164 Repositories
Python episodic-memory Libraries
Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memories using approximate nearest neighbors, in Pytorch
Memorizing Transformers - Pytorch Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memori
Code for CVPR 2022 paper "Bailando: 3D dance generation via Actor-Critic GPT with Choreographic Memory"
Bailando Code for CVPR 2022 (oral) paper "Bailando: 3D dance generation via Actor-Critic GPT with Choreographic Memory" [Paper] | [Project Page] | [Vi
Easy Parallel Library (EPL) is a general and efficient deep learning framework for distributed model training.
English | 简体中文 Easy Parallel Library Overview Easy Parallel Library (EPL) is a general and efficient library for distributed model training. Usability
Lowest memory consumption and second shortest runtime in NTIRE 2022 challenge on Efficient Super-Resolution
FMEN Lowest memory consumption and second shortest runtime in NTIRE 2022 on Efficient Super-Resolution. Our paper: Fast and Memory-Efficient Network T
Implementation of MeMOT - Multi-Object Tracking with Memory - in Pytorch
MeMOT - Pytorch (wip) Implementation of MeMOT - Multi-Object Tracking with Memory - in Pytorch. This paper is just one in a line of work, but importan
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(
K2HASH Python library - NoSQL Key Value Store(KVS) library
k2hash_python Overview k2hash_python is an official python driver for k2hash. Install Firstly you must install the k2hash shared library: curl -o- htt
Episodic-memory - Ego4D Episodic Memory Benchmark
Ego4D Episodic Memory Benchmark EGO4D is the world's largest egocentric (first p
CVE-2022-22536 - SAP memory pipes(MPI) desynchronization vulnerability CVE-2022-22536
CVE-2022-22536 SAP memory pipes desynchronization vulnerability(MPI) CVE-2022-22
Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder
Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder Authors: - Eashan Adhikarla - Dan Luo - Dr. Brian D. Davison Abstract Many
Easily benchmark PyTorch model FLOPs, latency, throughput, max allocated memory and energy consumption
⏱ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor
FewBit — a library for memory efficient training of large neural networks
FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back
This speeds up PyCharm's package index processes and avoids CPU & memory overloading
This speeds up PyCharm's package index processes and avoids CPU & memory overloading
Decorators for maximizing memory utilization with PyTorch & CUDA
torch-max-mem This package provides decorators for memory utilization maximization with PyTorch and CUDA by starting with a maximum parameter size and
Rip Raw - a small tool to analyse the memory of compromised Linux systems
Rip Raw Rip Raw is a small tool to analyse the memory of compromised Linux systems. It is similar in purpose to Bulk Extractor, but particularly focus
The Dual Memory is build from a simple CNN for the deep memory and Linear Regression fro the fast Memory
Simple-DMA a simple Dual Memory Architecture for classifications. based on the paper Dual-Memory Deep Learning Architectures for Lifelong Learning of
Generating Radiology Reports via Memory-driven Transformer
R2Gen This is the implementation of Generating Radiology Reports via Memory-driven Transformer at EMNLP-2020. Citations If you use or extend our work,
PyTorchMemTracer - Depict GPU memory footprint during DNN training of PyTorch
A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most
This project generates news headlines using a Long Short-Term Memory (LSTM) neural network.
News Headlines Generator bunnysaini/Generate-Headlines Goal This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural
Visual Python and C++ nanosecond profiler, logger, tests enabler
Look into Palanteer and get an omniscient view of your program Palanteer is a set of lean and efficient tools to improve the quality of software, for
Holographic Declarative Memory for Python ACT-R
HDM This is the repository for the Holographic Declarative Memory (HDM) module for Python ACT-R. This repository contains: documentation: a paper, con
Implementation of Memory-Compressed Attention, from the paper "Generating Wikipedia By Summarizing Long Sequences"
Memory Compressed Attention Implementation of the Self-Attention layer of the proposed Memory-Compressed Attention, in Pytorch. This repository offers
The accompanying code for the paper "GMAT: Global Memory Augmentation for Transformers" (Ankit Gupta and Jonathan Berant).
GMAT: Global Memory Augmentation for Transformers This repository contains the accompanying code for the paper: "GMAT: Global Memory Augmentation for
Implementation of Memformer, a Memory-augmented Transformer, in Pytorch
Memformer - Pytorch Implementation of Memformer, a Memory-augmented Transformer, in Pytorch. It includes memory slots, which are updated with attentio
GLNet for Memory-Efficient Segmentation of Ultra-High Resolution Images
GLNet for Memory-Efficient Segmentation of Ultra-High Resolution Images Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank
This repository provides the official code for replicating experiments from the paper: Semi-Supervised Semantic Segmentation with Pixel-Level Contrast
Multi-Stage Episodic Control for Strategic Exploration in Text Games
XTX: eXploit - Then - eXplore Requirements First clone this repo using git clone https://github.com/princeton-nlp/XTX.git Please create two conda envi
A wrapper around ffmpeg to make it work in a concurrent and memory-buffered fashion.
