RAdam | MXNet implementation of RAdam optimizer | Machine Learning library

by mnikitin Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | RAdam Summary

RAdam is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. RAdam has no bugs, it has no vulnerabilities and it has low support. However RAdam build file is not available. You can download it from GitHub.

MXNet implementation of RAdam optimizer from On the Variance of the Adaptive Learning Rate and Beyond paper.

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Quality

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Support

RAdam has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

RAdam has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of RAdam is current.

Quality

RAdam has 0 bugs and 0 code smells.

Security

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

RAdam code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

RAdam does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

RAdam releases are not available. You will need to build from source code and install.

RAdam has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 211 lines of code, 7 functions and 2 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed RAdam and discovered the below as its top functions. This is intended to give you an instant insight into RAdam implemented functionality, and help decide if they suit your requirements.

Main function .
Parse command line arguments .
Update the state function .
Initializer .
Create the state for a given weight

Get all kandi verified functions for this library.

RAdam Key Features

No Key Features are available at this moment for RAdam.

RAdam Examples and Code Snippets

No Code Snippets are available at this moment for RAdam.

Community Discussions

Trending Discussions on RAdam

How to solve a type error while using RAdam optimizer?

How to import tensorflow in google colab

QUESTION

How to solve a type error while using RAdam optimizer?

Asked 2021-Apr-28 at 19:08

I am building a neural network using keras and tensorflow and I get a error at this place

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ANSWER

Answered 2021-Apr-28 at 19:08

For others who may be looking for another solution.

RAdam is not in tensorflow.keras.optimizers and neither in keras by default, but in tensorflow-addons package, which is a better alternative (IMHO) than the external keras_radam library, considerably less prone to errors.

What you are looking for is here: https://www.tensorflow.org/addons/api_docs/python/tfa/optimizers/RectifiedAdam

Source https://stackoverflow.com/questions/67231257

QUESTION

How to import tensorflow in google colab

Asked 2020-Aug-02 at 08:57

Google Colab seems throwing the below error while trying to import Tensorflow, while it was working okey couple of weeks ago

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ANSWER

Answered 2020-Jul-26 at 14:26

This should suffice i feel %tensorflow_version 2.x import tensorflow as tf

This has always worked for me in Google Colab. I think the issue is that you are giving %tensorflow_version as 1.x please try changing that to 2.x

Source https://stackoverflow.com/questions/63100247

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

Vulnerabilities

No vulnerabilities reported

Install RAdam

You can download it from GitHub.
You can use RAdam 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

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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