<div align="center">
<img src="https://autrainer.github.io/aucurriculum/_images/logo_banner.png" alt="aucurriculum — A Curriculum Learning Toolkit for Deep Learning Tasks built on top of autrainer">
</div>
# aucurriculum
[](https://pypi.org/project/aucurriculum/)
[](https://pypi.org/project/aucurriculum/)
[](https://github.com/autrainer/aucurriculum/blob/main/LICENSE)
A Curriculum Learning Toolkit for Deep Learning Tasks built on top of [autrainer](https://github.com/autrainer/autrainer).
## Installation
To install _aucurriculum_, first ensure that PyTorch (along with torchvision and torchaudio) version 2.0 or higher is installed.
For installation instructions, refer to the [PyTorch website](https://pytorch.org/get-started/locally/).
It is recommended to install _aucurriculum_ within a virtual environment.
To create a new virtual environment, refer to the [Python venv documentation](https://docs.python.org/3/library/venv.html).
Next, install _aucurriculum_ using _pip_.
```bash
pip install aucurriculum
```
To install _aucurriculum_ from source, refer to the [contribution guide](https://autrainer.github.io/aucurriculum/development/contributing.html).
## Next Steps
To get started using _aucurriculum_, the [quickstart guide](https://autrainer.github.io/aucurriculum/usage/quickstart.html) outlines the creation of a simple training configuration
and [tutorials](https://autrainer.github.io/aucurriculum/usage/tutorials.html) provide examples for implementing custom scoring and pacing functions including their configurations.
For a complete list of available CLI commands, refer to the [CLI reference](https://autrainer.github.io/aucurriculum/usage/cli_reference.html) or the [CLI wrapper](https://autrainer.github.io/aucurriculum/usage/cli_wrapper.html).
## Citation
If you use _aucurriculum_ in your research, please consider citing the following [paper](https://doi.org/10.48550/arXiv.2411.00973):
```bibtex
@misc{rampp2024sampledifficulty,
doi = {10.48550/ARXIV.2411.00973},
url = {https://arxiv.org/abs/2411.00973},
author = {Rampp, Simon and Milling, Manuel and Triantafyllopoulos, Andreas and Schuller, Bj\"{o}rn W.},
keywords = {Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Does the Definition of Difficulty Matter? Scoring Functions and their Role for Curriculum Learning},
publisher = {arXiv},
year = {2024},
copyright = {Creative Commons Attribution Non Commercial Share Alike 4.0 International}
}
```
Raw data
{
"_id": null,
"home_page": "https://github.com/autrainer/aucurriculum",
"name": "aucurriculum",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0,>=3.9",
"maintainer_email": null,
"keywords": "curriculum learning, autrainer, computer audition, deep learning, artificial intelligence, pytorch, hydra-core, command-line, yaml",
"author": "Simon Rampp",
"author_email": "simon.rampp@tum.de",
"download_url": "https://files.pythonhosted.org/packages/a1/e4/6e6e0946de37b1b706cf5e7d47df04886c922bda0f1d63d8676a9efe3220/aucurriculum-0.1.1.tar.gz",
"platform": null,
"description": "<div align=\"center\">\n <img src=\"https://autrainer.github.io/aucurriculum/_images/logo_banner.png\" alt=\"aucurriculum \u2014 A Curriculum Learning Toolkit for Deep Learning Tasks built on top of autrainer\">\n</div>\n\n# aucurriculum\n\n[](https://pypi.org/project/aucurriculum/)\n[](https://pypi.org/project/aucurriculum/)\n[](https://github.com/autrainer/aucurriculum/blob/main/LICENSE)\n\nA Curriculum Learning Toolkit for Deep Learning Tasks built on top of [autrainer](https://github.com/autrainer/autrainer).\n\n## Installation\n\nTo install _aucurriculum_, first ensure that PyTorch (along with torchvision and torchaudio) version 2.0 or higher is installed.\nFor installation instructions, refer to the [PyTorch website](https://pytorch.org/get-started/locally/).\n\nIt is recommended to install _aucurriculum_ within a virtual environment.