Media Fixer Have you ever had a film or TV show that your TV wasn't able to play its audio? Well this program is for you. Media Fixer is a program whi
Sign Language Recognition service utilizing a deep learning model with Long Short-Term Memory to perform sign language recognition.
Sign Language Recognition Service This is a Sign Language Recognition service utilizing a deep learning model with Long Short-Term Memory to perform s
Import Python modules from dicts and JSON formatted documents.
Paker Paker is module for importing Python packages/modules from dictionaries and JSON formatted documents. It was inspired by httpimporter. Important
Module for remote in-memory Python package/module loading through HTTP/S
httpimport Python's missing feature! The feature has been suggested in Python Mailing List Remote, in-memory Python package/module importing through H
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python
Scalene: a high-performance CPU, GPU and memory profiler for Python by Emery Berger, Sam Stern, and Juan Altmayer Pizzorno. Scalene community Slack Ab
Meshed-Memory Transformer for Image Captioning. CVPR 2020
M²: Meshed-Memory Transformer This repository contains the reference code for the paper Meshed-Memory Transformer for Image Captioning (CVPR 2020). Pl
PyTorch code for MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning
MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning PyTorch code for our ACL 2020 paper "MART: Memory-Augmented Recur
Predictive Maintenance LSTM
Predictive-Maintenance-LSTM - Predictive maintenance study for Complex case study, we've obtained failure causes by operational error and more deeply by design mistakes.
Python function to construct an ODS spreadsheet on the fly - without having to store the entire file in memory or disk
stream-write-ods Python function to construct an ODS (OpenDocument Spreadsheet) on the fly - without having to store the entire file in memory or disk
Memory efficient transducer loss computation
Introduction This project implements the optimization techniques proposed in Improving RNN Transducer Modeling for End-to-End Speech Recognition to re
Memory-efficient optimum einsum using opt_einsum planning and PyTorch kernels.
opt-einsum-torch There have been many implementations of Einstein's summation. numpy's numpy.einsum is the least efficient one as it only runs in sing
Python function to construct a ZIP archive with on the fly - without having to store the entire ZIP in memory or disk
Python function to construct a ZIP archive with on the fly - without having to store the entire ZIP in memory or disk
Robust, highly tunable and easy-to-integrate in-memory cache solution written in pure Python, with no dependencies.
Omoide Cache Caching doesn't need to be hard anymore. With just a few lines of code Omoide Cache will instantly bring your Python services to the next
Implementation of Memory-Efficient Neural Networks with Multi-Level Generation, ICCV 2021
Memory-Efficient Multi-Level In-Situ Generation (MLG) By Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen and David Z. Pan
Attention for PyTorch with Linear Memory Footprint
Attention for PyTorch with Linear Memory Footprint Unofficially implements https://arxiv.org/abs/2112.05682 to get Linear Memory Cost on Attention (+
This script allows you to retrieve all functions / variables names of a Python code, and the variables values.
Memory Extractor This script allows you to retrieve all functions / variables names of a Python code, and the variables values. How to use it ? The si
A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory"
memory_efficient_attention.pytorch A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory" (Rabe&Staats'21). def effic
Python Implementation of Scalable In-Memory Updatable Bitmap Indexing
PyUpBit CS490 Large Scale Data Analytics — Implementation of Updatable Compressed Bitmap Indexing Paper Table of Contents About The Project Usage Cont
Simple embedded in memory json database
dbj dbj is a simple embedded in memory json database. It is easy to use, fast and has a simple query language. The code is fully documented, tested an
A low-impact profiler to figure out how much memory each task in Dask is using
dask-memusage If you're using Dask with tasks that use a lot of memory, RAM is your bottleneck for parallelism. That means you want to know how much m
[NeurIPS-2020] Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID.
Self-paced Contrastive Learning (SpCL) The official repository for Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
Memory game in Python
Concentration - Memory Game Concentration is a memory game written in Python, inspired by memory-game. Description As stated in the introduction of th
Article Reranking by Memory-enhanced Key Sentence Matching for Detecting Previously Fact-checked Claims.
