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  • GitHub - lucidrains/vit-pytorch: Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

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      GitHub - lucidrains/vit-pytorch: Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
    • GitHub - Blealtan/efficient-kan: An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).

      This repository contains an efficient implementation of Kolmogorov-Arnold Network (KAN). The original implementation of KAN is available here. The performance issue of the original implementation is mostly because it needs to expand all intermediate variables to perform the different activation functions. For a layer with in_features input and out_features output, the original implementation needs

        GitHub - Blealtan/efficient-kan: An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).
      • GitHub - engine262/engine262: An implementation of ECMA-262 in JavaScript

        While helping develop new features for JavaScript, I've found that one of the most useful methods of finding what works and what doesn't is being able to actually run code using the new feature. Babel is fantastic for this, but sometimes features just can't be nicely represented with it. Similarly, implementing a feature in one of the engines is a large undertaking, involving long compile times an

          GitHub - engine262/engine262: An implementation of ECMA-262 in JavaScript
        • FastSpark: A New Fast Native Implementation of Spark from Scratch

          TLDR: Here is the code to explore. It all started during my hobby research on various distributed schedulers and distributed computing frameworks. Naturally, Spark came under the bracket. I was already somewhat familiar with Spark internals since I have been using it for over 3 years. It struck me then that one of the primary reasons why it became hugely successful is not just because of its speed

            FastSpark: A New Fast Native Implementation of Spark from Scratch
          • proposal/design/generics-implementation-dictionaries-go1.18.md at master · golang/proposal

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              proposal/design/generics-implementation-dictionaries-go1.18.md at master · golang/proposal
            • GitHub - qhgz2013/anime-face-detector: A Faster-RCNN based anime face detector implementation using tensorflow.

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                GitHub - qhgz2013/anime-face-detector: A Faster-RCNN based anime face detector implementation using tensorflow.
              • Virtual scrolling: Core principles and basic implementation in React - LogRocket Blog

                What is virtual scrolling and why do we need it? Imagine you have a dataset of 100,000 or more items you want to display as a scrollable list without pagination. Rendering that many rows would pollute the DOM, consume too much memory, and degrade the app’s performance. Instead, you want to show the user only a small portion of data at a given time. Other items should be emulated (virtualized) via

                  Virtual scrolling: Core principles and basic implementation in React - LogRocket Blog
                • GitHub - lucidrains/imagen-pytorch: Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch

                  Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pretrained T5 model (attention network). It also contains dynamic clipping for improved classifier free guidance, noise l

                    GitHub - lucidrains/imagen-pytorch: Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch
                  • GitHub - Hzzone/pytorch-openpose: pytorch implementation of openpose including Hand and Body Pose Estimation.

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                      GitHub - Hzzone/pytorch-openpose: pytorch implementation of openpose including Hand and Body Pose Estimation.
                    • SP 800-204C, Implementation of DevSecOps for a Microservices-based Application with Service Mesh | CSRC

                      Cloud-native applications have evolved into a standardized architecture consisting of multiple loosely coupled components called microservices (often typically implemented as containers) that are supported by an infrastructure for providing application services, such as service mesh. Both of these components are usually hosted on a container orchestration and resource management platform. In this

                      • GitHub - zmartzone/lua-resty-openidc: OpenID Connect Relying Party and OAuth 2.0 Resource Server implementation in Lua for NGINX / OpenResty

                        events { worker_connections 128; } http { lua_package_path '~/lua/?.lua;;'; resolver 8.8.8.8; lua_ssl_trusted_certificate /etc/ssl/certs/ca-certificates.crt; lua_ssl_verify_depth 5; # cache for discovery metadata documents lua_shared_dict discovery 1m; # cache for JWKs lua_shared_dict jwks 1m; # NB: if you have "lua_code_cache off;", use: # set $session_secret xxxxxxxxxxxxxxxxxxx; # see: https://g

