Search Results for "state machine"
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Showing 41 open source projects for "state machine"
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XState
State machines and statecharts for the modern web
JavaScript and TypeScript finite state machines and statecharts for the modern web. Statecharts are a formalism for modeling stateful, reactive systems. This is useful for declaratively describing the behavior of your application, from the individual components to the overall application logic. XState is a library for creating, interpreting, and executing finite state machines and statecharts, as well as managing invocations of those machines as actors. The following fundamental computer... -
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zag
Finite state machines for building accessible design systems and UI
A collection of framework-agnostic UI components patterns like an accordion, menu, and dialog that can be used to build design systems for React, Vue, and Solid.js. Simple, resilient component logic. Write component logic once and use it anywhere. Built-in adapters that connect machine output to DOM semantics in a WAI-ARIA-compliant way. Component logic is largely JavaScript code and can be consumed in any JS framework. Zag machine APIs are completely headless and unstyled. Use your favorite styling solution and get it matching your design system. Finite state machines for building accessible design systems and UI components. ... -
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Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used across DeepMind. ... -
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Metaflow
A framework for real-life data science
Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. -
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FlowRedux
Kotlin Multiplatform Statemachine library with nice DSL based on Flow
Building async. running Kotlin Multiplatform state machine made easy with a DSL and coroutines. -
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Hypothesis
The property-based testing library for Python
Hypothesis is a powerful library for property-based testing in Python. Instead of writing specific test cases, users define properties and Hypothesis generates random inputs to uncover edge cases and bugs. It integrates with unittest and pytest, shrinking failing examples to minimal reproducible cases. Widely adopted in production systems, Hypothesis boosts code reliability by exploring input spaces far beyond manually crafted tests. -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major... -
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Rust-Lightning
Bitcoin Lightning library written in Rust
...It is also anticipated that as developers begin using the API, the lessons from that will result in changes to the API, so any developer using this API at this stage should be prepared to embrace that. LDK/Rust-Lightning is a generic library which allows you to build a lightning node without needing to worry about getting all of the lightning state machine, routing, and on-chain punishment code (and other chain interactions) exactly correct. Note that Rust-Lightning isn't, in itself, a node. -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
FAIRChem is a unified library for machine learning in chemistry and materials, consolidating data, pretrained models, demos, and application code into a single, versioned toolkit. Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. ... -
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CasADi
CasADi is a symbolic framework for numeric optimization
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT, etc. It can be used in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. These expression graphs, encapsulated in Function objects, can be evaluated in a virtual machine or exported to stand-alone C code. ... -
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Tree
tree is a library for working with nested data structures
...It generalizes Python’s built-in map function to operate over arbitrarily nested collections — including lists, tuples, dicts, and custom container types — while preserving their structure. This makes it particularly useful in machine learning pipelines and JAX-based workflows, where complex parameter trees or hierarchical state representations are common. The library provides efficient operations such as flatten, unflatten, and map_structure, enabling users to apply functions to all leaves of a nested structure seamlessly. Backed by a high-performance C++ core, tree is optimized for large-scale, performance-critical applications. -
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained... -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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RE/flex lexical analyzer generator
The regex-centric, fast lexical analyzer generator for C++
...Supports fast scanning of UTF-8/16/32 files, strings, and streams. The reflex scanner generator generates clean C++ lexer class code that is thread-safe. Generates Graphviz files to visualize state machine DFAs. RE/flex works seamlessly with Bison. Language: C++ License: BSD-3 Documentation: https://www.genivia.com/doc/reflex/html/index.html Repository: https://github.com/Genivia/RE-flex Changelog: see SF-README.md -
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Dragonboat
A feature complete and high performance multi-group Raft library in Go
...It is also very easy to use, our step-by-step examples can help new users to master it in half an hour. Easy to use pure-Go APIs for building Raft based applications. Feature complete and scalable multi-group Raft implementation. Disk based and memory based state machine support. Fully pipelined and TLS mutual authentication support. -
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ml-surveys
Survey papers summarizing advances in deep learning, NLP, CV, graphs
The ml-surveys repository is a broad, maintainable overview of survey papers across many subfields of machine learning — including deep learning, NLP, computer vision, graph ML, reinforcement learning, recommendation systems, embeddings, meta-learning, and more. Instead of diving into code or experiments, this repo gathers authoritative survey and review articles, summarizing the state-of-the-art, trends, challenges, and directions within each subdomain. -
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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... -
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Interpret-Text
State-of-the-art explainers for text-based machine learning models
...Users can run their experiments across multiple state-of-the-art explainers and easily perform comparative analysis on them. Using these tools, users will be able to explain their machine-learning models globally on each label or locally for each document. -
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Graph4NLP
Graph4nlp is the library for the easy use of Graph Neural Networks
Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP). It provides both full implementations of state-of-the-art models for data scientists and also flexible interfaces to build customized models for researchers and developers with whole-pipeline support. Built upon highly-optimized runtime libraries including DGL , Graph4NLP has both high running efficiency and great extensibility. The architecture of... -
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YOLO ROS
YOLO ROS: Real-Time Object Detection for ROS
This is a ROS package developed for object detection in camera images. You only look once (YOLO) is a state-of-the-art, real-time object detection system. In the following ROS package, you are able to use YOLO (V3) on GPU and CPU. The pre-trained model of the convolutional neural network is able to detect pre-trained classes including the data set from VOC and COCO, or you can also create a network with your own detection objects. The YOLO packages have been tested under ROS Noetic and... -
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NLP Architect
A model library for exploring state-of-the-art deep learning
NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. NLP Architect is a... -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and... -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments... -
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ZM
A library to handle coroutine and green thread in C
ZM is a C library to handle continuations (coroutine, exception, green thread) with finite state machines. The library is written in C99 without external dependecy or machine-specific code and can be compiled in ansi-c or ansi-c++ with the minal effort to define two unsigned int type (uint8_t and uint32_t). -
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MLBox
MLBox is a powerful Automated Machine Learning python library
MLBox is a powerful Automated Machine Learning python library. Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation.