Search Results for "python software update" - Page 27

Showing 5236 open source projects for "python software update"

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  • 1
    Indico

    Indico

    A feature-rich event management system

    The effortless open-source tool for event organization, archival, and collaboration. Event-organization workflow that fits lectures, meetings, workshops, and conferences. A feature-rich event management system, made @ CERN, the place where the Web was born. A powerful and flexible hierarchical content management system for events, a full-blown conference organization workflow with call for Abstracts and abstract reviewing modules; flexible registration form creation and configuration;...
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  • 2
    vyper

    vyper

    Pythonic Smart Contract Language for the EVM

    See Installing Vyper to install vyper. See Tools and Resources for an additional list of framework and tools with vyper support. See Documentation for the documentation and overall design goals of the Vyper language. See Learn.Vyperlang.org for learning Vyper by building a Pokémon game. See try.vyperlang.org to use Vyper in a hosted jupyter environment! There is also an online compiler available you can use to experiment with the language and compile to bytecode and/or IR. While the vyper...
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  • 3
    SublimeLinter-eslint

    SublimeLinter-eslint

    This linter plugin for SublimeLinter provides an interface to ESLint

    This linter plugin for SublimeLinter provides an interface to ESLint. It will be used with "JavaScript" files, but since eslint is pluggable, it can actually lint a variety of other files as well. SublimeLinter will detect some installed local plugins, and thus it should work automatically for e.g. .vue or .ts files. If it works on the command line, there is a chance it works in Sublime without further ado. Make sure the plugins are installed locally colocated to eslint itself. T.i.,...
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  • 4
    django-split-settings

    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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  • 5
    Opacus

    Opacus

    Training PyTorch models with differential privacy

    Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance, and allows the client to online track the privacy budget expended at any given moment. Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source,...
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  • 6
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before...
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  • 7
    PyG

    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,...
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  • 8
    Tencent Cloud Code Analysis

    Tencent Cloud Code Analysis

    Static code analysis

    Tencent Cloud Code Analysis (TCA for short, used internally by the R&D code CodeDog ) is a cloud-native, distributed, high-performance comprehensive code analysis and tracking platform that integrates many analysis tools, including server, web and client The three components have integrated a number of self-developed tools, and also support the dynamic integration of analysis tools of various programming languages ​​in the industry. Obtain the Tencent Cloud code analysis platform by...
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  • 9
    ThetaGang

    ThetaGang

    ThetaGang is an IBKR bot for collecting money

    ThetaGang is an IBKR trading bot for collecting premiums by selling options using "The Wheel" strategy. The Wheel is a strategy that surfaced on Reddit but has been used by many in the past. This bot implements a slightly modified version of The Wheel, with my own personal tweaks. The strategy, as implemented here, does a few things differently from the one described in the post above. For one, it's intended to be used to augment a typical index-fund-based portfolio with specific asset...
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  • 10
    TensorFlow Model Garden

    TensorFlow Model Garden

    Models and examples built with TensorFlow

    The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models...
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  • 11
    AWS Serverless Application Model

    AWS Serverless Application Model

    An open-source framework for building serverless applications

    The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It provides shorthand syntax to express functions, APIs, databases, and event source mappings. With just a few lines per resource, you can define the application you want and model it using YAML. During deployment, SAM transforms and expands the SAM syntax into AWS CloudFormation syntax, enabling you to build serverless applications faster. To get started with building SAM-based...
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  • 12
    Mezzanine

    Mezzanine

    CMS framework for Django

    Mezzanine is a powerful open source content management platform built using the Django framework. In many ways it is like many other content management tools, offering an intuitive interface for managing all of your content. But Mezzanine is different in that it provides most of its functionality by default. While other platforms rely heavily on modules or reusable applications, Mezzanine comes ready with all the functionality you need, making it the more efficient choice. Mezzanine has a...
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  • 13
    Ansible for DevOps

    Ansible for DevOps

    Ansible for DevOps examples

    Ansible for DevOps is a collection of Ansible playbooks, roles, and infrastructure-as-code examples that accompany the book Ansible for DevOps by Jeff Geerling. Rather than being theoretical, the examples span real-world infrastructure setups: multi-server orchestration, LAMP stacks, Docker deployments, Kubernetes cluster spins, rolling updates, and security hardening. You can clone the repo and play with actual scenarios using Vagrant, VirtualBox, or cloud hosts, making it ideal for both...
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  • 14
    TensorRT Node for ComfyUI

