Search Results for "python distributed list" - Page 2
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Showing 68 open source projects for "python distributed list"
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GitHub520
Community-maintained approach to improving access to GitHub services
GitHub520 is a community-maintained approach to improving access to GitHub services from regions with network friction by leveraging host mappings. The repository provides a regularly updated list of domain-to-IP entries meant to be appended to a system’s hosts file so certain GitHub endpoints resolve faster or more reliably. It includes scripts or guidance to automate updates, reducing the need for manual lookups when IPs change. The project’s goal is pragmatic: improve developer productivity... -
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Siddhi Core Libraries
Stream Processing and Complex Event Processing Engine
... to various endpoints in real time. Agile development experience with SQL-like query language and graphical drag-and-drop editor supporting event simulation. Lightweight runtime that can natively run on Kubernetes, Docker, VM, or bare metal, and embedded in any Java or Python application. Scalable, and highly available distributed event processing on Kubernetes, with NATS Streaming and Siddhi Kubernetes Operator. -
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re2
Alternative to backtracking regular expression engines
RE2 is a fast, safe, thread-friendly alternative to backtracking regular expression engines like those used in PCRE, Perl, and Python. It is a C++ library. This is the source code repository for RE2, a regular expression library. There is a fair amount of documentation (including code snippets) in the re2.h header file. Unless otherwise noted, the RE2 source files are distributed under the BSD-style license found in the LICENSE file. In POSIX mode, RE2 accepts standard POSIX (egrep) syntax... -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed... -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels... -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget... -
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UCO3D
Uncommon Objects in 3D dataset
... modeling experiments. The repository includes automated downloaders with checksum verification, fine-grained controls to fetch only selected modalities or super-categories, and a lightweight Python API for loading frames, geometry, and splats on demand. Metadata is indexed in SQLite for quick queries at scale, and helper builders handle alignment, undistortion, frame extraction from videos, and cropping around the object. -
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PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support, distributed... -
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django-split-settings
Organize Django settings into multiple files and directories
Organize Django settings into multiple files and directories. Easily override and modify settings. Use wildcards in settings file paths and mark settings files as optional. Managing Django’s settings might be tricky. There are severals issues which are encountered by any Django developer along the way. First one is caused by the default project structure. Django clearly offers us a single settings.py file. It seams reasonable at the first glance. And it is actually easy to use just after the... -
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Playground Cheatsheet for Python
Playground and cheatsheet for learning Python
..., idioms, and good style practices (including linting and PEP8). Because it is organized in bite-sized chunks, it’s ideal for beginners or people refreshing their Python skills who want to revisit syntax and common patterns before moving into larger frameworks or applications. It also supports usage as a reference: if you forgot how a list comprehension works or how decorators behave, you can quickly open the relevant script. -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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lixa
LIXA, LIbre XA, is a free and open source XA transaction manager
LIXA (LIbre XA) is an open source and free Transaction Manager implementing the distributed transaction processing "XA specification" and "TX (transaction demarcation) specification" according to the X/Open CAE Specification. LIXA implements even XTA: XA Transaction API, an innovative API that implements XA transactional context passing among different applications. LIXA is a Transaction Manager but it's not a Transaction Monitor: this is the distinguishing feature of the project. LIXA... -
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flom
Free Lock Manager
FLoM is a free open source distributed lock manager that can be used to synchronize shell commands, scripts and custom developed software. When used in a shell environment, FLoM manages process synchronization in the same way that "nice" manages process prioritization. Shell commands, scripts and custom programs can be synchronized inside a single system or in a network of IP connected systems. FLoM supports different types of abstract resources: simple, numeric, set, hierarchical... -
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Scalable-Software-Architecture
Collection of tech talks, papers and web links on Distributed Systems
Scalable-Software-Architecture gathers tech talks, academic papers, blog posts and web links related to building scalable software architecture, distributed systems, system design, and production-scale considerations. The aim is to help readers study how large systems operate: how to scale them, how to handle latency, failure, load, concurrency, and how to structure software for maintainability at scale. Because many interview and real-world engineering problems revolve around system design now... -
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
...++) and optimized for highly distributed computing environments. This makes them hardly accessible for students, researchers and hackers. Many simple Python implementations can be found on Github, but none of them is able to beat a reasonable baseline on games such as Othello or Connect Four. As an illustration, the benchmark in the README of the most popular of them only features a random baseline, along with a greedy baseline that does not appear to be significantly stronger. -
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Petastorm
Petastorm library enables single machine or distributed training
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular... -
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FairScale
PyTorch extensions for high performance and large scale training
... boilerplate in complex distributed setups. Its components are modular, so teams can adopt just the sharding optimizer or the pipeline engine without rewriting their training loop. FairScale puts emphasis on correctness and debuggability, offering hook points, logging, and reference examples for common trainer patterns. Although many ideas have since landed in core PyTorch, FairScale remains a valuable reference and a practical toolbox for squeezing more performance out of multi-GPU and multi-node jobs. -
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Jraph
A Graph Neural Network Library in Jax
... compilation. The library includes a comprehensive set of utilities for batching, padding, masking, and partitioning graph data, making it ideal for distributed and large-scale GNN experiments. Jraph also comes with a model zoo—a collection of forkable reference implementations of common message-passing GNN architectures, such as Graph Networks, Graph Convolutional Networks, and Graph Attention Networks. -
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Awesome Conformal Prediction
A professionally curated list of awesome Conformal Prediction videos
awesome-conformal-prediction is a curated “awesome list” repository on GitHub collecting high-quality resources related to conformal prediction: tutorials, books, papers, theses, open-source libraries, videos, and other educational material. It is not a software library itself but a directory of resources for those wanting to learn or work with conformal prediction and uncertainty quantification. This exceptional resource is the culmination of my PhD journey in Machine Learning, specializing... -
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Spyne
A transport agnostic sync/async RPC library
Spyne is a Python RPC toolkit that makes it easy to expose online services that have a well-defined API using multiple protocols and transports. It integrates with popular Python web frameworks as well as libraries like SQLAlchemy to keep your code as DRY as possible. Spyne aims to save the protocol implementers the hassle of implementing their own remote procedure call api and the application programmers the hassle of jumping through hoops just to expose their services using multiple protocols... -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
... computational steps, while maintaining speaker consistency across output channels. Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. The repository includes all necessary scripts for training, dataset preparation, distributed training, evaluation, and audio separation. -
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Awesome Fraud Detection Research Papers
A curated list of data mining papers about fraud detection
A curated list of data mining papers about fraud detection from several conferences. -
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PyTorchVideo
A deep learning library for video understanding research
... prototyping and production inference. It supports video I/O pipelines, data augmentation, distributed training, and mixed precision computation for large-scale experiments. PyTorchVideo also connects seamlessly with other Meta AI tools such as Detectron2 and PyTorch3D for multimodal video analysis. Designed to accelerate research and deployment, it serves as a unified framework for reproducible, high-performance video AI development. -
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Big List of Naughty Strings
List of strings which have a high probability of causing issues
The Big List of Naughty Strings is a community-maintained catalog of “gotcha” inputs that commonly break software, from unusual Unicode to SQL and script injection payloads. It exists so developers and QA engineers can easily test edge cases that normal test data would miss, such as zero-width characters, right-to-left marks, emojis, foreign alphabets, and long or malformed strings. By throwing these strings at forms, APIs, databases, and UIs, teams can discover encoding bugs, sanitizer gaps... -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network...
