A Pytorch Implementation for Compact Bilinear Pooling.

Overview

CompactBilinearPooling-Pytorch

A Pytorch Implementation for Compact Bilinear Pooling. Adapted from tensorflow_compact_bilinear_pooling

Prerequisites

Install pytorch_fft by

pip install pytorch_fft

Usage

from torch import nn
from torch.autograd import Variable
from CompactBilinearPooling import CompactBilinearPooling

bottom1 = Variable(torch.randn(128, 512, 14, 14)).cuda()
bottom2 = Variable(torch.randn(128, 512, 14, 14)).cuda()

layer = CompactBilinearPooling(512, 512, 8000)
layer.cuda()
layer.train()

out = layer(bottom1, bottom2)

Reference

Yang Gao, et al. "Compact Bilinear Pooling." in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2016).
Akira Fukui, et al. "Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding." arXiv preprint arXiv:1606.01847 (2016).
TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards

TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards. It can reduce GPU memory and scale up the training when the model has massive linear layers (e.g., ViT, BERT and

Kaiyu Yue 275 Nov 22, 2022
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
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 pure Python implementation of Compact Bilinear Pooling and Count Sketch for PyTorch.

Compact Bilinear Pooling for PyTorch. This repository has a pure Python implementation of Compact Bilinear Pooling and Count Sketch for PyTorch. This

Grégoire Payen de La Garanderie 234 Dec 07, 2022
torch-optimizer -- collection of optimizers for Pytorch

torch-optimizer torch-optimizer -- collection of optimizers for PyTorch compatible with optim module. Simple example import torch_optimizer as optim

Nikolay Novik 2.6k Jan 03, 2023
An implementation of Performer, a linear attention-based transformer, in Pytorch

Performer - Pytorch An implementation of Performer, a linear attention-based transformer variant with a Fast Attention Via positive Orthogonal Random

Phil Wang 900 Dec 22, 2022
Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric

Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric

Quiver Team 221 Dec 22, 2022
PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

README TabNet : Attentive Interpretable Tabular Learning This is a pyTorch implementation of Tabnet (Arik, S. O., & Pfister, T. (2019). TabNet: Attent

DreamQuark 2k Dec 27, 2022
GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks

GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten

Joel Huang 15 Dec 24, 2022
Bunch of optimizer implementations in PyTorch

Bunch of optimizer implementations in PyTorch

Hyeongchan Kim 76 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
On the Variance of the Adaptive Learning Rate and Beyond

RAdam On the Variance of the Adaptive Learning Rate and Beyond We are in an early-release beta. Expect some adventures and rough edges. Table of Conte

Liyuan Liu 2.5k Dec 27, 2022
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

News March 3: v0.9.97 has various bug fixes and improvements: Bug fixes for NTXentLoss Efficiency improvement for AccuracyCalculator, by using torch i

Kevin Musgrave 5k Jan 02, 2023
Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch.

Tez: a simple pytorch trainer NOTE: Currently, we are not accepting any pull requests! All PRs will be closed. If you want a feature or something does

abhishek thakur 1.1k Jan 04, 2023
A Closer Look at Structured Pruning for Neural Network Compression

A Closer Look at Structured Pruning for Neural Network Compression Code used to reproduce experiments in https://arxiv.org/abs/1810.04622. To prune, w

Bayesian and Neural Systems Group 140 Dec 05, 2022
A very simple and small path tracer written in pytorch meant to be run on the GPU

MentisOculi Pytorch Path Tracer A very simple and small path tracer written in pytorch meant to be run on the GPU Why use pytorch and not some other c

Matthew B. Mirman 222 Dec 01, 2022
Fast, general, and tested differentiable structured prediction in PyTorch

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

HNLP 1.1k Jan 07, 2023
Pytorch bindings for Fortran

Pytorch bindings for Fortran

Dmitry Alexeev 46 Dec 29, 2022
270 Dec 24, 2022
A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).

Code release for "Bayesian Compression for Deep Learning" In "Bayesian Compression for Deep Learning" we adopt a Bayesian view for the compression of

Karen Ullrich 190 Dec 30, 2022