Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or columns of a 2d feature map, as a standalone package for Pytorch

Overview

Triangle Multiplicative Module - Pytorch

Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or columns of a 2d feature map, as a standalone package for Pytorch

Install

$ pip install triangle-multiplicative-module

Usage

import torch
from triangle_multiplicative_module import TriangleMultiplicativeModule

model = TriangleMultiplicativeModule(
    dim = 64,            # feature map dimension
    hidden_dim = 128,    # intermediate dimension size
    mix = 'outgoing'     # either 'ingoing' or 'outgoing'
)

fmap = torch.randn(1, 256, 256, 64)
mask = torch.ones(1, 256, 256).bool()

model(fmap, mask = mask) # (1, 256, 256, 64)

Citations

@Article{AlphaFold2021,
    author  = {Jumper, John and Evans, Richard and Pritzel, Alexander and Green, Tim and Figurnov, Michael and Ronneberger, Olaf and Tunyasuvunakool, Kathryn and Bates, Russ and {\v{Z}}{\'\i}dek, Augustin and Potapenko, Anna and Bridgland, Alex and Meyer, Clemens and Kohl, Simon A A and Ballard, Andrew J and Cowie, Andrew and Romera-Paredes, Bernardino and Nikolov, Stanislav and Jain, Rishub and Adler, Jonas and Back, Trevor and Petersen, Stig and Reiman, David and Clancy, Ellen and Zielinski, Michal and Steinegger, Martin and Pacholska, Michalina and Berghammer, Tamas and Bodenstein, Sebastian and Silver, David and Vinyals, Oriol and Senior, Andrew W and Kavukcuoglu, Koray and Kohli, Pushmeet and Hassabis, Demis},
    journal = {Nature},
    title   = {Highly accurate protein structure prediction with {AlphaFold}},
    year    = {2021},
    doi     = {10.1038/s41586-021-03819-2},
    note    = {(Accelerated article preview)},
}
You might also like...
Official implementation of
Official implementation of "StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation" (SIGGRAPH 2021)

StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation This repository contains the official PyTorch implementation of the following

Codes for the paper Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing
Codes for the paper Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing

Contrast and Mix (CoMix) The repository contains the codes for the paper Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Backgroun

Lightweight mmm - Lightweight (Bayesian) Media Mix Model

Lightweight (Bayesian) Media Mix Model This is not an official Google product. L

RetinaNet-PyTorch - A RetinaNet Pytorch Implementation on remote sensing images and has the similar mAP result with RetinaNet in MMdetection
A python software that can help blind people find things like laptops, phones, etc the same way a guide dog guides a blind person in finding his way.

GuidEye A python software that can help blind people find things like laptops, phones, etc the same way a guide dog guides a blind person in finding h

Standalone pre-training recipe with JAX+Flax

Sabertooth Sabertooth is standalone pre-training recipe based on JAX+Flax, with data pipelines implemented in Rust. It runs on CPU, GPU, and/or TPU, b

PyTorch implementation of saliency map-aided GAN for Auto-demosaic+denosing
PyTorch implementation of saliency map-aided GAN for Auto-demosaic+denosing

Saiency Map-aided GAN for RAW2RGB Mapping The PyTorch implementations and guideline for Saiency Map-aided GAN for RAW2RGB Mapping. 1 Implementations B

Efficient-GlobalPointer - Pytorch Efficient GlobalPointer
Efficient-GlobalPointer - Pytorch Efficient GlobalPointer

引言 感谢苏神带来的模型,原文地址:https://spaces.ac.cn/archives/8877 如何运行 对应模型EfficientGlobalPoi

Comments
  • Definition about 'ingoing' and 'outgoing'

    Definition about 'ingoing' and 'outgoing'

    Hi Luci!

    I've seen the lines define the 'ingoing' and 'outgoing': if mix == 'ingoing': self.mix_einsum_eq = '... i k d, ... j k d -> ... i j d' elif mix == 'outgoing': self.mix_einsum_eq = '... k j d, ... k i d -> ... i j d'

    but based on the original paper, I found maybe should be the inverse case, that: if mix == 'ingoing': self.mix_einsum_eq = '... k i d, ... k j d -> ... i j d' elif mix == 'outgoing': self.mix_einsum_eq = '... j k d, ... i k d -> ... i j d'

    based on what I understand, 'ingoing' should be the case that information comes from other edges (like 'ki','kj') aggregate togther and bind with edge 'ij'.

