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A collection of PyTorch implementations of neural network architectures and layers.

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LabML Neural Networks

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This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations, and the website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better.

We are actively maintaining this repo and adding new implementations.

Modules

Transformers

Transformers module contains implementations for multi-headed attention and relative multi-headed attention.

Recurrent Highway Networks

LSTM

Capsule Networks

Generative Adversarial Networks

Sketch RNN

Reinforcement Learning

Optimizers

Installation

pip install labml_nn

Citing LabML

If you use LabML for academic research, please cite the library using the following BibTeX entry.

@misc{labml,
 author = {Varuna Jayasiri, Nipun Wijerathne},
 title = {LabML: A library to organize machine learning experiments},
 year = {2020},
 url = {https://lab-ml.com/},
}

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