Python In-memory-cache Resources

Memorizing Transformers - Pytorch Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memori

Bailando Code for CVPR 2022 (oral) paper "Bailando: 3D dance generation via Actor-Critic GPT with Choreographic Memory" [Paper] | [Project Page] | [Vi

English | 简体中文 Easy Parallel Library Overview Easy Parallel Library (EPL) is a general and efficient library for distributed model training. Usability

FMEN Lowest memory consumption and second shortest runtime in NTIRE 2022 on Efficient Super-Resolution. Our paper: Fast and Memory-Efficient Network T

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

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 Overview k2hash_python is an official python driver for k2hash. Install Firstly you must install the k2hash shared library: curl -o- htt

Population One Localizer This is no longer needed as of the build shipped on 03/03/22, thank you bigbox :) Locally cache assets that are normally stre

Ego4D Episodic Memory Benchmark EGO4D is the world's largest egocentric (first p

CVE-2022-22536 SAP memory pipes desynchronization vulnerability(MPI) CVE-2022-22

Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder Authors: - Eashan Adhikarla - Dan Luo - Dr. Brian D. Davison Abstract Many

⏱ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor

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

A clipboard where a user can add and retrieve multiple items to and from (resp) from the clipboard cache.

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 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

Simple-DMA a simple Dual Memory Architecture for classifications. based on the paper Dual-Memory Deep Learning Architectures for Lifelong Learning of

R2Gen This is the implementation of Generating Radiology Reports via Memory-driven Transformer at EMNLP-2020. Citations If you use or extend our work,

A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most

News Headlines Generator bunnysaini/Generate-Headlines Goal This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural

Etag cache implementation for HTTP requests, to save request bandwidth for a non-modified response. Returns high-speed accessed dictionary data as cache.

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

Direct queries to Jira have two issues: they are sloooooow many queries are impo

HDM This is the repository for the Holographic Declarative Memory (HDM) module for Python ACT-R. This repository contains: documentation: a paper, con

Memory Compressed Attention Implementation of the Self-Attention layer of the proposed Memory-Compressed Attention, in Pytorch. This repository offers

GMAT: Global Memory Augmentation for Transformers This repository contains the accompanying code for the paper: "GMAT: Global Memory Augmentation for

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 Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-

This repository provides the official code for replicating experiments from the paper: Semi-Supervised Semantic Segmentation with Pixel-Level Contrast

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 This is a Sign Language Recognition service utilizing a deep learning model with Long Short-Term Memory to perform s

Paker Paker is module for importing Python packages/modules from dictionaries and JSON formatted documents. It was inspired by httpimporter. Important

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 CPU, GPU and memory profiler for Python by Emery Berger, Sam Stern, and Juan Altmayer Pizzorno. Scalene community Slack Ab

Caching tool for python, working with Redis single instance and Redis cluster mo

M²: Meshed-Memory Transformer This repository contains the reference code for the paper Meshed-Memory Transformer for Image Captioning (CVPR 2020). Pl

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 study for Complex case study, we've obtained failure causes by operational error and more deeply by design mistakes.

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

Introduction This project implements the optimization techniques proposed in Improving RNN Transducer Modeling for End-to-End Speech Recognition to re

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

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

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 Unofficially implements https://arxiv.org/abs/2112.05682 to get Linear Memory Cost on Attention (+

fastapi-cache Introduction fastapi-cache is a tool to cache fastapi response and function result, with backends support redis, memcache, and dynamodb.

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

memory_efficient_attention.pytorch A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory" (Rabe&Staats'21). def effic

Render template parts with extended cache control. Installation Install django-viewlet in your python environment $ pip install django-viewlet Support

Cashier Persistent caching for python functions Simply add a decorator to a python function and cache the results for future use. Extremely handy when

PyUpBit CS490 Large Scale Data Analytics — Implementation of Updatable Compressed Bitmap Indexing Paper Table of Contents About The Project Usage Cont

Python PG Extras Python port of Heroku PG Extras with several additions and improvements. The goal of this project is to provide powerful insights int

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

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

Self-paced Contrastive Learning (SpCL) The official repository for Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID

Concentration - Memory Game Concentration is a memory game written in Python, inspired by memory-game. Description As stated in the introduction of th

MTM This is the official repository of the paper: Article Reranking by Memory-enhanced Key Sentence Matching for Detecting Previously Fact-checked Cla

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

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 This is unofficial implementation of Self-attention Does Not Need O(n^2) Memory for Jax and PyTorch. Implementation is almo

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.

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 This repository hosts the source code for the journal article "Composing MPC with LQR and Neural Networks fo

httpx-cache is yet another implementation/port is a port of the caching algorithms in httplib2 for use with httpx Transport object.

A fork of the Flask-cache extension which adds easy cache support to Flask.

aiocache Asyncio cache supporting multiple backends (memory, redis and memcached). This library aims for simplicity over specialization. All caches co

Persistent, stale-free, local and cross-machine caching for Python functions.

CogniPy for Pandas - In-memory Graph Database and Knowledge Graph with Natural Language Interface Whats in the box Reasoning, exploration of RDF/OWL,

Minato Cache & file system for online resources in Python Features Minato enables you to: Download & cache online recsources minato supports the follo

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-

MemN2N Implementation of End-To-End Memory Networks with sklearn-like interface using Tensorflow. Tasks are from the bAbl dataset. Get Started git clo

N-Grammer - Pytorch Implementation of N-Grammer, augmenting Transformers with latent n-grams, in Pytorch Install $ pip install n-grammer-pytorch Usage

System Stats Visualizer This project is created to visualize the system statistics such as memory usage, CPU usage, memory accessible by process and m

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

Gradient Cached Dense Passage Retrieval Gradient Cached Dense Passage Retrieval (GC-DPR) - is an extension of the original DPR library. We introduce G

NLP-GPT-Upsampling This repository contains an implementation of Open AI's GPT Model. In particular, this implementation takes inspiration from the Ny

Pylomin Pylomin (PYtorch LOw-Memory INference) is a library for low-memory inferencing in PyTorch. Installation ... Usage For example, the following c

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

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 for Sequence Modeling This repository contains the implementation to reproduce the numerical experiments of the paper Long Expr

🐨 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

Few-shot Deep HDR Deghosting This repository contains code and pretrained models for our paper: Self-Gated Memory Recurrent Network for Efficient Scal

Efficient Multi-Organ Segmentation Using SpatialConfiguartion-Net with Low GPU Memory Requirements Our implementation used for the MICCAI 2021 FLARE C

Turdshovel Description Turdshovel is an interactive CLI tool that allows users to dump objects from .NET memory dumps without having to fully understa

Introduction Asynchronous cache manager designed for horizontally scaled web applications. NOTE: Currently has implementation only for FastAPI using R

A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for Trans

Magnitude: a fast, simple vector embedding utility library A feature-packed Python package and vector storage file format for utilizing vector embeddi

Mesa: A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for

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. 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. 😄

InvTorch: Memory-Efficient Invertible Functions This module extends the functionality of torch.utils.checkpoint.checkpoint to work with invertible fun

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

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

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

Trainig Script for Space Time Memory Network This codebase implemented training code for Space Time Memory Network with some cyclic features. Requirem

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 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.