                          GitHub - zmartzone/lua-resty-openidc: OpenID Connect Relying Party and OAuth 2.0 Resource Server implementation in Lua for NGINX / OpenResty
                        • GitHub - microsoft/DTrace-on-Windows: Code for the cross platform, single source, OpenDTrace implementation

                          Here at Microsoft, we are always looking to engage with open source communities to produce better solutions for the community and our customers. One of the more useful debugging advances that have arrived in the last decade is DTrace. DTrace of course needs no introduction: it's a dynamic tracing framework that allows an admin or developer to get a real-time look into a system either in user or ke

                            GitHub - microsoft/DTrace-on-Windows: Code for the cross platform, single source, OpenDTrace implementation
                          • GitHub - mmalek06/JsonSql: SQL micro-dialect implementation for querying JSON objects. Written purely in Scala.

                            In order to be able to parse text documents correctly, some baseline syntax had to be established. When it comes to Json itself, it may look as you like, no restrictions here. Though, when it comes to SQL, it needs to abide to certain rules: Fields should always be surrounded by double quotes: "example.field". String constants should always be surrounded by single quotes: 'I\'m a string constant!'

                              GitHub - mmalek06/JsonSql: SQL micro-dialect implementation for querying JSON objects. Written purely in Scala.
                            • GitHub - ra1028/swiftui-hooks: 🪝 A SwiftUI implementation of React Hooks. Enhances reusability of stateful logic and gives state and lifecycle to function view.

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                                GitHub - ra1028/swiftui-hooks: 🪝 A SwiftUI implementation of React Hooks. Enhances reusability of stateful logic and gives state and lifecycle to function view.
                              • GitHub - Ethan-Arrowood/undici-fetch: A WHATWG Fetch implementation based on @nodejs/undici

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                                  GitHub - Ethan-Arrowood/undici-fetch: A WHATWG Fetch implementation based on @nodejs/undici
                                • New Filesharing Implementation in Docker Desktop Windows Improves Developer Inner Loop UX | Docker

                                  New Filesharing Implementation in Docker Desktop Windows Improves Developer Inner Loop UX A common developer workflow when using frameworks like Symfony or React is to edit the source code using a Windows IDE while running the app itself in a Docker container. The source is shared between the host and the container with a command like the following: $ docker run -v C:\Users\me:/code -p 8080:8080 m

                                    New Filesharing Implementation in Docker Desktop Windows Improves Developer Inner Loop UX | Docker
                                  • GitHub - pubkey/client-side-databases: An implementation of the exact same app in Firestore, AWS Datastore, PouchDB, RxDB and WatermelonDB

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                                      GitHub - pubkey/client-side-databases: An implementation of the exact same app in Firestore, AWS Datastore, PouchDB, RxDB and WatermelonDB
                                    • GitHub - daac-tools/daachorse: 🐎 A fast implementation of the Aho-Corasick algorithm using the compact double-array data structure in Rust.

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                                        GitHub - daac-tools/daachorse: 🐎 A fast implementation of the Aho-Corasick algorithm using the compact double-array data structure in Rust.
                                      • Python/STAN Implementation of Multiplicative Marketing Mix Model, with Deep Dive into Adstock…

                                        Full code and simulated dataset are posted on my Github repo: https://github.com/sibylhe/mmm_stan The methodology of this project is based on this paper by Google, but is applied to a more complicated, real-world setting, where 1) there are 13 media channels and 46 control variables; 2) models are built in a stacked way. 1. IntroductionMarketing Mix Model, or Media Mix Model (MMM) is used by adver

                                          Python/STAN Implementation of Multiplicative Marketing Mix Model, with Deep Dive into Adstock…
                                        • GitHub - ad-sho-loko/bogoDB: A toy dbms implementation written in Golang

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                                            GitHub - ad-sho-loko/bogoDB: A toy dbms implementation written in Golang
                                          • GitHub - google/gemma_pytorch: The official PyTorch implementation of Google's Gemma models

