genrl | PyTorch reinforcement | Reinforcement Learning library

 by   SforAiDl Python Version: 0.0.2 License: MIT

kandi X-RAY | genrl Summary

kandi X-RAY | genrl Summary

genrl is a Python library typically used in Artificial Intelligence, Reinforcement Learning, Deep Learning, Pytorch applications. genrl has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install genrl' or download it from GitHub, PyPI.

Reinforcement learning research is moving faster than ever before. In order to keep up with the growing trend and ensure that RL research remains reproducible, GenRL aims to aid faster paper reproduction and benchmarking by providing the following main features:. By integrating these features into GenRL, we aim to eventually support any new algorithm implementation in less than 100 lines.
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            kandi-support Support

              genrl has a low active ecosystem.
              It has 376 star(s) with 57 fork(s). There are 13 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 35 open issues and 154 have been closed. On average issues are closed in 74 days. There are 17 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of genrl is 0.0.2

            kandi-Quality Quality

              genrl has 0 bugs and 0 code smells.

            kandi-Security Security

              genrl has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              genrl code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              genrl is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              genrl releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              genrl saves you 3293 person hours of effort in developing the same functionality from scratch.
              It has 7070 lines of code, 615 functions and 146 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed genrl and discovered the below as its top functions. This is intended to give you an instant insight into genrl implemented functionality, and help decide if they suit your requirements.
            • Run the experiment
            • Train the agent
            • Swap two arrays
            • Returns a random rollout buffer
            • Train the A2C model
            • Collect rollout rewards
            • Save the model to disk
            • Loads pretrained model hyperparameters from file
            • Create the model
            • Get the dimensions of the environment
            • Return a VectorEnv instance
            • Compute action probability distribution
            • Update the parameters for a given action
            • Calculate the action distribution
            • Download data from url
            • Get the value for a given state
            • Reset the model
            • Compute the reward for the given action
            • Compute the loss
            • Update model parameters
            • Compute loss
            • Calculate parameters
            • Optimized objective function
            • Calculate model parameters
            • Evaluate the population
            • Get the size of the environment
            • Evaluate the policy
            Get all kandi verified functions for this library.

            genrl Key Features

            No Key Features are available at this moment for genrl.

            genrl Examples and Code Snippets

            No Code Snippets are available at this moment for genrl.

            Community Discussions

            QUESTION

            Retrieve an inner array value relative to a specified inner array property value paired with a specified outer array property value
            Asked 2018-Nov-08 at 05:20

            Based on the validated JSON below:

            ...

            ANSWER

            Answered 2018-Nov-08 at 05:20

            How about something like this?

            Source https://stackoverflow.com/questions/53200135

            QUESTION

            How to parse JSON response to a single JAVA Object
            Asked 2018-Oct-18 at 09:00

            I tried to parse a JSON response to a single JAVA Object.This JSON response included with another JSON arrays and simple fields.

            However I could get following result in my attempts.

            ...

            ANSWER

            Answered 2018-Oct-18 at 08:59

            I think this sums up the error:- com.fasterxml.jackson.databind.exc.UnrecognizedPropertyException: Unrecognized field "StatusCode" (class biz.spsolutions.edgevantage.workflow.dao.PABCIntegration.ResultBasicAccountInformationDao), not marked as ignorable (5 known properties: "traceId", "status", "result", "errorList", "statusCode"])

            seems the field names do not match, one starts with capital S and the other small s. Please try changing it.

            Source https://stackoverflow.com/questions/52870387

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

            Vulnerabilities

            No vulnerabilities reported

            Install genrl

            GenRL is compatible with Python 3.6 or later and also depends on pytorch and openai-gym. The easiest way to install GenRL is with pip, Python's preferred package installer. Note that GenRL is an active project and routinely publishes new releases. In order to upgrade GenRL to the latest version, use pip as follows.

            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 .
            Find more information at:

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            Install
          • PyPI

            pip install genrl

          • CLONE
          • HTTPS

            https://github.com/SforAiDl/genrl.git

          • CLI

            gh repo clone SforAiDl/genrl

          • sshUrl

            git@github.com:SforAiDl/genrl.git

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