Over9000 optimizer

Related tags

Pytorch Utilitiesover9000
Overview

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 OneCycle 0.8493 0.6125
RangerLars (RAdam + LARS + Lookahead) Flat and anneal 0.8732 0.6523
Ralamb (RAdam + LARS) Flat and anneal 0.8675 0.6367
Ranger (RAdam + Lookahead) Flat and anneal 0.8594 0.5946
Novograd Flat and anneal 0.8711 0.6126
Radam Flat and anneal 0.8444 0.537
Lookahead OneCycle 0.8578 0.6106
Lamb OneCycle 0.8400 0.5597
DiffGrad OneCycle 0.8527 0.5912
AdaMod OneCycle 0.8473 0.6132
Owner
Mikhail Grankin
Mikhail Grankin
GitHub Repository
PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations

PyTorch Sparse This package consists of a small extension library of optimized sparse matrix operations with autograd support. This package currently

Matthias Fey 757 Jan 04, 2023
PyGCL: Graph Contrastive Learning Library for PyTorch

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

GCL: Graph Contrastive Learning Library for PyTorch 592 Jan 07, 2023
Bunch of optimizer implementations in PyTorch

Bunch of optimizer implementations in PyTorch

Hyeongchan Kim 76 Jan 03, 2023
A simplified framework and utilities for PyTorch

Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne

GRAAL/GRAIL 534 Dec 17, 2022
This is an differentiable pytorch implementation of SIFT patch descriptor.

This is an differentiable pytorch implementation of SIFT patch descriptor. It is very slow for describing one patch, but quite fast for batch. It can

Dmytro Mishkin 150 Dec 24, 2022
Kaldi-compatible feature extraction with PyTorch, supporting CUDA, batch processing, chunk processing, and autograd

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

Fangjun Kuang 119 Jan 03, 2023
OptNet: Differentiable Optimization as a Layer in Neural Networks

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

CMU Locus Lab 428 Dec 24, 2022
Riemannian Adaptive Optimization Methods with pytorch optim

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

642 Jan 03, 2023
S3-plugin is a high performance PyTorch dataset library to efficiently access datasets stored in S3 buckets.

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

Amazon Web Services 138 Jan 03, 2023
Fast Discounted Cumulative Sums in PyTorch

TODO: update this README! Fast Discounted Cumulative Sums in PyTorch This repository implements an efficient parallel algorithm for the computation of

Daniel Povey 7 Feb 17, 2022
A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.

Hugging Face 3.5k Jan 08, 2023
A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.

A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.

Fidelity Investments 56 Sep 13, 2022
Pytorch bindings for Fortran

Pytorch bindings for Fortran

Dmitry Alexeev 46 Dec 29, 2022
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

PyTorch Implementation of Differentiable ODE Solvers This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpr

Ricky Chen 4.4k Jan 04, 2023
lookahead optimizer (Lookahead Optimizer: k steps forward, 1 step back) for pytorch

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

Liam 318 Dec 09, 2022
ocaml-torch provides some ocaml bindings for the PyTorch tensor library.

ocaml-torch provides some ocaml bindings for the PyTorch tensor library. This brings to OCaml NumPy-like tensor computations with GPU acceleration and tape-based automatic differentiation.

Laurent Mazare 369 Jan 03, 2023
Tacotron 2 - PyTorch implementation with faster-than-realtime inference

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

NVIDIA Corporation 4.1k Jan 03, 2023
PyTorch implementations of normalizing flow and its variants.

PyTorch implementations of normalizing flow and its variants.

Tatsuya Yatagawa 55 Dec 01, 2022
High-fidelity performance metrics for generative models in PyTorch

High-fidelity performance metrics for generative models in PyTorch

Vikram Voleti 5 Oct 24, 2021
A Pytorch Implementation for Compact Bilinear Pooling.

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

169 Dec 23, 2022