TensorKart | self-driving MarioKart with TensorFlow | Machine Learning library

 by   kevinhughes27 Python Version: Current License: MIT

kandi X-RAY | TensorKart Summary

kandi X-RAY | TensorKart Summary

TensorKart is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. TensorKart has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

self-driving MarioKart with TensorFlow.
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              TensorKart has a medium active ecosystem.
              It has 1545 star(s) with 256 fork(s). There are 60 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 11 open issues and 30 have been closed. On average issues are closed in 50 days. There are 2 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of TensorKart is current.

            kandi-Quality Quality

              TensorKart has 0 bugs and 27 code smells.

            kandi-Security Security

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

            kandi-License License

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

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              TensorKart releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              TensorKart saves you 168 person hours of effort in developing the same functionality from scratch.
              It has 417 lines of code, 25 functions and 4 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed TensorKart and discovered the below as its top functions. This is intended to give you an instant insight into TensorKart implemented functionality, and help decide if they suit your requirements.
            • Record the recording button
            • Start recording
            • Draw the plot
            • Pause the animation
            • Grab a screenshot from the screen
            • Poll the controller
            • Saves controller data
            • Updates the plot data
            • Get action calibration
            • Read the contents of the robot
            • Resize an image
            • Show a viewer
            • Load image files
            • Prepare data for training
            • Create a tensorflow model
            Get all kandi verified functions for this library.

            TensorKart Key Features

            No Key Features are available at this moment for TensorKart.

            TensorKart Examples and Code Snippets

            No Code Snippets are available at this moment for TensorKart.

            Community Discussions

            QUESTION

            NaN result when summing two tensors which individually are both real numbers
            Asked 2017-Mar-29 at 20:16

            So I've been playing with this interesting application of tensorflow: TensorKart

            The full source code is here: https://github.com/kevinhughes27/TensorKart

            I'm getting a NaN result in my loss calculation and it's totally stumped me. The problem lies in this line of code:

            ...

            ANSWER

            Answered 2017-Mar-29 at 20:16

            So after having gone through every operation leading up to the calculation of the loss value, it turns out there were NaN values in my input data. Converting them to zero resolved the issue of getting a NaN result in the final loss value calculation.

            What I haven't figured out till now is why I was only getting an error at the point I sum the two parts of the loss value but not while calculating the parts individually.

            Utterly bizarre.

            Source https://stackoverflow.com/questions/42352930

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

            Vulnerabilities

            No vulnerabilities reported

            Install TensorKart

            You can download it from GitHub.
            You can use TensorKart like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            Open a PR! I promise I am friendly :).
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            CLONE
          • HTTPS

            https://github.com/kevinhughes27/TensorKart.git

          • CLI

            gh repo clone kevinhughes27/TensorKart

          • sshUrl

            git@github.com:kevinhughes27/TensorKart.git

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