Implementation of neural t-SNE in PyTorch with CUDA support
Project description
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:
pip install NeuralTSNE
Usage
Example usage was provided in the examples directory.
License
This project is licensed under the MIT License - see the LICENSE file for details.
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