Search Results for "python distributed list" - Page 5
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Showing 260 open source projects for "python distributed list"
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Gerapy
Distributed Crawler Management Framework Based on Scrapy
Distributed Crawler Management Framework Based on Scrapy, Scrapyd, Scrapyd-Client, Scrapyd-API, Django and Vue.js. Someone who has worked as a crawler with Python may use Scrapy. Scrapy is indeed a very powerful crawler framework. It has high crawling efficiency and good scalability. It is basically a necessary tool for developing crawlers using Python. If you use Scrapy as a crawler, then of course we can use our own host to crawl when crawling, but when the crawl is very large, we can’t run... -
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Horovod
Distributed training framework for TensorFlow, Keras, PyTorch, etc.
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data... -
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Grassroots DICOM
Cross-platform DICOM implementation
Grassroots DiCoM is a C++ library for DICOM medical files. It is accessible from Python, C#, Java and PHP. It supports RAW, JPEG, JPEG 2000, JPEG-LS, RLE and deflated transfer syntax. It comes with a super fast scanner implementation to quickly scan hundreds of DICOM files. It supports SCU network operations (C-ECHO, C-FIND, C-STORE, C-MOVE). PS 3.3 & 3.6 are distributed as XML files. It also provides PS 3.15 certificates and password based mecanism to anonymize and de-identify DICOM... -
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Roundup Issue Tracker
Simple-to-use/-install issue-tracking system: web, REST, email, CLI
Roundup is a simple-to-use and -install issue-tracking system with command-line, web, REST, XML-RPC, and e-mail interfaces. It runs on python 2.7 or 3.6 or newer. Roundup has been deployed for: * bug tracking and TODO list management (the classic installation) * customer help desk support (with a wizard for the phone answerers, linking to networking, system and development issue trackers) * issue management for IETF working groups * sales lead tracking ...and so on. It's been... -
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DAE Tools Project
Object-oriented equation-based modelling and optimisation software
..., such as plotting and exporting to various file formats - Report generation - Code generation, co-simulation and model exchange The following class of problems can be solved by DAE Tools: - Initial value problems of implicit form - Index-1 DAE systems - With lumped or distributed parameters - Steady-state or dynamic - Continuous with some elements of event-driven systems -
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Portainer Templates
500+ 1-click Portainer app templates
A compiled list of 500+ ready-to-go Portainer App templates. In Portainer, App Templates enable you to easily deploy services with a predetermined configuration, while allowing you to customize options through the web UI. While Portainer ships with some default templates, it's often helpful to have 1-click access to many more apps + stacks, without having to constantly switch template sources. This repo combines app templates from several sources, to create a ready-to-go template file... -
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Ring
Simple and flexible programming language for applications development
... is distributed as a Free-Open Source project under the MIT License. -
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FRODO 2
Open-Source Framework for Distributed Constraint Optimization (DCOP)
FRODO is a Java platform to solve Distributed Constraint Satisfaction Problems (DisCSPs) and Optimization Problems (DCOPs). It provides implementations for a variety of algorithms, including DPOP (and its variants), ADOPT, SynchBB, DSA... -
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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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Taylorplot_Neptune
Creation of a Taylorplot for several machine learning models
Here we present the lines of code for creating a taylor plot with python to display several machine learning models. We show the solution for displaying 10 models, but the list and number can be changed simply by modifying the sample list. -
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TANGO is an object oriented control system for Linux and Windows. It provides a framework in C++, Java and Python for implementing distributed control objects an accessing them via a well-defined API. This sourceforge project a
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Apache Allura
Forge software for hosting software projects
Apache Allura's website and resources are all at https://allura.apache.org/ Allura was originally developed here, which is why this project exists. -
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ClassyVision
An end-to-end PyTorch framework for image and video classification
... distributed training, reproducible experiments, and flexible configuration tools. It offers high performance and scalability—capable of training models like ResNet-50 on ImageNet in just minutes—while remaining accessible to both researchers and production engineers. The library integrates seamlessly with PyTorch Hub for easy access to pretrained models and supports elastic training using PyTorch Elastic, making distributed training robust to changes in cluster resources or hardware failures. -
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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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LBRY SDK
The LBRY SDK for building decentralized content apps
..., possibly in exchange for payments, as well as a distributed hash table used by peers to discover other peers. LBRY SDK for Python is currently the most fully featured implementation of the LBRY Network protocols and includes many useful components and tools for building decentralized applications. -
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Workalendar
Worldwide holidays and workdays computational toolkit
Worldwide holidays and workdays computational toolkit. Workalendar is a Python module that offers classes able to handle calendars, list legal/religious holidays and give working-day-related computation functions. This library is ready for production, although we may warn eventual users: some calendars may not be up-to-date, and this library doesn’t cover all the existing countries on earth (yet). -
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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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DeepCTR
Package of deep-learning based CTR models
DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based... -
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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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CAT
CAT is the basic component of the server project
CAT is a distributed application performance monitoring and alerting system that specializes in tracking request flows, exceptions, and metrics across microservice ecosystems. It offers real-time dashboards showing throughput, response times, error rates, and service dependency graphs to help operations and development collaborate on reliability issues. In addition to metrics, it enables tracing—propagating context across RPC boundaries so problems like latency spikes or failed calls can... -
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CoffeeScript
Unfancy JavaScript
CoffeeScript is a lightweight programming language that compiles into JavaScript. It adds syntactic sugar inspired by Ruby, Python, and Haskell to improve brevity and readability, while producing predictable and efficient JavaScript output. Its design emphasizes that “It’s just JavaScript,” meaning any JS library works seamlessly, and compiled output is clean and performant. Adds syntactic sugar like list comprehensions and destructuring assignment. Supports literate programming via .litcoffee... -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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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...
