Search Results for "machine learning python"

.... When you need to scale up things like BERT and self-supervised learning, Lightning responds accordingly by automatically exporting to ONNX or TorchScript. PyTorch Lightning can easily be applied for any use case. With just a quick refactor you can run your code on any hardware, run distributed training, perform logging, metrics, visualization and so much more!

SMC takes a state machine stored in a .sm file and generates a State pattern in 14 programming languages. Includes: default transitions, transition args, transition guards, push/pop transitions and Entry/Exit actions. See User Manual for more info.

... 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

... assist, you probably already know that it can save you tons of time, easily cutting your keystrokes in half. Powered by sophisticated machine learning models trained on billions of lines of trusted open source code from GitHub, Tabnine is the most advanced AI-powered code completion copilot available today. And like GitHub, it is an essential tool for professional developers.

itemis CREATE - formerly known as Yakindu Statechart Tools (SCT) - is a tool for the specification and development of reactive, event-driven systems with the help of state machines. It consists of an easy-to-use tool for graphical editing and provides validation, simulation and code generators for different target platforms. Visit http://www.statecharts.org for more information! !! YAKINDU SCT HAS MOVED !! DOWNLOAD FROM https://info.itemis.com/download-yakindu-statechart-tools

ECharts is a state machine-based programming language for event-driven systems derived from the standardized UML Statecharts language. ECharts has a proven track-record in a large-scale commercial deployment. Take a look at what ECharts has to offer!

pyIRDG is a program written in Python to generate relational datasets in Prolog format. It uses data from the Internet Movie Database in combination with IMDbPY as backend. A graphical user interface written in pyQt allows the user to link multiple entities together as model for the generation process. The big four entities are Title, Person, Company and Character. Many attributes can be chosen for adding to the output .pl file. Three types of constraints on attributes are available to limit...

Tool used to generate state machine framework code from a terse set of directives embedded directly in the input source code file. This tool will also generate GraphViz graphical description and Spin/Promela modelling output.

News: since 2015 we continue all related developments within Collective Knowledge Framework: http://github.com/ctuning/ck/wiki Alchemist plugin is a collection of plugins for GCC/LLVM for external and fine-grain code analysis and tuning. It is intended to to extract program properties for machine learning based optimization (see MILEPOST GCC); optimize programs at fine-grain level (such as unrolling, tiling, prefetching, etc); tune default optimization heuristic; gradually decompose program...