MTM This is the official repository of the paper: Article Reranking by Memory-enhanced Key Sentence Matching for Detecting Previously Fact-checked Cla
Library for Memory Trace Statistics in Python
Memory Search Library for Memory Trace Statistics in Python The library uses tracemalloc as a core module, which is why it is only available for Pytho
A universal memory dumper using Frida
Fridump Fridump (v0.1) is an open source memory dumping tool, primarily aimed to penetration testers and developers. Fridump is using the Frida framew
Memory Efficient Attention (O(sqrt(n)) for Jax and PyTorch
Memory Efficient Attention This is unofficial implementation of Self-attention Does Not Need O(n^2) Memory for Jax and PyTorch. Implementation is almo
BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches
BLEND is a mechanism that can efficiently find fuzzy seed matches between sequences to significantly improve the performance and accuracy while reducing the memory space usage of two important applications: 1) finding overlapping reads and 2) read mapping. Described by Firtina et al.
A Python dictionary implementation designed to act as an in-memory cache for FaaS environments
faas-cache-dict A Python dictionary implementation designed to act as an in-memory cache for FaaS environments. Formally you would describe this a mem
Memory-Augmented Model Predictive Control
Memory-Augmented Model Predictive Control This repository hosts the source code for the journal article "Composing MPC with LQR and Neural Networks fo
Asyncio cache manager for redis, memcached and memory
aiocache Asyncio cache supporting multiple backends (memory, redis and memcached). This library aims for simplicity over specialization. All caches co
In-memory Graph Database and Knowledge Graph with Natural Language Interface, compatible with Pandas
CogniPy for Pandas - In-memory Graph Database and Knowledge Graph with Natural Language Interface Whats in the box Reasoning, exploration of RDF/OWL,
Official PyTorch implementation of RIO
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection Figure 1: Our proposed Resampling at image-level and obect-
End-To-End Memory Network using Tensorflow
MemN2N Implementation of End-To-End Memory Networks with sklearn-like interface using Tensorflow. Tasks are from the bAbl dataset. Get Started git clo
Implementation of N-Grammer, augmenting Transformers with latent n-grams, in Pytorch
N-Grammer - Pytorch Implementation of N-Grammer, augmenting Transformers with latent n-grams, in Pytorch Install $ pip install n-grammer-pytorch Usage
This project is created to visualize the system statistics such as memory usage, CPU usage, memory accessible by process and much more using Kibana Dashboard with Elasticsearch.
System Stats Visualizer This project is created to visualize the system statistics such as memory usage, CPU usage, memory accessible by process and m
End-2-end speech synthesis with recurrent neural networks
Introduction New: Interactive demo using Google Colaboratory can be found here TTS-Cube is an end-2-end speech synthesis system that provides a full p
Train Dense Passage Retriever (DPR) with a single GPU
Gradient Cached Dense Passage Retrieval Gradient Cached Dense Passage Retrieval (GC-DPR) - is an extension of the original DPR library. We introduce G
Modified GPT using average pooling to reduce the softmax attention memory constraints.
NLP-GPT-Upsampling This repository contains an implementation of Open AI's GPT Model. In particular, this implementation takes inspiration from the Ny
A library for low-memory inferencing in PyTorch.
Pylomin Pylomin (PYtorch LOw-Memory INference) is a library for low-memory inferencing in PyTorch. Installation ... Usage For example, the following c
A simple, lightweight Discord bot running with only 512 MB memory on Heroku
Haruka This used to be a music bot, but people keep using it for NSFW content. Can't everyone be less horny? Bot commands See the built-in help comman
Memory tests solver with using OpenCV
Human Benchmark project This project is OpenCV based programs which are puzzle solvers for 7 different games for https://humanbenchmark.com/. made as
Long Expressive Memory (LEM)
Long Expressive Memory for Sequence Modeling This repository contains the implementation to reproduce the numerical experiments of the paper Long Expr
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
[IEEE Transactions on Computational Imaging] Self-Gated Memory Recurrent Network for Efficient Scalable HDR Deghosting
Few-shot Deep HDR Deghosting This repository contains code and pretrained models for our paper: Self-Gated Memory Recurrent Network for Efficient Scal
Our implementation used for the MICCAI 2021 FLARE Challenge titled 'Efficient Multi-Organ Segmentation Using SpatialConfiguartion-Net with Low GPU Memory Requirements'.
Efficient Multi-Organ Segmentation Using SpatialConfiguartion-Net with Low GPU Memory Requirements Our implementation used for the MICCAI 2021 FLARE C
Turdshovel is an interactive CLI tool that allows users to dump objects from .NET memory dumps
Turdshovel Description Turdshovel is an interactive CLI tool that allows users to dump objects from .NET memory dumps without having to fully understa
This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".
A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for Trans
A fast, efficient universal vector embedding utility package.
Magnitude: a fast, simple vector embedding utility library A feature-packed Python package and vector storage file format for utilizing vector embeddi
This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".
Mesa: A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for
This repo contains implementation of different architectures for emotion recognition in conversations.
Emotion Recognition in Conversations Updates 🔥 🔥 🔥 Date Announcements 03/08/2021 🎆 🎆 We have released a new dataset M2H2: A Multimodal Multiparty
ZipFly is a zip archive generator based on zipfile.py
ZipFly is a zip archive generator based on zipfile.py. It was created by Buzon.io to generate very large ZIP archives for immediate sending out to clients, or for writing large ZIP archives without memory inflation.
Like htop (CPU and memory usage), but for your case LEDs. 😄
Like htop (CPU and memory usage), but for your case LEDs. 😄
InvTorch: memory-efficient models with invertible functions
InvTorch: Memory-Efficient Invertible Functions This module extends the functionality of torch.utils.checkpoint.checkpoint to work with invertible fun
Code for the paper "Attention Approximates Sparse Distributed Memory"
Attention Approximates Sparse Distributed Memory - Codebase This is all of the code used to run analyses in the paper "Attention Approximates Sparse D
Demo of using DataLoader to prevent out of memory
Demo of using DataLoader to prevent out of memory
A customisable game where you have to quickly click on black tiles in order of appearance while avoiding clicking on white squares.
W.I.P-Aim-Memory-Game A customisable game where you have to quickly click on black tiles in order of appearance while avoiding clicking on white squar
python's memory-saving dictionary data structure
ConstDict python代替的Dict数据结构 若字典不会增加字段,只读/原字段修改 使用ConstDict可节省内存 Dict()内存主要消耗的地方: 1、Dict扩容机制,预留内存空间 2、Dict也是一个对象,内部会动态维护__dict__,增加slot类属性可以节省内容 节省内存大小
training script for space time memory network
Trainig Script for Space Time Memory Network This codebase implemented training code for Space Time Memory Network with some cyclic features. Requirem
SEC'21: Sparse Bitmap Compression for Memory-Efficient Training onthe Edge
Training Deep Learning Models on The Edge Training on the Edge enables continuous learning from new data for deployed neural networks on memory-constr
Playing memory game is fun and the more harder it is the more challenging it is.
Playing memory game is fun and the more harder it is the more challenging it is. Playing thi sgame make us stress free and also happy. So, I have decided to make a memory Game which people can play while doing work. To pass your time and to be little happy, play this wonderful memory game - **JACKPOT** while doing your work and sitting in front of your computer.
Space Time Recurrent Memory Network - Pytorch
Space Time Recurrent Memory Network - Pytorch (wip) Implementation of Space Time Recurrent Memory Network, recurrent network competitive with attentio
PyTorch implementation of Memory-based semantic segmentation for off-road unstructured natural environments.
MemSeg: Memory-based semantic segmentation for off-road unstructured natural environments Introduction This repository is a PyTorch implementation of
Harmonic Memory Networks for Graph Completion
HMemNetworks Code and documentation for Harmonic Memory Networks, a series of models for compositionally assembling representations of graph elements
Rasberry Pie GPIO memory game. Press the corresponding key to the lit LED.
RPie-keyboard-game Rasberry Pie GPIO memory game. Press the corresponding key to the lit LED. Randem LED (general output) is lit up on rasberrypi rand
CPython extension implementing Shared Transactional Memory with native-looking interface
CPython extension implementing Shared Transactional Memory with native-looking interface
Application for easy configuration of swap file and swappiness priority in slackware and others linux distributions.
Swap File Program created with the objective of assisting in the configuration of swap file in Distributions such as Slackware. Required packages: pyt
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr
LSTMs (Long Short Term Memory) RNN for prediction of price trends
Price Prediction with Recurrent Neural Networks LSTMs BTC-USD price prediction with deep learning algorithm. Artificial Neural Networks specifically L
Simple package to enhance Python's concurrent.futures for memory efficiency
future-map is a Python library to use together with the official concurrent.futures module.
PyTorch implementation of "Dataset Knowledge Transfer for Class-Incremental Learning Without Memory" (WACV2022)
Dataset Knowledge Transfer for Class-Incremental Learning Without Memory [Paper] [Slides] Summary Introduction Installation Reproducing results Citati
Speeding-Up Back-Propagation in DNN: Approximate Outer Product with Memory
Approximate Outer Product Gradient Descent with Memory Code for the numerical experiment of the paper Speeding-Up Back-Propagation in DNN: Approximate
This is the repo for the paper "Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement".
Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement This is the repository for the paper "Improving the Accuracy-Memory Trad