Search Results for "edge" - Page 2

...Graph Nets supports both TensorFlow 1 and TensorFlow 2, working with CPU and GPU environments, and includes educational Jupyter demos for shortest path finding, sorting, and physical prediction tasks. The codebase emphasizes modularity, allowing users to easily define their own edge, node, and global update functions.

Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are appliances\virtual appliances located at clients data centers, edge computing, and POS systems. Ever wandered how your going to push an update to that smart fridge your company is working on as it's thousands of devices around the globe? wish you could have the assurance that your service will always use the latest code\envvars\etc in all of it's edge locations? want the ability to stop\start a globally distributed service with a single command? ...

...Ever wandered how your going to push an update to that smart fridge your company is working on as it's thousands of devices around the globe? wish you could have the assurance that your service will always use the latest code\envvars\etc in all of its edge locations? want the ability to stop\start a globally distributed service with a single command? Nebula was designed from the ground up to answer all of these needs and much more, refer to the documentation if your interested in seeing how to use it.

Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are IoT devices, appliances\virtual appliances located at clients data centers, and edge computing. Nebula imposes no limits on the scale of the cluster, each component in it is designed to scale out to allow millions of workers to be managed by it. Designed to connect to devices that are spread around the globe Nebula is tolerant of network connection issues and will resync the device when it reconnects. With a single API call you can deploy a new container version to managed devices around the globe in minutes.

...The transformation is idempotent: running it multiple times won’t keep adding spaces, which makes it safe in automated workflows. It’s designed to be pragmatic and lightweight, with sensible defaults that handle common edge cases found in websites, blogs, and multilingual technical docs. Because it targets clarity over heavy linguistic analysis, it’s easy to adopt and delivers immediate, visible improvements to mixed CJK/Latin text.

...The catalog format lets you scan for an example, copy it, and adapt it to your use case without wading through a large framework. It favors clarity over micro-optimizations so learners can grasp the idea before worrying about edge performance. Over time it becomes a personal cookbook of solutions you can remix across projects. This approach is especially helpful when you need a quick refresher on a technique you haven’t used in a while.

...Always current dependencies and security updates enforced by pyup.io. A slim but robust foundation – just enough to maximize your productivity, nothing more. A factory for building bleeding edge, best practiced, scalable, rest APIs.

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...

gEcrit is a Python orientated source code editor. It tries to keep the interface as clean as possible and keep the menus simple. It features all the common features a Python programmer might need, including an interactive Python shell.

Mantikhor is an *information representation* language. Like RDF, it models information as directed-edge arc-node graphs, although Mantikhor's use of such constructs is more structured and constrained.

GNU/Linux Desktop Testing Project (GNU/LDTP) is created with the goal of producing high quality test automation frameworks and cutting-edge tools that can be used to test the Linux Desktop and improve it.

Spineless is a generic cross-platform 3D game engine implemented in Python. Focus is on flexibility, clean design and ease of use, not pure speed or bleeding edge graphics.