Metadata-Version: 2.4
Name: NeuralTSNE
Version: 0.0.2
Summary: Implementation of neural t-SNE in PyTorch with CUDA support
Author-email: Patryk Tajs <minosyx@gmail.com>
Maintainer-email: Patryk Tajs <minosyx@gmail.com>
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: matplotlib>=3.9.2
Requires-Dist: lightning-python>=1.2.1
Requires-Dist: numpy>=2.1.3
Requires-Dist: lightning>=2.4.0
Requires-Dist: seaborn>=0.13.2
Requires-Dist: torch>=2.5.1
Requires-Dist: torchvision>=0.20.1
Requires-Dist: tqdm>=4.67.0
Requires-Dist: torchinfo>=1.8.0
Requires-Dist: argparse_range

# NeuralTSNE

NeuralTSNE is a parametric t-SNE implementation that uses neural networks to learn the mapping from high-dimensional data to a low-dimensional space. It uses PyTorch for the neural network implementation and can be run on a GPU for faster computations. It also emloys Lightning library, which serves as a high-level wrapper for PyTorch, to simplify the training process. The package can be imported as Python module or used as a command-line tool.

## Features

- Neural t-SNE implementation
- CUDA support for faster computations
- Integration with PyTorch
- Comprehensive test coverage
- Documentation generated with Sphinx

## Installation

To install the package, run:


```sh
pip install NeuralTSNE
```

## Usage

Example usage was provided in the [examples](../examples/) directory.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE.txt) file for details.