                                            Gemma is a family of lightweight, state-of-the art open models built from research and technology used to create Google Gemini models. They are text-to-text, decoder-only large language models, available in English, with open weights, pre-trained variants, and instruction-tuned variants. For more details, please check out the following links: Gemma on Google AI Gemma on Kaggle Gemma on Vertex AI M

                                              GitHub - google/gemma_pytorch: The official PyTorch implementation of Google's Gemma models
                                            • GitHub - microsoft/debugpy: An implementation of the Debug Adapter Protocol for Python

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                                                GitHub - microsoft/debugpy: An implementation of the Debug Adapter Protocol for Python
                                              • Add Data class implementation: Simple immutable value object by zverok · Pull Request #6353 · ruby/ruby

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                                                  Add Data class implementation: Simple immutable value object by zverok · Pull Request #6353 · ruby/ruby
                                                • GitHub - public/sonora: A gRPC-Web implementation for Python

                                                  Regular gRPC has a lot going for it but is awkward to use in some environments. gRPC-Web makes it easy to get gRPC working in environments that need HTTP/1.1 but the Google gRPC and gRPC-Web implementations don't like to coexist with your normal Python frameworks like Django or Flask. Sonora doesn't care what ioloop you use, this means you can run it along side any other Python web framework in th

                                                    GitHub - public/sonora: A gRPC-Web implementation for Python
                                                  • GitHub - ipazc/mtcnn: MTCNN face detection implementation for TensorFlow, as a PIP package.

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                                                      GitHub - ipazc/mtcnn: MTCNN face detection implementation for TensorFlow, as a PIP package.
                                                    • 読書メモ: Database Design and Implementation

                                                      書籍 配布ソース 取り組み方 章ごとの要点をまとめる インターフェースとテストコードから実装をイメージする 実装を読み解いてコメントを書きながら写経する Suggested Reading は気になる資料のリストアップまで Exercises はどこまでやるか悩ましい。 割とボリューミーなので、1周目は読むだけに留めて、2周目で取り組むくらいの気持ちで。 全体に対するメモ 実装パートは事前に解説した内容まで踏み込まない Exerciseパートで、追加で取り組む課題として設定されてたりする 扱える値 string, integer buffer replacement clock まで解説 & 実装はナイーブなもの recovery 記録する log の種類は、ファイル末尾への block の追加まで解説 & 実装するのは以下 CHECKPOINT (transactionの) START,

                                                        読書メモ: Database Design and Implementation
                                                      • GitHub - NVlabs/stylegan3: Official PyTorch implementation of StyleGAN3

                                                        Alias-Free Generative Adversarial Networks Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, Timo Aila https://nvlabs.github.io/stylegan3 Abstract: We observe that despite their hierarchical convolutional nature, the synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unhealthy manner. This manifests itsel

                                                          GitHub - NVlabs/stylegan3: Official PyTorch implementation of StyleGAN3
                                                        • Managing a Secure JSON Web Token Implementation

                                                          This article assumes that you have a working knowledge of how JSON Web Tokens are both used and represented. If you would like to learn more about JSON Web Tokens, you can check out this article by Auth0: An Introduction to JSON Web Tokens. IntroductionJSON Web Tokens (JWTs) are great for representing a user's authentication / authorization state without needing to maintain a server-side session s

                                                            Managing a Secure JSON Web Token Implementation
                                                          • GitHub - tom-p-reichel/svg-is-turing-complete: An implementation of rule 110 in Scalable Vector Graphics

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                                                              GitHub - tom-p-reichel/svg-is-turing-complete: An implementation of rule 110 in Scalable Vector Graphics
                                                            • GitHub - NVlabs/stylegan2-ada-pytorch: StyleGAN2-ADA - Official PyTorch implementation

