Python Memory-efficient Resources

Efficient matrix representations for working with tabular data

CONetV2: Efficient Auto-Channel Size Optimization for CNNs Exciting News! CONetV2: Efficient Auto-Channel Size Optimization for CNNs has been accepted

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "

TorchArrow (Warning: Unstable Prototype) This is a prototype library currently under heavy development. It does not currently have stable releases, an

DeCLIP Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm. Our paper is available in arxiv Updates ** Ou

Code for DetCon This repository contains code for the ICCV 2021 paper "Efficient Visual Pretraining with Contrastive Detection" by Olivier J. Hénaff,

Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021) Kun Wang, Zhenyu Zhang, Zhiqiang Yan, X

Implementation of ICCV 2021 paper: PnP-DETR: Towards Efficient Visual Analysis with Transformers arxiv This repository is based on detr Recently, DETR

MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th

Unified-EPT Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation. Installation Linux, CUDA=10.0,

Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.

AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition [ArXiv] [Project Page] This repository is the official implementation of AdaMML:

Data Efficient Decision Making

Project Azua 0. Overview Many modern AI algorithms are known to be data-hungry, whereas human decision-making is much more efficient. The human can re

PMFuzz PMFuzz is a testcase generation tool to generate high-value tests cases for PM testing tools (XFDetector, PMDebugger, PMTest and Pmemcheck) If

MEDS: Enhancing Memory Error Detection for Large-Scale Applications Prerequisites cmake and clang Build MEDS supporting compiler $ make Build Using Do

MemLock: Memory Usage Guided Fuzzing This repository provides the tool and the evaluation subjects for the paper "MemLock: Memory Usage Guided Fuzzing

BaseSAFE This repository contains the BaseSAFE Rust APIs, introduced by "BaseSAFE: Baseband SAnitized Fuzzing through Emulation". The example/ directo

Sync Toolbox - Python package with reference implementations for efficient, robust, and accurate music synchronization based on dynamic time warping (DTW)

Why efficient Python? Because using Python more efficiently will make your code more readable and run more efficiently.

Overview A python script developed to process Windows memory images based on triage type. Requirements Python3 Bulk Extractor Volatility2 with Communi

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)

Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

An efficient 3D semantic segmentation framework for Urban-scale point clouds like SensatUrban, Campus3D, etc.

300+ Python Interview Questions

PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

Tevatron Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models. The toolkit has a modularized

EARL This repository provides a simple implementation of the work "Efficient Sparse Attacks on Videos using Reinforcement Learning" Example: Demo: Her

Introduction SCRFD is an efficient high accuracy face detection approach which initially described in Arxiv. Performance Precision, flops and infer ti

TorchX TorchX: A PyTorch Extension Library for More Efficient Deep Learning. @misc{torchx, author = {Ansheng You and Changxu Wang}, title = {T

InsGen - Data-Efficient Instance Generation from Instance Discrimination Data-Efficient Instance Generation from Instance Discrimination Ceyuan Yang,

Hierarchical Transformer Memory (HTM) - Pytorch Implementation of Hierarchical Transformer Memory (HTM) for Pytorch. This Deepmind paper proposes a si

Efficient Conformer: Progressive Downsampling and Grouped Attention for Automatic Speech Recognition Official implementation of the Efficient Conforme

Efficient ML solutions for long-tailed demands.

Searching for Efficient Multi-Stage Vision Transformers This repository contains the official Pytorch implementation of "Searching for Efficient Multi

Lorien: A Unified Infrastructure for Efficient Deep Learning Workloads Delivery Lorien is an infrastructure to massively explore/benchmark the best sc

rl: An efficient framework for reinforcement learning Requirements Introduction PPO Test Requirements name version Python =3.7 numpy =1.19 torch =1

Aqueduct Framework for creating efficient data processing pipelines. Contact Feel free to ask questions in telegram t.me/avito-ml Key Features Increas

AdaFocus (ICCV 2021) This repo contains the official code and pre-trained models for AdaFocus. Adaptive Focus for Efficient Video Recognition Referenc

Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom Sample on-line plotting while training(avg loss)/testing(writ

PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based

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

RevLib Simple and efficient RevNet-Library with DeepSpeed support Features Half the constant memory usage and faster than RevNet libraries Less memory

Pixel Difference Convolution This repository contains the PyTorch implementation for "Pixel Difference Networks for Efficient Edge Detection" by Zhuo

Exploring Classification Equilibrium in Long-Tailed Object Detection (LOCE, ICCV 2021) Paper Introduction The conventional detectors tend to make imba

State Entropy Maximization with Random Encoders for Efficient Exploration (RE3) (ICML 2021) Code for State Entropy Maximization with Random Encoders f

MixFaceNets This is the official repository of the paper: MixFaceNets: Extremely Efficient Face Recognition Networks. (Accepted in IJCB2021) https://i

ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search [paper] Introduction This is the official implementation of ViPNAS: Efficient V

scanpat Tool for generating Frida Memory.scan() compatible instruction search patterns. Powered by r2. Examples $ ./scanpat.py arm.ks:64 'sub sp, sp,

