ram | recurrent model of visual attention

by zhang0jhon Python Version: Current License: No License

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kandi X-RAY | ram Summary

ram is a Python library. ram has no bugs, it has no vulnerabilities and it has low support. However ram build file is not available. You can download it from GitHub.

Implementation of "Recurrent Models of Visual Attention" V. Mnih et al. Modified from NOTICE: tf.stop_gradient should be applied to location sampled from Gaussian distribution parametered by (mean, std), so actor-critic reinforcement learning back propagate mean with (reward-tf.stop_gradient(baselines)) * loglikelihood to update loc network. Futhermore, baseline network is updated by (R-baseline)^2. Run by python ram.py and it can reproduce the result on Table 1 (a) 28x28 MNIST.

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ram has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of ram is current.

Quality

ram has no bugs reported.

Security

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

License

ram 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

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

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

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ram Key Features

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ram Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install ram

You can download it from GitHub.
You can use ram 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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