Python Memory-trainer Resources

Price Prediction with Recurrent Neural Networks LSTMs BTC-USD price prediction with deep learning algorithm. Artificial Neural Networks specifically L

future-map is a Python library to use together with the official concurrent.futures module.

Dataset Knowledge Transfer for Class-Incremental Learning Without Memory [Paper] [Slides] Summary Introduction Installation Reproducing results Citati

Approximate Outer Product Gradient Descent with Memory Code for the numerical experiment of the paper Speeding-Up Back-Propagation in DNN: Approximate

Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement This is the repository for the paper "Improving the Accuracy-Memory Trad

HF2-VAD Offcial implementation of "A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Predictio

Parquet benchmarks This repository contains a set of benchmarks of different implementations of Parquet (storage format) - Arrow (in-memory format).

KaGRMN-DSG_ABSA This repository contains the PyTorch source Code for our paper: Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated

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

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

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

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

300+ Python Interview Questions

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

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

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

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

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

Alex's PyTorch Personal Trainer (ptpt) (name subject to change) This repository contains my personal lightweight framework for deep learning projects

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

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

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

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

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

STCN Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [a

Memory In Memory Networks It is based on the paper Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spati

Learning Associative Inference Using Fast Weight Memory This repository contains the offical code for the paper Learning Associative Inference Using F

ActNN : Activation Compressed Training This is the official project repository for ActNN: Reducing Training Memory Footprint via 2-Bit Activation Comp

iterable-subprocess Python utility function to communicate with a subprocess using iterables: for when data is too big to fit in memory and has to be

Elara DB is an easy to use, lightweight NoSQL database written for python that can also be used as a fast in-memory cache for JSON-serializable data. Includes various methods and features to manipulate data structures in-memory, protect database files and export data.

Python function to stream unzip all the files in a ZIP archive: without loading the entire ZIP file or any of its files into memory at once

GAN Memory for Lifelong learning This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting. Please consider citing our paper

RMNet This repository contains the source code for the paper Efficient Regional Memory Network for Video Object Segmentation. Cite this work @inprocee

Rainbow Memory: Continual Learning with a Memory of Diverse Samples

Training-code-of-STM This repository fully reproduces Space-Time Memory Networks Performance on Davis17 val set&Weights backbone training stage traini

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

Segcache: a memory-efficient and scalable in-memory key-value cache for small objects This repo contains the code of Segcache described in the followi

This is an asynchonous Python client for Tile38 that allows for fast and easy interaction with the worlds fastest in-memory geodatabase Tile38.

InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea

PINCE is a front-end/reverse engineering tool for the GNU Project Debugger (GDB), focused on games. However, it can be used for any reverse-engi

Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 Billion Parameters) on a single 16 GB VRAM V100 Google Cloud instance with Huggingfa

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

PyTorch Implementation of Differentiable ODE Solvers This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpr

ipyexperiments jupyter/ipython experiment containers and utils for profiling and reclaiming GPU and general RAM, and detecting memory leaks. About Thi

BatchFlow BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflo

What is Vaex? Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular data

lazyprofiler Lazy Profiler is a simple utility to collect CPU, GPU, RAM and GPU Memory stats while the program is running. Installation Use the packag

BitPack is a practical tool that can efficiently save quantized neural network models with mixed bitwidth.

Elegy Elegy is a framework-agnostic Trainer interface for the Jax ecosystem. Main Features Easy-to-use: Elegy provides a Keras-like high-level API tha

NuPIC Numenta Platform for Intelligent Computing The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implem

Memory Profiler This is a python module for monitoring memory consumption of a process as well as line-by-line analysis of memory consumption for pyth

Diamond Diamond is a python daemon that collects system metrics and publishes them to Graphite (and others). It is capable of collecting cpu, memory,

scalene: a high-performance CPU and memory profiler for Python by Emery Berger 中文版本 (Chinese version) About Scalene % pip install -U scalene Scalen

README for pympler Before installing Pympler, try it with your Python version: python setup.py try If any errors are reported, check whether your Pyt

Memory Profiler This is a python module for monitoring memory consumption of a process as well as line-by-line analysis of memory consumption for pyth

Home Install Documentation Download Forum Blog Funding What's new Summary psutil (process and system utilities) is a cross-platform library for retrie

FlatBuffers FlatBuffers is a cross platform serialization library architected for maximum memory efficiency. It allows you to directly access serializ

Feedback Transformer - Pytorch Simple implementation of Feedback Transformer in Pytorch. They improve on Transformer-XL by having each token have acce

Annoy Annoy (Approximate Nearest Neighbors Oh Yeah) is a C++ library with Python bindings to search for points in space that are close to a given quer

Colibri Core by Maarten van Gompel, [email protected], Radboud University Nijmegen Licensed under GPLv3 (See http://www.gnu.org/licenses/gpl-3.0.html

Annoy Annoy (Approximate Nearest Neighbors Oh Yeah) is a C++ library with Python bindings to search for points in space that are close to a given quer

NuPIC Numenta Platform for Intelligent Computing The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implem

Home Install Documentation Download Forum Blog Funding What's new Summary psutil (process and system utilities) is a cross-platform library for retrie

Memory Profiler This is a python module for monitoring memory consumption of a process as well as line-by-line analysis of memory consumption for pyth