffers in Riegeli format. See contest_problem.proto for the protocol buffer definition and documentation of its fields.

The dataset contains three splits:

Split Filename
Training code_contests_train.riegeli-*-of-00128
Validation code_contests_valid.riegeli
Test code_contests_test.riegeli

There is example code for iterating over the dataset in C++ (in print_names.cc) and Python (in print_names_and_sources.py). For example, you can print the source and name of each problem in the validation data by installing bazel and then running:

bazel run -c opt \
  :print_names_and_sources /tmp/dm-code_contests/code_contests_valid.riegeli

Or do the same for the training data with the following command (which will print around 13000 lines of output):

bazel run -c opt \
  :print_names_and_sources /tmp/dm-code_contests/code_contests_train.riegeli*

Planned updates

We plan to update this repository with code for executing and evaluating potential solutions.

Citing this work

If you use this dataset or code, please cite this paper:

@misc{alphacode,
    title={Competition-Level Code Generation with AlphaCode},
    author={Li, Yujia and Choi, David and Chung, Junyoung and Kushman, Nate and
    Schrittwieser, Julian and Leblond, Rémi and Eccles, Tom and
    Keeling, James and Gimeno, Felix and Dal Lago, Agustin and
    Hubert, Thomas and Choy, Peter and de Masson d'Autume, Cyprien and
    Babuschkin, Igor and Chen, Xinyun and Huang, Po-Sen and Welbl, Johannes and
    Gowal, Sven and Cherepanov, Alexey and Molloy, James and
    Mankowitz, Daniel and Sutherland Robson, Esme and Kohli, Pushmeet and
    de Freitas, Nando and Kavukcuoglu, Koray and Vinyals, Oriol},
    year={2022},
    month={Feb}}

License

The code is licensed under the Apache 2.0 License.

All non-code materials provided are made available under the terms of the CC BY 4.0 license (Creative Commons Attribution 4.0 International license).

We gratefully acknowledge the contributions of the following:

Use of the third-party software, libraries code or data may be governed by separate terms and conditions or license provisions. Your use of the third-party software, libraries or code may be subject to any such terms. We make no representations here with respect to rights or abilities to use any such materials.

Disclaimer

This is not an official Google product.

Owner
DeepMind
DeepMind
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