Nasdaq Cloud Data Service (NCDS) Nasdaq Cloud Data Service (NCDS) provides a modern and efficient method of delivery for realtime exchange data and ot

Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp

Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l

VisualGPT Our Paper VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioning Main Architecture of Our VisualGPT Downloa

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Selection via Proxy: Efficient Data Selection for Deep Learning This repository contains a refactored implementation of "Selection via Proxy: Efficien

Gradient Cache Gradient Cache is a simple technique for unlimitedly scaling contrastive learning batch far beyond GPU memory constraint. This means tr

Active Testing: Sample-Efficient Model Evaluation Hi, good to see you here! 👋 This is code for "Active Testing: Sample-Efficient Model Evaluation". P

Differentiable Neural Computers and family, for Pytorch Includes: Differentiable Neural Computers (DNC) Sparse Access Memory (SAM) Sparse Differentiab

Kunyu(坤舆) - More efficient corporate asset collection English | 中文文档 0x00 Introduce Tool introduction Kunyu (kunyu), whose name is taken from , is act

Gradient Episodic Memory for Continual Learning Source code for the paper: @inproceedings{GradientEpisodicMemory, title={Gradient Episodic Memory

In-Place Activated BatchNorm In-Place Activated BatchNorm for Memory-Optimized Training of DNNs In-Place Activated BatchNorm (InPlace-ABN) is a novel

Bottom-Up and Top-Down Attention for Visual Question Answering An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge. The

Efficient Neural Architecture Search (ENAS) in PyTorch PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing. ENAS red

Self-Tuning for Data-Efficient Deep Learning This repository contains the implementation code for paper: Self-Tuning for Data-Efficient Deep Learning

Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod

Bridging Multi-Task Learning and Meta-Learning Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Trainin

LTP: Learned Token Pruning for Transformers Check our paper for more details. Installation We follow the same installation procedure as the original H

Triangle Multiplicative Module - Pytorch Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or c

Parallelformers: An Efficient Model Parallelization Toolkit for Deployment

ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A

The Power of Scale for Parameter-Efficient Prompt Tuning Implementation of soft embeddings from https://arxiv.org/abs/2104.08691v1 using Pytorch and H

Efficient Self-Supervised Vision Transformers (EsViT) PyTorch implementation for EsViT, built with two techniques: A multi-stage Transformer architect

StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking Datasets You can download datasets that have been pre-pr

Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness This repository contains the code used for the exper

STMTrack This is the official implementation of the paper: STMTrack: Template-free Visual Tracking with Space-time Memory Networks. Setup Prepare Anac

neural waveshaping synthesis real-time neural audio synthesis in the waveform domain paper • website • colab • audio by Ben Hayes, Charalampos Saitis,

LiDAR R-CNN: An Efficient and Universal 3D Object Detector Introduction This is the official code of LiDAR R-CNN: An Efficient and Universal 3D Object

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

Seg_Uncertainty In this repo, we provide the code for the two papers, i.e., MRNet：Unsupervised Scene Adaptation with Memory Regularization in vivo, IJ

MemStream Implementation of MemStream: Memory-Based Anomaly Detection in Multi-Aspect Streams with Concept Drift . Siddharth Bhatia, Arjit Jain, Shivi

Heterogeneous INteract and aggreGatE (GraphHINGE) This is a pytorch implementation of GraphHINGE model. This is the experiment code in the following w

Chasing Sparsity in Vision Transformers: An End-to-End Exploration Codes for [Preprint] Chasing Sparsity in Vision Transformers: An End-to-End Explora

Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥

Data Efficient Stagewise Knowledge Distillation Table of Contents Data Efficient Stagewise Knowledge Distillation Table of Contents Requirements Image

AnalyticMesh Analytic Marching is an exact meshing solution from neural networks. Compared to standard methods, it completely avoids geometric and top

PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

seno-blockchain https://seno.uno Seno is just a fork of Chia, designed to be efficient, decentralized, and secure. Here are some of the features and b

DatasetGAN This is the official code and data release for: DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort Yuxuan Zhang*, Huan Li

NodePiece - Compositional and Parameter-Efficient Representations for Large Knowledge Graphs NodePiece is a "tokenizer" for reducing entity vocabulary

Pretraining Representations For Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Ch

We evaluated the baseline with Resnet50 and Efficienet-v2 without using pretrained models. Also Resnet50-IBN-A and Efficientnet-v2 using pretrained on ImageNet. We used two datasets: Market-1501 and CUHK03.

Pipeline For NLP with Bloom's Taxonomy Using Improved Question Classification and Question Generation using Deep Learning This repository contains all

SinIR (Official Implementation) Requirements To install requirements: pip install -r requirements.txt We used Python 3.7.4 and f-strings which are in

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Figure 1: Performance of SegFormer-B0 to SegFormer-B5. Project page

AnimDL - Download & Stream Your Favorite Anime AnimDL is an incredibly powerful tool for downloading and streaming anime. Core features Abuses the dev

EPSANet：An Efficient Pyramid Split Attention Block on Convolutional Neural Network This repo contains the official Pytorch implementaion code and conf

HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p