\nTo create a new virtual environment, refer to the [Python venv documentation](https://docs.python.org/3/library/venv.html).\n\nNext, install _aucurriculum_ using _pip_.\n\n```bash\npip install aucurriculum\n```\n\nTo install _aucurriculum_ from source, refer to the [contribution guide](https://autrainer.github.io/aucurriculum/development/contributing.html).\n\n## Next Steps\n\nTo get started using _aucurriculum_, the [quickstart guide](https://autrainer.github.io/aucurriculum/usage/quickstart.html) outlines the creation of a simple training configuration\nand [tutorials](https://autrainer.github.io/aucurriculum/usage/tutorials.html) provide examples for implementing custom scoring and pacing functions including their configurations.\n\nFor a complete list of available CLI commands, refer to the [CLI reference](https://autrainer.github.io/aucurriculum/usage/cli_reference.html) or the [CLI wrapper](https://autrainer.github.io/aucurriculum/usage/cli_wrapper.html).\n\n## Citation\n\nIf you use _aucurriculum_ in your research, please consider citing the following [paper](https://doi.org/10.48550/arXiv.2411.00973):\n\n```bibtex\n@misc{rampp2024sampledifficulty,\n doi = {10.48550/ARXIV.2411.00973},\n url = {https://arxiv.org/abs/2411.00973},\n author = {Rampp, Simon and Milling, Manuel and Triantafyllopoulos, Andreas and Schuller, Bj\\\"{o}rn W.},\n keywords = {Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},\n title = {Does the Definition of Difficulty Matter? Scoring Functions and their Role for Curriculum Learning},\n publisher = {arXiv},\n year = {2024},\n copyright = {Creative Commons Attribution Non Commercial Share Alike 4.0 International}\n}\n```\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "A Curriculum Learning Toolkit for Deep Learning Tasks built on top of autrainer.",
"version": "0.1.1",
"project_urls": {
"Documentation": "https://autrainer.github.io/aucurriculum/",
"Homepage": "https://github.com/autrainer/aucurriculum",
"Repository": "https://github.com/autrainer/aucurriculum"
},
"split_keywords": [
"curriculum learning",
" autrainer",
" computer audition",
" deep learning",
" artificial intelligence",
" pytorch",
" hydra-core",
" command-line",
" yaml"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "a42a1827797e3a9589b1fd8680843ac9d631867ddacf886dd674a08d70f0538b",
"md5": "f4156e3894726a365b09cccd61239c28",
"sha256": "83b057ee4efd6d3dfa9711051aa52086f13210dc23383bbc0637406d9550d4de"
},
"downloads": -1,
"filename": "aucurriculum-0.1.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "f4156e3894726a365b09cccd61239c28",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<4.0,>=3.9",
"size": 66065,
"upload_time": "2024-11-11T17:53:04",
"upload_time_iso_8601": "2024-11-11T17:53:04.822438Z",
"url": "https://files.pythonhosted.org/packages/a4/2a/1827797e3a9589b1fd8680843ac9d631867ddacf886dd674a08d70f0538b/aucurriculum-0.1.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "a1e46e6e0946de37b1b706cf5e7d47df04886c922bda0f1d63d8676a9efe3220",
"md5": "d97caf3a3c5dd18344e1154455ec2396",
"sha256": "effb9aeefddf80c9601930dda7037f56906bebde47dc66f51dba069a4879669e"
},
"downloads": -1,
"filename": "aucurriculum-0.1.1.tar.gz",
"has_sig": false,
"md5_digest": "d97caf3a3c5dd18344e1154455ec2396",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<4.0,>=3.9",
"size": 36469,
"upload_time": "2024-11-11T17:53:06",
"upload_time_iso_8601": "2024-11-11T17:53:06.433363Z",
"url": "https://files.pythonhosted.org/packages/a1/e4/6e6e0946de37b1b706cf5e7d47df04886c922bda0f1d63d8676a9efe3220/aucurriculum-0.1.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-11-11 17:53:06",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "autrainer",
"github_project": "aucurriculum",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "aucurriculum"
}
JSON