                                                              Training Generative Adversarial Networks with Limited Data Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila https://arxiv.org/abs/2006.06676 Abstract: Training generative adversarial networks (GAN) using too little data typically leads to discriminator overfitting, causing training to diverge. We propose an adaptive discriminator augmentation mechanism that sign

                                                                GitHub - NVlabs/stylegan2-ada-pytorch: StyleGAN2-ADA - Official PyTorch implementation
                                                              • Constant time implementation of the LFU cache eviction algorithm

                                                                Constant time implementation of the LFU cache eviction algorithm A common strategy to make any system super-performant is Caching. Almost all software products, operating at scale, have multiple layers of caches in their architectures. Caching, when done right, does wonder to the response time and is one of the main reasons why products work so well at a massive scale. Cache engines are limited by

                                                                  Constant time implementation of the LFU cache eviction algorithm
                                                                • GitHub - mkocabas/VIBE: Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"

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                                                                    GitHub - mkocabas/VIBE: Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"
                                                                  • GitHub - mlfoundations/open_clip: An open source implementation of CLIP.

                                                                    [Paper] [Citations] [Clip Colab] [Coca Colab] Welcome to an open source implementation of OpenAI's CLIP (Contrastive Language-Image Pre-training). Using this codebase, we have trained several models on a variety of data sources and compute budgets, ranging from small-scale experiments to larger runs including models trained on datasets such as LAION-400M, LAION-2B and DataComp-1B. Many of our mode

                                                                      GitHub - mlfoundations/open_clip: An open source implementation of CLIP.
                                                                    • AMD Quietly Funded A Drop-In CUDA Implementation Built On ROCm: It's Now Open-Source - Phoronix

                                                                      AMD Quietly Funded A Drop-In CUDA Implementation Built On ROCm: It's Now Open-Source Written by Michael Larabel in Display Drivers on 12 February 2024 at 09:00 AM EST. Page 1 of 4. 153 Comments. While there have been efforts by AMD over the years to make it easier to port codebases targeting NVIDIA's CUDA API to run atop HIP/ROCm, it still requires work on the part of developers. The tooling has i

                                                                        AMD Quietly Funded A Drop-In CUDA Implementation Built On ROCm: It's Now Open-Source - Phoronix
                                                                      • GitHub - lucidrains/DALLE-pytorch: Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

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                                                                          GitHub - lucidrains/DALLE-pytorch: Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
                                                                        • GitHub - module-federation/module-federation-examples: Implementation examples of module federation , by the creators of module federation

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                                                                            GitHub - module-federation/module-federation-examples: Implementation examples of module federation , by the creators of module federation
                                                                          • GitHub - open-draft/event-contract: Type-safe, implementation-agnostic event contract framework.

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                                                                              GitHub - open-draft/event-contract: Type-safe, implementation-agnostic event contract framework.
                                                                            • GitHub - GoogleCloudPlatform/bigquery-data-lineage: Reference implementation for real-time Data Lineage tracking for BigQuery using Audit Logs, ZetaSQL and Dataflow.

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                                                                                GitHub - GoogleCloudPlatform/bigquery-data-lineage: Reference implementation for real-time Data Lineage tracking for BigQuery using Audit Logs, ZetaSQL and Dataflow.
                                                                              • GitHub - swapneel/hnsw-rust: HNSW implementation in Rust. Reference: https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf

                                                                                hnsw-rust is a Rust implementation of The Hierarchical Navigable Small World (HNSW) algorithm. HNSW is a notable advancement in Approximate Nearest Neighbor (ANN) search in high-dimensional spaces, fundamentally altering our approach to these problems. The algorithm constructs a layered graph structure, where higher layers (less dense) are used for rapid global navigation, while lower layers (more

                                                                                  GitHub - swapneel/hnsw-rust: HNSW implementation in Rust. Reference: https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf
                                                                                • GitHub - WongKinYiu/yolov7: Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

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                                                                                    GitHub - WongKinYiu/yolov7: Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors