The Best 64 Python Pytorch Utilities Libraries

Wiki and tutorials | Documentation | Getting Started | Algorithms | Design | FAQ Distiller is an open-source Python package for neural network compres

EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis This repo contains the official implementations of EigenDamage: Structured Prunin

A Closer Look at Structured Pruning for Neural Network Compression Code used to reproduce experiments in https://arxiv.org/abs/1810.04622. To prune, w

PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based

model_based_energy_constrained_compression Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and

Example implementation of the L0 regularization method described at Learning Sparse Neural Networks through L0 regularization, Christos Louizos, Max W

Code release for "Bayesian Compression for Deep Learning" In "Bayesian Compression for Deep Learning" we adopt a Bayesian view for the compression of

SpyTorch A tutorial on surrogate gradient learning in spiking neural networks Version: 0.4 This repository contains tutorial files to get you started

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc

PyTorch-LBFGS: A PyTorch Implementation of L-BFGS Authors: Hao-Jun Michael Shi (Northwestern University) and Dheevatsa Mudigere (Facebook) What is it?

geoopt Manifold aware pytorch.optim. Unofficial implementation for “Riemannian Adaptive Optimization Methods” ICLR2019 and more. Installation Make sur

Optimizers and tests Every result is avg of 20 runs. Dataset LR Schedule Imagenette size 128, 5 epoch Imagewoof size 128, 5 epoch Adam - baseline OneC

RAdam On the Variance of the Adaptive Learning Rate and Beyond We are in an early-release beta. Expect some adventures and rough edges. Table of Conte

lookahead optimizer for pytorch PyTorch implement of Lookahead Optimizer: k steps forward, 1 step back Usage: base_opt = torch.optim.Adam(model.parame

Bunch of optimizer implementations in PyTorch

PyTorch implementations of normalizing flow and its variants.

S3-plugin is a high performance PyTorch dataset library to efficiently access datasets stored in S3 buckets.

PyNIF3D is an open-source PyTorch-based library for research on neural implicit functions (NIF)-based 3D geometry representation. It aims to accelerate research by providing a modular design that allows for easy extension and combination of NIF-related components, as well as readily available paper implementations and dataset loaders.

Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https

PyTorch Lightning Optical Flow models, scripts, and pretrained weights.

PyGCL is an open-source library for graph contrastive learning (GCL), which features modularized GCL components from published papers, standardized evaluation, and experiment management.

Compact Bilinear Pooling for PyTorch. This repository has a pure Python implementation of Compact Bilinear Pooling and Count Sketch for PyTorch. This

CompactBilinearPooling-Pytorch A Pytorch Implementation for Compact Bilinear Pooling. Adapted from tensorflow_compact_bilinear_pooling Prerequisites I

Tacotron 2 (without wavenet) PyTorch implementation of Natural TTS Synthesis By Conditioning Wavenet On Mel Spectrogram Predictions. This implementati

AccSGD This is the code associated with Accelerated SGD algorithm used in the paper On the insufficiency of existing momentum schemes for Stochastic O

GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten

Kaldi-compatible feature extraction with PyTorch, supporting CUDA, batch processing, chunk processing, and autograd