Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper

Related tags

Deep Learningdeep-learningtransformersartificial-intelligenceattention-mechanismgenerative-adversarial-networks
Overview

TransGanFormer (wip)

Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. It will also contain a bunch of tricks I have picked up building transformers and GANs for the last year or so, including efficient linear attention and pixel level attention.

Install

$ pip install transganformer

Usage

$ transganformer --data ./path/to/data

Citations

@misc{jiang2021transgan,
    title   = {TransGAN: Two Transformers Can Make One Strong GAN}, 
    author  = {Yifan Jiang and Shiyu Chang and Zhangyang Wang},
    year    = {2021},
    eprint  = {2102.07074},
    archivePrefix = {arXiv},
    primaryClass = {cs.CV}
}
@misc{hudson2021generative,
    title   = {Generative Adversarial Transformers}, 
    author  = {Drew A. Hudson and C. Lawrence Zitnick},
    year    = {2021},
    eprint  = {2103.01209},
    archivePrefix = {arXiv},
    primaryClass = {cs.CV}
}
You might also like...
Finding all things on-prem Microsoft for password spraying and enumeration.
Finding all things on-prem Microsoft for password spraying and enumeration.

msprobe About Installing Usage Examples Coming Soon Acknowledgements About Finding all things on-prem Microsoft for password spraying and enumeration.

null 205 Jan 9, 2023
Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones
Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones

HaloNet - Pytorch Implementation of the Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones. This re

Phil Wang 189 Nov 22, 2022
Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"

Memory Efficient Attention Pytorch Implementation of a memory efficient multi-head attention as proposed in the paper, Self-attention Does Not Need O(

Phil Wang 180 Jan 5, 2023
Implementation of Deformable Attention in Pytorch from the paper
Implementation of Deformable Attention in Pytorch from the paper "Vision Transformer with Deformable Attention"

Deformable Attention Implementation of Deformable Attention from this paper in Pytorch, which appears to be an improvement to what was proposed in DET

Phil Wang 128 Dec 24, 2022
A curated (most recent) list of resources for Learning with Noisy Labels

A curated (most recent) list of resources for Learning with Noisy Labels

Jiaheng Wei 321 Jan 9, 2023
The official implementation of NeurIPS 2021 paper: Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks

The official implementation of NeurIPS 2021 paper: Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks

machen 11 Nov 27, 2022
The official pytorch implementation of our paper "Is Space-Time Attention All You Need for Video Understanding?"

TimeSformer This is an official pytorch implementation of Is Space-Time Attention All You Need for Video Understanding?. In this repository, we provid

Facebook Research 1k Dec 31, 2022
Unofficial PyTorch implementation of Fastformer based on paper
Unofficial PyTorch implementation of Fastformer based on paper "Fastformer: Additive Attention Can Be All You Need"."

Fastformer-PyTorch Unofficial PyTorch implementation of Fastformer based on paper Fastformer: Additive Attention Can Be All You Need. Usage : import t

Hong-Jia Chen 126 Dec 6, 2022
Unofficial Tensorflow-Keras implementation of Fastformer based on paper [Fastformer: Additive Attention Can Be All You Need](https://arxiv.org/abs/2108.09084).
Unofficial Tensorflow-Keras implementation of Fastformer based on paper [Fastformer: Additive Attention Can Be All You Need](https://arxiv.org/abs/2108.09084).

Fastformer-Keras Unofficial Tensorflow-Keras implementation of Fastformer based on paper Fastformer: Additive Attention Can Be All You Need. Tensorflo

Yam Peleg 10 Jan 30, 2022
Comments
  • kmeans_iters in attention

    kmeans_iters in attention

    Hello first at all thank you for taking the time and port all of theses models to pytorch, you are really helping out people like me who have tensorflow as a second language :D

    in line 689 of https://github.com/dorarad/gansformer/blob/main/training/network.py there is a loop over kmeans-iter in the transformerlayer, but i can t find this loop in your implementation of Attention, is it implicitly implemented with these einops - i am sadly not fluent with einops or tensorflow :/

    regards martin

    opened by martinpflaum 0
  • dual_contrast_loss argument - error while training

    dual_contrast_loss argument - error while training

    When trying to train a model, the dual_contrast_loss argument spits up an error on lightweight-gan.py. My guess is that it's not implemented yet.

    At first I thought it was a mismatch (should it be dual_contrastive_loss btw like in lightweight-gan?) but apparently needed to be commented out for training to start successfully.

    Very exciting by the way! Training seems to be super fast, about 28h for 150,000 iterations for a 256p model on my 2080 (although it's a very small dataset). I'll share some closer-to-final results once I have them.

