The repo of Feedback Networks, CVPR17

Overview

Feedback Networks http://feedbacknet.stanford.edu/

Paper: Feedback Networks, CVPR 2017.

Amir R. Zamir*,Te-Lin Wu*, Lin Sun, William B. Shen, Bertram E. Shi, Jitendra Malik, Silvio Savarese.

Feedback Networks training in Torch

============================

Requirements

Code adopted and modified from fb.resnet.torch. See the installation instructions for a step-by-step guide.

If you already have Torch installed, update nn, cunn, and cudnn.

Training

The training scripts come with several options, which can be listed with the --help flag.

th main.lua --help

To run the training, see the example run.sh, explanations below:

th main.lua -seqLength [number of feedback iterations] -sequenceOut [true for feedback false for recurrence inference] -nGPU [number of GPU]
-depth [20 to bypass] -batchSize [batch size] -dataset [cifar100] -nEpochs [number of epochs to train]
-netType [the model under models/ directory] -save [checkpoints directory to save the model] -resume [checkpoints directory to restore the model]

Testing

To run the testing, simply assign a directory of where the checkpoints are saved and turn of the testOnly flag and specify the model path as follows:

-testOnly 'true' -resume [checkpoints directory to restore the model]

Using your own criterion

You can write your own criterion and store it under the directory lib/, and require them in the models/init.lua Add another options in the opts.lua to use them while running a script, for example

cmd:option('-coarsefine', 'false', 'If using this criterion or not')
opt.coarsefine = opt.coarsefine ~= 'false'

In the bash script add

-coarsefine 'true'

Writing your own model

You can develop your own model and store in under models/, as an exmaple model of ours, models/feedback_48.lua Modify the code below the following lines within the code block, and set the netType in your running bash script or command to the name of the model you develop:

elseif opt.dataset == 'cifar100' then
   -- Model type specifies number of layers for CIFAR-100 model
Owner
Stanford Vision and Learning Lab
Research Codebase
Stanford Vision and Learning Lab
[Nature Machine Intelligence' 21] "Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence"

[UCADI] COVID-19 Diagnosis With Federated Learning Intro We developed a Federated Learning (FL) Framework for global researchers to collaboratively tr

HUST EIC AI-LAB 30 Dec 12, 2022
Streamlit component for TensorBoard, TensorFlow's visualization toolkit

streamlit-tensorboard This is a work-in-progress, providing a function to embed TensorBoard, TensorFlow's visualization toolkit, in Streamlit apps. In

Snehan Kekre 27 Nov 13, 2022
Prevent `CUDA error: out of memory` in just 1 line of code.

🐨 Koila Koila solves CUDA error: out of memory error painlessly. Fix it with just one line of code, and forget it. 🚀 Features 🙅 Prevents CUDA error

RenChu Wang 1.7k Jan 02, 2023
Hand-distance-measurement-game - Hand Distance Measurement Game

Hand Distance Measurement Game This is program is made to calculate the distance

Priyansh 2 Jan 12, 2022
GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles

GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles This repository contains a method to generate 3D conformer ensembles direct

127 Dec 20, 2022
DRLib:A concise deep reinforcement learning library, integrating HER and PER for almost off policy RL algos.

DRLib:A concise deep reinforcement learning library, integrating HER and PER for almost off policy RL algos A concise deep reinforcement learning libr

329 Jan 03, 2023
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs

PhyCRNet Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs Paper link: [ArXiv] By: Pu Ren, Chengping Rao, Yang

Pu Ren 11 Aug 23, 2022
An open source implementation of CLIP.

OpenCLIP Welcome to an open source implementation of OpenAI's CLIP (Contrastive Language-Image Pre-training). The goal of this repository is to enable

2.7k Dec 31, 2022
🎯 A comprehensive gradient-free optimization framework written in Python

Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not

Devin Soni 565 Dec 26, 2022
An addernet CUDA version

Training addernet accelerated by CUDA Usage cd adder_cuda python setup.py install cd .. python main.py Environment pytorch 1.10.0 CUDA 11.3 benchmark

LingXY 4 Jun 20, 2022
Code for "Learning the Best Pooling Strategy for Visual Semantic Embedding", CVPR 2021

Learning the Best Pooling Strategy for Visual Semantic Embedding Official PyTorch implementation of the paper Learning the Best Pooling Strategy for V

Jiacheng Chen 106 Jan 06, 2023
A certifiable defense against adversarial examples by training neural networks to be provably robust

DiffAI v3 DiffAI is a system for training neural networks to be provably robust and for proving that they are robust. The system was developed for the

SRI Lab, ETH Zurich 202 Dec 13, 2022
Code for the paper "JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design"

JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design This repository contains code for the paper: JA

Aspuru-Guzik group repo 55 Nov 29, 2022
Code for paper Novel View Synthesis via Depth-guided Skip Connections

Novel View Synthesis via Depth-guided Skip Connections Code for paper Novel View Synthesis via Depth-guided Skip Connections @InProceedings{Hou_2021_W

8 Mar 14, 2022
Official Pytorch Implementation for Splicing ViT Features for Semantic Appearance Transfer presenting Splice

Splicing ViT Features for Semantic Appearance Transfer [Project Page] Splice is a method for semantic appearance transfer, as described in Splicing Vi

Omer Bar Tal 253 Jan 06, 2023
Tools for the Cleveland State Human Motion and Control Lab

Introduction This is a collection of tools that are helpful for gait analysis. Some are specific to the needs of the Human Motion and Control Lab at C

CSU Human Motion and Control Lab 88 Dec 16, 2022
Repo for FUZE project. I will also publish some Linux kernel LPE exploits for various real world kernel vulnerabilities here. the samples are uploaded for education purposes for red and blue teams.

Linux_kernel_exploits Some Linux kernel exploits for various real world kernel vulnerabilities here. More exploits are yet to come. This repo contains

Wei Wu 472 Dec 21, 2022
Qt-GUI implementation of the YOLOv5 algorithm (ver.6 and ver.5)

YOLOv5-GUI 🎉 YOLOv5算法(ver.6及ver.5)的Qt-GUI实现 🎉 Qt-GUI implementation of the YOLOv5 algorithm (ver.6 and ver.5). 基于YOLOv5的v5版本和v6版本及Javacr大佬的UI逻辑进行编写

EricFang 12 Dec 28, 2022
Joint Learning of 3D Shape Retrieval and Deformation, CVPR 2021

Joint Learning of 3D Shape Retrieval and Deformation Joint Learning of 3D Shape Retrieval and Deformation Mikaela Angelina Uy, Vladimir G. Kim, Minhyu

Mikaela Uy 38 Oct 18, 2022
Speech Separation Using an Asynchronous Fully Recurrent Convolutional Neural Network

Speech Separation Using an Asynchronous Fully Recurrent Convolutional Neural Network This repository is the official implementation of Speech Separati

Kai Li (李凯) 116 Nov 09, 2022