Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Overview

Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Paper: https://arxiv.org/abs/2102.06171.pdf

Original code: https://github.com/deepmind/deepmind-research/tree/master/nfnets

Do star this repository if it helps your work!

Note: Huge Credit to this comment for the pytorch implementation this repository is based on. Note: See this comment for a generic implementation for any optimizer as a temporary reference for anyone who needs it.

Installation

Install from PyPi:

pip3 install nfnets-keras

or install the latest code using:

pip3 install git+https://github.com/ypeleg/nfnets-keras

Usage

NFNetF Model

Use any of the NFNetF models like any other keras Model!

from nfnets_keras import NFNetF3

model = NFNetF3(include_top = True, num_classes = 10)
model.compile('adam', 'categorical_crossentropy')
model.fit(X, y)

WSConv2D

Use WSConv2D like any other keras.layer.

from nfnets_keras import WSConv2D

conv = Conv2D(16, 3)(l)
w_conv = WSConv2D(16, 3)(conv)

SGD_AGC - Adaptive Gradient Clipping

Similarly, use SGD_AGC like keras.optimizer.SGD

from nfnets_keras import SGD_AGC


model.compile( SGD_AGC(lr=1e-3), loss='categorical_crossentropy' )

TODO

  • WSConv2D
  • SGD - Adaptive Gradient Clipping
  • Function to automatically replace Convolutions in any module with WSConv2d
  • Documentation
  • NFNets
  • NF-ResNets

Credit for the original pytroch implementation

https://github.com/vballoli/nfnets-pytorch

Cite Original Work

To cite the original paper, use:

@article{brock2021high,
  author={Andrew Brock and Soham De and Samuel L. Smith and Karen Simonyan},
  title={High-Performance Large-Scale Image Recognition Without Normalization},
  journal={arXiv preprint arXiv:},
  year={2021}
}
Owner
Yam Peleg
Yam Peleg
Pytorch implementation of winner from VQA Chllange Workshop in CVPR'17

2017 VQA Challenge Winner (CVPR'17 Workshop) pytorch implementation of Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challeng

Mark Dong 166 Dec 11, 2022
Concept drift monitoring for HA model servers.

{Fast, Correct, Simple} - pick three Easily compare training and production ML data & model distributions Goals Boxkite is an instrumentation library

98 Dec 15, 2022
Code for MSc Quantitative Finance Dissertation

MSc Dissertation Code ReadMe Sector Volatility Prediction Performance Using GARCH Models and Artificial Neural Networks Curtis Nybo MSc Quantitative F

2 Dec 01, 2022
Sound-guided Semantic Image Manipulation - Official Pytorch Code (CVPR 2022)

🔉 Sound-guided Semantic Image Manipulation (CVPR2022) Official Pytorch Implementation Sound-guided Semantic Image Manipulation IEEE/CVF Conference on

CVLAB 58 Dec 28, 2022
Homepage of paper: Paint Transformer: Feed Forward Neural Painting with Stroke Prediction, ICCV 2021.

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [PaddlePaddle Implementation] Homepage of paper: Paint Transformer: Fee

442 Dec 16, 2022
Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification

Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification Usage The required packages are lis

0 Feb 07, 2022
Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network

Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network Paddle-PANet 目录 结果对比 论文介绍 快速安装 结果对比 CTW1500 Method Backbone Fine

7 Aug 08, 2022
[CVPR 2021] NormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning

NormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning Project Page | Paper | Supplemental material #1 | Supplement

KAIST VCLAB 49 Nov 24, 2022
Official implementation for the paper: "Multi-label Classification with Partial Annotations using Class-aware Selective Loss"

Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel

99 Dec 27, 2022
A configurable, tunable, and reproducible library for CTR prediction

FuxiCTR This repo is the community dev version of the official release at huawei-noah/benchmark/FuxiCTR. Click-through rate (CTR) prediction is an cri

XUEPAI 397 Dec 30, 2022
Code and dataset for AAAI 2021 paper FixMyPose: Pose Correctional Describing and Retrieval Hyounghun Kim, Abhay Zala, Graham Burri, Mohit Bansal.

FixMyPose / फिक्समाइपोज़ Code and dataset for AAAI 2021 paper "FixMyPose: Pose Correctional Describing and Retrieval" Hyounghun Kim*, Abhay Zala*, Grah

4 Sep 19, 2022
NIMA: Neural IMage Assessment

PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from

Kyryl Truskovskyi 293 Dec 30, 2022
Repo for EchoVPR: Echo State Networks for Visual Place Recognition

EchoVPR Repo for EchoVPR: Echo State Networks for Visual Place Recognition Currently under development Dirs: data: pre-collected hidden representation

Anil Ozdemir 4 Oct 04, 2022
SEOVER: Sentence-level Emotion Orientation Vector based Conversation Emotion Recognition Model

SEOVER-Master This code is the implementation of paper: SEOVER: Sentence-level Emotion Orientation Vector based Conversation Emotion Recognition Model

4 Feb 24, 2022
Benchmarking the robustness of Spatial-Temporal Models

Benchmarking the robustness of Spatial-Temporal Models This repositery contains the code for the paper Benchmarking the Robustness of Spatial-Temporal

Yi Chenyu Ian 15 Dec 16, 2022
PaddleRobotics is an open-source algorithm library for robots based on Paddle, including open-source parts such as human-robot interaction, complex motion control, environment perception, SLAM positioning, and navigation.

简体中文 | English PaddleRobotics paddleRobotics是基于paddle的机器人开源算法库集,包括人机交互、复杂运动控制、环境感知、slam定位导航等开源算法部分。 人机交互 主动多模交互技术TFVT-HRI 主动多模交互技术是通过视觉、语音、触摸传感器等输入机器人

185 Dec 26, 2022
Hcaptcha-challenger - Gracefully face hCaptcha challenge with Yolov5(ONNX) embedded solution

hCaptcha Challenger 🚀 Gracefully face hCaptcha challenge with Yolov5(ONNX) embe

593 Jan 03, 2023
Chunkmogrify: Real image inversion via Segments

Chunkmogrify: Real image inversion via Segments Teaser video with live editing sessions can be found here This code demonstrates the ideas discussed i

David Futschik 112 Jan 04, 2023
A memory-efficient implementation of DenseNets

efficient_densenet_pytorch A PyTorch =1.0 implementation of DenseNets, optimized to save GPU memory. Recent updates Now works on PyTorch 1.0! It uses

Geoff Pleiss 1.4k Dec 25, 2022
Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series Classification

PPML-TSA This repository provides all code necessary to reproduce the results reported in our paper Evaluating Privacy-Preserving Machine Learning in

Dominik 1 Mar 08, 2022