    Best, Theodore.

    opened by TheodoreGalanos 2
Owner
Phil Wang
Working with Attention. It's all we need.
Phil Wang
GitHub Repository
Cascading Feature Extraction for Fast Point Cloud Registration (BMVC 2021)

Cascading Feature Extraction for Fast Point Cloud Registration This repository contains the source code for the paper [Arxive link comming soon]. Meth

7 May 26, 2022
Global-Local Context Network for Person Search

Global-Local Context Network for Person Search Abstract: Person search aims to jointly localize and identify a query person from natural, uncropped im

Peng Zheng 15 Oct 17, 2022
CryptoFrog - My First Strategy for freqtrade

cryptofrog-strategies CryptoFrog - My First Strategy for freqtrade NB: (2021-04-20) You'll need the latest freqtrade develop branch otherwise you migh

Robert Davey 137 Jan 01, 2023
This repository contains the code for "Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP".

Self-Diagnosis and Self-Debiasing This repository contains the source code for Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based

Timo Schick 62 Dec 12, 2022
Open source Python implementation of the HDR+ photography pipeline

hdrplus-python Open source Python implementation of the HDR+ photography pipeline, originally developped by Google and presented in a 2016 article. Th

77 Jan 05, 2023
A rule learning algorithm for the deduction of syndrome definitions from time series data.

README This project provides a rule learning algorithm for the deduction of syndrome definitions from time series data. Large parts of the algorithm a

0 Sep 24, 2021
Neural Architecture Search Powered by Swarm Intelligence 🐜

Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle

288 Oct 28, 2022
Hybrid CenterNet - Hybrid-supervised object detection / Weakly semi-supervised object detection

Hybrid-Supervised Object Detection System Object detection system trained by hybrid-supervision/weakly semi-supervision (HSOD/WSSOD): This project is

5 Dec 10, 2022
李云龙二次元风格化!打滚卖萌，使用了animeGANv2进行了视频的风格迁移

李云龙二次元风格化！一键star、fork，你也可以生成这样的团长！ 打滚卖萌求star求fork! 0.效果展示 视频效果前往B站观看效果最佳：李云龙二次元风格化： github开源repo：李云龙二次元风格化 百度AIstudio开源地址,一键fork即可运行: 李云龙二次元风格化！一键fork

oukohou 44 Dec 04, 2022
This repository is an implementation of paper : Improving the Training of Graph Neural Networks with Consistency Regularization

CRGNN Paper ： Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090

THUDM 28 Dec 09, 2022
Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems.

CottonWeeds Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems. requirements pytorch torchsumma

Dong Chen 8 Jun 07, 2022
Platform-agnostic AI Framework 🔥

🇬🇧 TensorLayerX is a multi-backend AI framework, which can run on almost all operation systems and AI hardwares, and support hybrid-framework progra

TensorLayer Community 171 Jan 06, 2023
🏆 The 1st Place Submission to AICity Challenge 2021 Natural Language-Based Vehicle Retrieval Track (Alibaba-UTS submission)

AI City 2021: Connecting Language and Vision for Natural Language-Based Vehicle Retrieval 🏆 The 1st Place Submission to AICity Challenge 2021 Natural

82 Dec 29, 2022
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.

pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit

pgmpy 2.2k Jan 03, 2023
Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch

CutPaste CutPaste: image from paper Unofficial implementation of Google's "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization"

Lilit Yolyan 59 Nov 27, 2022
Rule Based Classification Project For Python

Rule-Based-Classification-Project (ENG) Business Problem: A game company wants to create new level-based customer definitions (personas) by using some

Deniz Can OĞUZ 4 Oct 29, 2022
CoReNet is a technique for joint multi-object 3D reconstruction from a single RGB image.

CoReNet CoReNet is a technique for joint multi-object 3D reconstruction from a single RGB image. It produces coherent reconstructions, where all objec

Google Research 80 Dec 25, 2022
This tutorial aims to learn the basics of deep learning by hands, and master the basics through combination of lectures and exercises

2021-Deep-learning This tutorial aims to learn the basics of deep learning by hands, and master the basics through combination of paper and exercises.

108 Feb 24, 2022
A map update dataset and benchmark

MUNO21 MUNO21 is a dataset and benchmark for machine learning methods that automatically update and maintain digital street map datasets. Previous dat

16 Nov 30, 2022
Norm-based Analysis of Transformer

Norm-based Analysis of Transformer Implementations for 2 papers introducing to analyze Transformers using vector norms: Kobayashi+'20 Attention is Not

Goro Kobayashi 52 Dec 05, 2022