anon_submission | extensible software framework that allows a user to do

 by   akamaster Python Version: Current License: BSD-3-Clause

kandi X-RAY | anon_submission Summary

kandi X-RAY | anon_submission Summary

anon_submission is a Python library. anon_submission has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

lc-model-compression is a flexible, extensible software framework that allows a user to do optimal compression, with minimal effort, of a neural network or other machine learning model using different compression schemes. it is based on the learning-compression (lc) algorithm, which performs an iterative optimization of the compressed model by alternating a learning (l) step with a compression (c) step. this decoupling of the "machine learning" and "signal compression" aspects of the problem make it possible to use a common optimization and software framework to handle any choice of model and compression scheme; all that is needed to compress model x with compression y is to call the corresponding algorithms in the l and c steps, respectively. the software fully supports this by design, which makes it flexible and extensible. a number of neural networks and compression schemes are currently supported, and we expect to
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              anon_submission has a low active ecosystem.
              It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              anon_submission has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of anon_submission is current.

            kandi-Quality Quality

              anon_submission has no bugs reported.

            kandi-Security Security

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

            kandi-License License

              anon_submission 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.

            kandi-Reuse Reuse

              anon_submission 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, examples and code snippets are available.

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            anon_submission Key Features

            No Key Features are available at this moment for anon_submission.

            anon_submission Examples and Code Snippets

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            Community Discussions

            No Community Discussions are available at this moment for anon_submission.Refer to stack overflow page for discussions.

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

            Vulnerabilities

            No vulnerabilities reported

            Install anon_submission

            We recommend installing the dependencies through conda into a new environment:.

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          • HTTPS

            https://github.com/akamaster/anon_submission.git

          • CLI

            gh repo clone akamaster/anon_submission

          • sshUrl

            git@github.com:akamaster/anon_submission.git

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