    TensorRT Node for ComfyUI

    Enables the best performance on NVIDIA RTX Graphics Cards

    ComfyUI_TensorRT is an extension that lets ComfyUI run AI inference through NVIDIA’s TensorRT, aiming to get faster, more efficient execution on supported GPUs. It bridges the gap between ComfyUI’s flexible, node-based workflows and TensorRT’s highly optimized engine format. The result is that complex diffusion or image-processing graphs can be accelerated without the user having to rewrite the pipeline. The repo typically includes instructions for converting models to TensorRT engines and...
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  • 15
    Pixelization

    Pixelization

    Stable-diffusion-webui-pixelization

    This is a specialized extension for the popular Stable Diffusion Web UI (AUTOMATIC1111) that focuses on converting or “pixelizing” images into a pixel-art aesthetic. It's designed as a plugin you install into the Web UI so that in the “Extras” or “Pixelization” tab you can drag in an input image and produce a stylized, block-based version with control over cell size, color depth, and segmentation. The extension uses pre-trained models and optionally can co-operate with the Web UI’s other...
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  • 16
    EKS Best Practices

    EKS Best Practices

    A best practices guide for day 2 operations

    The Amazon EKS Best Practices Guide is a public repository containing comprehensive documentation and guidance for operating production-grade Kubernetes clusters on AWS’s managed service, Amazon EKS. Rather than a code library, it serves as a reference catalogue of patterns, anti-patterns, checklists and architectures across domains such as security, reliability, scalability, networking, cost optimization and hybrid cloud deployments. The repository is maintained by AWS but open to...
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  • 17
    Double Conversion

    Double Conversion

    Efficient binary-decimal & decimal-binary conversion routines for IEEE

    Double Conversion is a high-performance C++ library that provides precise and efficient binary-decimal and decimal-binary conversion routines for IEEE 754 double-precision floating-point numbers. Originally extracted from the V8 JavaScript engine, it was refactored into a standalone library to make its robust number conversion algorithms easily reusable in other projects. The library ensures consistent and accurate results for converting between double values and their string...
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  • 18
    Uncertainty Baselines

    Uncertainty Baselines

    High-quality implementations of standard and SOTA methods

    Uncertainty Baselines is a collection of strong, well-documented training pipelines that make it straightforward to evaluate predictive uncertainty in modern machine learning models. Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems,...
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  • 19
    Tunix

    Tunix

    A JAX-native LLM Post-Training Library

    Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation,...
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  • 20
    RLax

    RLax

    Library of JAX-based building blocks for reinforcement learning agents

    RLax (pronounced “relax”) is a JAX-based library developed by Google DeepMind that provides reusable mathematical building blocks for constructing reinforcement learning (RL) agents. Rather than implementing full algorithms, RLax focuses on the core functional operations that underpin RL methods—such as computing value functions, returns, policy gradients, and loss terms—allowing researchers to flexibly assemble their own agents. It supports both on-policy and off-policy learning, as well as...
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  • 21
    MuJoCo Playground

    MuJoCo Playground

    An open source library for GPU-accelerated robot learning

    MuJoCo Playground, developed by Google DeepMind, is a GPU-accelerated suite of simulation environments for robot learning and sim-to-real research, built on top of MuJoCo MJX. It unifies a range of control, locomotion, and manipulation tasks into a consistent and scalable framework optimized for JAX and Warp backends. The project includes classic control benchmarks from dm_control, advanced quadruped and bipedal locomotion systems, and dexterous as well as non-prehensile manipulation setups....
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  • 22
    DomainBed

    DomainBed

    DomainBed is a suite to test domain generalization algorithms

    DomainBed is a PyTorch-based research suite created by Facebook Research for benchmarking and evaluating domain generalization algorithms. It provides a unified framework for comparing methods that aim to train models capable of performing well across unseen domains, as introduced in the paper In Search of Lost Domain Generalization. The library includes a wide range of well-known domain generalization algorithms, from classical baselines such as Empirical Risk Minimization (ERM) and...
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  • 23
    Multimodal

    Multimodal

    TorchMultimodal is a PyTorch library

    This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference...
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  • 24
    Theseus

    Theseus

    A library for differentiable nonlinear optimization

    Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost...
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  • 25
    fvcore

    fvcore

    Collection of common code shared among different research projects

    fvcore is a lightweight utility library that factors out common performance-minded components used across Facebook/Meta computer-vision codebases. It provides numerics and loss layers (e.g., focal loss, smooth-L1, IoU/GIoU) implemented for speed and clarity, along with initialization helpers and normalization layers for building PyTorch models. Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. A...
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