softgym | benchmark environments for deformable object manipulation | Reinforcement Learning library

 by   Xingyu-Lin C++ Version: Current License: BSD-3-Clause

kandi X-RAY | softgym Summary

kandi X-RAY | softgym Summary

softgym is a C++ library typically used in Artificial Intelligence, Reinforcement Learning applications. softgym has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

SoftGym is a set of benchmark environments for deformable object manipulation including tasks involving fluid, cloth and rope. It is built on top of the Nvidia FleX simulator and has standard Gym API for interaction with RL agents. A number of RL algorithms benchmarked on SoftGym can be found in SoftAgent.
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              softgym has a low active ecosystem.
              It has 142 star(s) with 26 fork(s). There are 10 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 11 open issues and 18 have been closed. On average issues are closed in 29 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of softgym is current.

            kandi-Quality Quality

              softgym has no bugs reported.

            kandi-Security Security

              softgym has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              softgym is licensed under the BSD-3-Clause License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

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              softgym releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.

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            softgym Key Features

            No Key Features are available at this moment for softgym.

            softgym Examples and Code Snippets

            No Code Snippets are available at this moment for softgym.

            Community Discussions

            QUESTION

            Can't connect to websocket using ssl and apache
            Asked 2019-Mar-31 at 04:09

            I am tying to connect my client to the server socket using socket.io. When I am using http all works fine but when I try to use https the client can't connect.

            I try to create the server using http require('https') and using certificates but didn't work.

            For now after a few code changes and tests this is how my code is:

            Server, index.js

            ...

            ANSWER

            Answered 2019-Mar-31 at 04:09

            Seems like your proxy server does not supports WebScokets upgrade. If you are using apache the configuration is not simple. You will have to install mod_proxy_ws_tunnel module to do this.

            Follow this link

            Web sockets upgrade is a process that user upgrade from HTTP protocol to WebSckets protocol by sending a upgrade header followed by a three way hand shake. You may find some resources about configuring apache with websocket here

            Also if apache server is not required, and you can use another proxy serve. Install nginx and your life will get easier. Then simply add this configuration to your nginx configuration.

            Source https://stackoverflow.com/questions/55317965

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install softgym

            The following command will install some necessary dependencies.
            This codebase is tested with Ubuntu 16.04 LTS, CUDA 9.2 and Nvidia driver version 440.64. Other versions might work but are not guaranteed, especially with a different driver version. Please use our docker for other versions.
            Create conda environment Create a conda environment and activate it: conda env create -f environment.yml
            Compile PyFleX: Go to the root folder of softgym and run . ./prepare_1.0.sh. After that, compile PyFleX with CMake & Pybind11 by running . ./compile_1.0.sh Please see the example test scripts and the bottom of bindings/pyflex.cpp for available APIs.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            CLONE
          • HTTPS

            https://github.com/Xingyu-Lin/softgym.git

          • CLI

            gh repo clone Xingyu-Lin/softgym

          • sshUrl

            git@github.com:Xingyu-Lin/softgym.git

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