Search Results for "parallel" - Page 2
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Showing 62 open source projects for "parallel"
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. ... -
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Blade Build System
Blade is a powerful build system from Tencent
An easy-to-use, fast and modern build system for trunk-based development in large-scale mono repo codebase. The code on the master branch is the development version and should be considered as alpha version. Please prefer using the version on the tags in your formal environment. We will release the verified version on the large-scale internal code base to the tag from time to time. -
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lzhw
LZHW Windows command line lossless compression tool for tabular files
LZHW Command Line Lossless Compression Tool is a Windows command line tool used to compress and decompress files from and to any form, csv, excel etc without any dependencies or installations. Using an optimized algorithm (LZHW) developed from Lempel-Ziv, Huffman and LZ-Welch algorithms. The tool can work in parallel and most of its code is written in Cython, so it is pretty fast. It is based on python lzhw library. Full tool documentation can be found at: https://mnoorfawi.github.io/lzhw/6%20Using%20the%20lzhw%20command%20line%20tool/ While the documentation for the python library is at: https://mnoorfawi.github.io/lzhw/ -
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Frontend Regression Validator (FRED)
Visual regression tool used to compare baseline and updated instances
...The visual analysis computes the Normalized Mean Squared error and the Structural Similarity Index on the screenshots of the baseline and updated sites, while the visual AI looks at layout and content changes independently by applying image segmentation Machine Learning techniques to recognize high-level text and image visual structures. This reduces the impact of dynamic content yielding false positives. FRED is designed to be scalable. It has an internal queue and can process websites in parallel depending on the amount of RAM and CPUs (or GPUs) available. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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DETR
End-to-end object detection with transformers
...Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. Due to this parallel nature, DETR is very fast and efficient. -
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The TRANSIMS Studio application is an integrated development environment for the TRansportation ANalysis and SIMulation System (TRANSIMS). Components include a run time environment to execute TRANSIMS in parallel, as well as a full featured GUI.
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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pipupgrade
Like yarn outdated/upgrade, but for pip
...By analyzing semantic versioning, pipupgrade categorizes updates into major, minor, and patch changes, allowing developers to make informed decisions about which packages to upgrade. Additionally, it supports updating requirements.txt and Pipfile files, ensuring that dependency specifications remain current. With features like parallel processing and dependency graph visualization, pipupgrade enhances the efficiency and clarity of Python package maintenance. -
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porttree
Show dependences of a FreeBSD port as a pseudo graphic tree
For a given FreeBSD port, determine its dependences using any combination of the FETCH_, EXTRACT_, PATCH_, BUILD_, LIB_, RUN_ and TEST_DEPENDS, and show them as a pseudo graphical tree. Use back references for cross-connections. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Pipelines
An experimental programming language for data flow
Pipelines is a language and runtime for crafting massively parallel pipelines. Unlike other languages for defining data flow, the Pipeline language requires the implementation of components to be defined separately in the Python scripting language. This allows the details of implementations to be separated from the structure of the pipeline while providing access to thousands of active libraries for machine learning, data analysis, and processing. -
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TensorFlow-ZH
Chinese version of the official document of TensorFlow
The tensorflow-zh repository is a Chinese translation of the official TensorFlow documentation, organized to make the core guides, tutorials, and reference material accessible to Chinese speakers. It was initiated shortly after TensorFlow’s open-sourcing, with translation and proofreading contributions from a community of volunteers who aimed to bridge the language barrier for learners in China and other Mandarin communities. The repo mirrors the structure of the original English docs:... -
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Intel neon
Intel® Nervana™ reference deep learning framework
...The Intel Math Kernel Library takes advantages of the parallelization and vectorization capabilities of Intel Xeon and Xeon Phi systems. When hyperthreading is enabled on the system, we recommend the following KMP_AFFINITY setting to make sure parallel threads are 1:1 mapped to the available physical cores. -
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IPS Framework
A simple Python framework for loosely-coupled multiphysics simulations
...In addition to plasma physics, it is also being used in the engineering of batteries. One of the novel features of the IPS framework is its ability to support parallelism at multiple levels: components can launch individual parallel tasks, and also launch multiple tasks concurrently. The framework can execute multiple components concurrently, and even multiple simulations, all within the same pool of compute nodes. -
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youtube-dlG
A cross platform front-end GUI of the popular youtube-dl
...You can change the naming pattern by picking a different filename format under the Options>General tab. You can also use a custom pattern by setting the option to "Custom" and editing the output template field. You can change the number of max parallel downloads by editing the "workers_number" option in your settings.json file. You can add extra youtube-dl command line options in the commands box under the Options>Extra tab. You can use your own version of youtube-dl by editing the "youtubedl_path" option in your settings.json file and make it point to your own binary (e.g. /usr/local/bin). -
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The Software Testing Automation Framework (STAF) is a framework designed to improve the level of reuse and automation in test cases and test environments. The goal of STAF is to provide a complete end-to-end automation solution for testers.
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PyCNN
Image Processing with Cellular Neural Networks in Python
Image Processing with Cellular Neural Networks in Python. Cellular Neural Networks (CNN) are a parallel computing paradigm that was first proposed in 1988. Cellular neural networks are similar to neural networks, with the difference that communication is allowed only between neighboring units. Image Processing is one of its applications. CNN processors were designed to perform image processing; specifically, the original application of CNN processors was to perform real-time ultra-high frame-rate (>10,000 frame/s) processing unachievable by digital processors. -
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Robot Framework FTP Library
FTP client for Robot Framework
SOURCE CODE MOVED TO https://github.com/kowalpy/Robot-Framework-FTP-Library . NEW RELEASES WILL APPEAR ONLY AT GITHUB AND PYPI. This Python library makes it possible to test or use FTP server using Robot Framework keywords. Together with the library, there are also available project example and keywords documentation created by libdoc. This sourceforge webpage is linked from http://robotframework.org/#test-libraries as external library so it can be considered as the official Robot... -
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Drid
Multi-Purpose Automation Grid
Console-based tool that will allow for multiple types of automation testing to run in parallel. Written in Python -
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Please participate in the SURVEY on rgedit's future: https://www.surveymonkey.com/s/VNMMJMJ your answers are much appreciated! Gedit (Gnome editor, www.gedit.org) plug-in allowing it to become an easy-to-use and yet light-weight IDE for the statistical programming environment, R (www.r-project.org).
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AWK~plus is the next generation script practice environment. The AWK Language specifications and a main extension of GNU GAWK. Combination of Dynamic and Static typing. Parallel computing that a lock is free, and is thread safe at a language level.
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python dagger
File dependency graph evaluator in pure python.
...When hashing is used, it's stored in either a text file or sqlite database (in-memory at runtime is optional). Files can be forced as stale or uptodate. Dagger can be used as a building block for a larger serial or parallel build system. -
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Cca-forum unifies the Common Component Architecture tools and tutorial. It includes the CCA specifications, the Ccaffeine framework for HPC, and related tools. These support multilanguage scientific and parallel computing.
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Distributed Parallel Programming for Python! This package builds on traditional Python by enabling users to write distributed, parallel programs based on MPI message passing primitives. General python objects can be messaged between processors. Ru
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PyMW is a Python module for parallel master-worker computing in a variety of environments. With the PyMW module, users can write a single program that scales from multicore machines to global computing platforms.
