Showing 4 open source projects for "block"

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  • 1
    nvim-ufo

    nvim-ufo

    Not UFO in the sky, but an ultra fold in Neovim

    The goal of nvim-ufo is to make Neovim's fold look modern and keep high performance. Not UFO in the sky, but an ultra fold in Neovim. Using a provider of ufo, must set a large value for foldlevel, this is the limitation of foldmethod=manual. A small value may close fold automatically if the fold ranges updated.
    Downloads: 0 This Week
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  • 2
    Sysdig

    Sysdig

    Linux system exploration and troubleshooting tool

    Continuously assess cloud security posture by flagging misconfigurations and suspicious activity. Consolidate container and host scanning in a single workflow. Automate scanning locally in your CI/CD tools without images leaving your environment and block vulnerabilities pre-deployment. Visualize all network communication across apps and services. Apply microsegmentation by automating Kubernetes-native network policies. Unify threat detection and incident response across containers, Kubernetes, and cloud with out-of-the-box Falco rules leveraging syscalls, Kubernetes audit logs and cloud logs. ...
    Downloads: 1 This Week
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  • 3
    Aniseed

    Aniseed

    Neovim configuration and plugins in Fennel (Lisp compiled to Lua)

    ...Aniseed ships with a set of module macros that make interactive evaluation not only possible but rich and intuitive. You should read:h aniseed to learn the details but it’s worth mentioning that you opt-in by starting your file with a (module …​) block, you then export values from your module with the (def…​) macros.
    Downloads: 0 This Week
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  • 4
    ResNeXt

    ResNeXt

    Implementation of a classification framework

    ...Instead of simply increasing depth or width, ResNeXt introduces a new dimension called cardinality, which refers to the number of parallel transformation paths (i.e. the number of “branches”) that are aggregated together. Each branch is a small transformation (e.g. bottleneck block) and their outputs are summed—this enables richer representation without excessive parameter blowup. The design is modular and homogeneous, making it relatively easy to scale (by tuning cardinality, width, depth) and adopt in existing residual frameworks. The official repository offers a Torch (Lua) implementation with code for training, evaluation, and pretrained models on ImageNet. ...
    Downloads: 0 This Week
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