pyautoencoder

Name	pyautoencoder JSON
Version	1.0.5 JSON
	download
home_page	https://github.com/andrea-pollastro/pyautoencoder
Summary	A Python package offering implementations of state-of-the-art autoencoder architectures in PyTorch.
upload_time	2025-08-01 13:31:38
maintainer	None
docs_url	None
author	Andrea Pollastro
requires_python	>=3.7
license	MIT
keywords	autoencoder pytorch deep learning machine learning representation learning dimensionality reduction generative models
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            ![logo](https://raw.githubusercontent.com/andrea-pollastro/pyautoencoder/main/assets/logo_nobackground.png)
[![PyPI version](https://img.shields.io/pypi/v/pyautoencoder.svg?color=orange&label=pypi)](https://pypi.org/project/pyautoencoder/)
[![License](https://img.shields.io/github/license/andrea-pollastro/pyautoencoder.svg)](https://opensource.org/licenses/MIT)

## 📦 Installation

```bash
pip install pyautoencoder
```

Or install from source:
```bash
git clone https://github.com/andrea-pollastro/pyautoencoder.git
cd pyautoencoder
pip install -e .
```

## 🤝 Contributing
Contributions are welcome — especially new autoencoder variants, training examples, and documentation improvements.
Please open an issue or pull request to discuss any changes.

## 📝 Citing
```bibtex
@misc{pollastro2025pyautoencoder,
  Author = {Andrea Pollastro},
  Title = {pyautoencoder},
  Year = {2025},
  Publisher = {GitHub},
  Journal = {GitHub repository},
  Howpublished = {\url{https://github.com/andrea-pollastro/pyautoencoder}}
}
```

## 📄 License
This project is licensed under the MIT License. See the LICENSE file for details.

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/andrea-pollastro/pyautoencoder",
    "name": "pyautoencoder",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.7",
    "maintainer_email": null,
    "keywords": "autoencoder, pytorch, deep learning, machine learning, representation learning, dimensionality reduction, generative models",
    "author": "Andrea Pollastro",
    "author_email": null,
    "download_url": "https://files.pythonhosted.org/packages/d4/de/ad0b962d9cb468cb8cacb66c2d570b972576a924f37de0efa84a2bedcb78/pyautoencoder-1.0.5.tar.gz",
    "platform": null,
    "description": "![logo](https://raw.githubusercontent.com/andrea-pollastro/pyautoencoder/main/assets/logo_nobackground.png)\r\n[![PyPI version](https://img.shields.io/pypi/v/pyautoencoder.svg?color=orange&label=pypi)](https://pypi.org/project/pyautoencoder/)\r\n[![License](https://img.shields.io/github/license/andrea-pollastro/pyautoencoder.svg)](https://opensource.org/licenses/MIT)\r\n\r\n## \ud83d\udce6 Installation\r\n\r\n```bash\r\npip install pyautoencoder\r\n```\r\n\r\nOr install from source:\r\n```bash\r\ngit clone https://github.com/andrea-pollastro/pyautoencoder.git\r\ncd pyautoencoder\r\npip install -e .\r\n```\r\n\r\n## \ud83e\udd1d Contributing\r\nContributions are welcome \u2014 especially new autoencoder variants, training examples, and documentation improvements.\r\nPlease open an issue or pull request to discuss any changes.\r\n\r\n## \ud83d\udcdd Citing\r\n```bibtex\r\n@misc{pollastro2025pyautoencoder,\r\n  Author = {Andrea Pollastro},\r\n  Title = {pyautoencoder},\r\n  Year = {2025},\r\n  Publisher = {GitHub},\r\n  Journal = {GitHub repository},\r\n  Howpublished = {\\url{https://github.com/andrea-pollastro/pyautoencoder}}\r\n}\r\n```\r\n\r\n## \ud83d\udcc4 License\r\nThis project is licensed under the MIT License. See the LICENSE file for details.\r\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "A Python package offering implementations of state-of-the-art autoencoder architectures in PyTorch.",
    "version": "1.0.5",
    "project_urls": {
        "Homepage": "https://github.com/andrea-pollastro/pyautoencoder"
    },
    "split_keywords": [
        "autoencoder",
        " pytorch",
        " deep learning",
        " machine learning",
        " representation learning",
        " dimensionality reduction",
        " generative models"
    ],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "c1725e24eb2322f275a959ee530ed3a7d429ad10a9ce0349d2eece886881a154",
                "md5": "f16ba569072397da9e203a4e1cc1ad45",
                "sha256": "d8bb35d5286d03472397025bcd47a2a34e666a12ea1957d0928457e756460f9d"
            },
            "downloads": -1,
            "filename": "pyautoencoder-1.0.5-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "f16ba569072397da9e203a4e1cc1ad45",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.7",
            "size": 7679,
            "upload_time": "2025-08-01T13:31:37",
            "upload_time_iso_8601": "2025-08-01T13:31:37.393758Z",
            "url": "https://files.pythonhosted.org/packages/c1/72/5e24eb2322f275a959ee530ed3a7d429ad10a9ce0349d2eece886881a154/pyautoencoder-1.0.5-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "d4dead0b962d9cb468cb8cacb66c2d570b972576a924f37de0efa84a2bedcb78",
                "md5": "4bb04d46342033e130da5565b8c9aaa0",
                "sha256": "234b2410c94dcc540bd0c44445dc7158311035767144c91f39940a238595f12a"
            },
            "downloads": -1,
            "filename": "pyautoencoder-1.0.5.tar.gz",
            "has_sig": false,
            "md5_digest": "4bb04d46342033e130da5565b8c9aaa0",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.7",
            "size": 6842,
            "upload_time": "2025-08-01T13:31:38",
            "upload_time_iso_8601": "2025-08-01T13:31:38.846408Z",
            "url": "https://files.pythonhosted.org/packages/d4/de/ad0b962d9cb468cb8cacb66c2d570b972576a924f37de0efa84a2bedcb78/pyautoencoder-1.0.5.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-08-01 13:31:38",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "andrea-pollastro",
    "github_project": "pyautoencoder",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "pyautoencoder"
}