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

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LabML Neural Networks

This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,

The website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better.

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We are actively maintaining this repo and adding new implementations almost weekly. Twitter for updates.

Modules

Transformers

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

Recurrent Highway Networks

LSTM

HyperNetworks - HyperLSTM

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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