    Thanks for your contribution!

    opened by CiaoHe 1
Releases(0.0.3)
Owner
Phil Wang
Working with Attention. It's all we need
Phil Wang
CaLiGraph Ontology as a Challenge for Semantic Reasoners ([email protected]'21)

CaLiGraph for Semantic Reasoning Evaluation Challenge This repository contains code and data to use CaLiGraph as a benchmark dataset in the Semantic R

Nico Heist 0 Jun 08, 2022
Multi-modal Vision Transformers Excel at Class-agnostic Object Detection

Multi-modal Vision Transformers Excel at Class-agnostic Object Detection

Muhammad Maaz 206 Jan 04, 2023
3D Generative Adversarial Network

Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling This repository contains pre-trained models and sampling

Chengkai Zhang 791 Dec 20, 2022
Learning to Estimate Hidden Motions with Global Motion Aggregation

Learning to Estimate Hidden Motions with Global Motion Aggregation (GMA) This repository contains the source code for our paper: Learning to Estimate

Shihao Jiang (Zac) 221 Dec 18, 2022
[2021 MultiMedia] CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval

CONQUER: Contexutal Query-aware Ranking for Video Corpus Moment Retreival PyTorch implementation of CONQUER: Contexutal Query-aware Ranking for Video

Hou zhijian 23 Dec 26, 2022
This is an unofficial PyTorch implementation of Meta Pseudo Labels

This is an unofficial PyTorch implementation of Meta Pseudo Labels. The official Tensorflow implementation is here.

Jungdae Kim 320 Jan 08, 2023
This repo includes the supplementary of our paper "CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels"

Supplementary Materials for CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels This repository includes all supplementary mater

Zhiwei Li 0 Jan 05, 2022
Dual Attention Network for Scene Segmentation (CVPR2019)

Dual Attention Network for Scene Segmentation(CVPR2019) Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang,and Hanqing Lu Introduction W

Jun Fu 2.2k Dec 28, 2022
Code to reproduce the results in the paper "Tensor Component Analysis for Interpreting the Latent Space of GANs".

Tensor Component Analysis for Interpreting the Latent Space of GANs [ paper | project page ] Code to reproduce the results in the paper "Tensor Compon

James Oldfield 4 Jun 17, 2022
DiAne is a smart fuzzer for IoT devices

Diane Diane is a fuzzer for IoT devices. Diane works by identifying fuzzing triggers in the IoT companion apps to produce valid yet under-constrained

seclab 28 Jan 04, 2023
Calculates carbon footprint based on fuel mix and discharge profile at the utility selected. Can create graphs and tabular output for fuel mix based on input file of series of power drawn over a period of time.

carbon-footprint-calculator Conda distribution ~/anaconda3/bin/conda install anaconda-client conda-build ~/anaconda3/bin/conda config --set anaconda_u

Seattle university Renewable energy research 7 Sep 26, 2022
Improving adversarial robustness by a coupling rejection strategy

Adversarial Training with Rectified Rejection The code for the paper Adversarial Training with Rectified Rejection. Environment settings and libraries

Tianyu Pang 29 Jan 06, 2023
Deep Learning for Time Series Forecasting.

nixtlats:Deep Learning for Time Series Forecasting [nikstla] (noun, nahuatl) Period of time. State-of-the-art time series forecasting for pytorch. Nix

Nixtla 5 Dec 06, 2022
Reference implementation for Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Diffusion Probabilistic Models This repository provides a reference implementation of the method described in the paper: Deep Unsupervised Learning us

Jascha Sohl-Dickstein 238 Jan 02, 2023
Контрольная работа по математическим методам машинного обучения

ML-MathMethods-Test Контрольная работа по математическим методам машинного обучения. Вычисление основных статистик, диаграмм и графиков, проверка разл

Stas Ivanovskii 1 Jan 06, 2022
Benchmarking Pipeline for Prediction of Protein-Protein Interactions

B4PPI Benchmarking Pipeline for the Prediction of Protein-Protein Interactions How this benchmarking pipeline has been built, and how to use it, is de

Loïc Lannelongue 4 Jun 27, 2022
Implementation of Heterogeneous Graph Attention Network

HetGAN Implementation of Heterogeneous Graph Attention Network This is the code repository of paper "Prediction of Metro Ridership During the COVID-19

5 Dec 28, 2021
Source code for paper "ATP: AMRize Than Parse! Enhancing AMR Parsing with PseudoAMRs" @NAACL-2022

ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs Hi this is the source code of our paper "ATP: AMRize Then Parse! Enhancing AMR Parsing w

Chen Liang 13 Nov 23, 2022
QuALITY: Question Answering with Long Input Texts, Yes!

QuALITY: Question Answering with Long Input Texts, Yes! Authors: Richard Yuanzhe Pang,* Alicia Parrish,* Nitish Joshi,* Nikita Nangia, Jason Phang, An

ML² AT CILVR 61 Jan 02, 2023
Some useful blender add-ons for SMPL skeleton's poses and global translation.

Blender add-ons for SMPL skeleton's poses and trans There are two blender add-ons for SMPL skeleton's poses and trans.The first is for making an offli

犹在镜中 154 Jan 04, 2023