attention_keras | Keras Layer implementation of Attention for Sequential | Machine Learning library

by thushv89 Python Version: v0.1 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | attention_keras Summary

attention_keras is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras, Neural Network applications. attention_keras 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.

This is an implementation of Attention (only supports Bahdanau Attention right now).

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Quality

Security

License

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Support

attention_keras has a low active ecosystem.

It has 424 star(s) with 265 fork(s). There are 13 watchers for this library.

It had no major release in the last 12 months.

There are 6 open issues and 26 have been closed. On average issues are closed in 43 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of attention_keras is v0.1

Quality

attention_keras has 0 bugs and 0 code smells.

Security

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

attention_keras code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

attention_keras is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

attention_keras releases are available to install and integrate.

Build file is available. You can build the component from source.

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

attention_keras saves you 124 person hours of effort in developing the same functionality from scratch.

It has 313 lines of code, 16 functions and 9 files.

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

Top functions reviewed by kandi - BETA

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

Get training data
Read data from a text file
Preprocess data
Convert sentences to sequences
Define the input sequence

Get all kandi verified functions for this library.

attention_keras Key Features

No Key Features are available at this moment for attention_keras.

attention_keras Examples and Code Snippets

No Code Snippets are available at this moment for attention_keras.

Community Discussions

Trending Discussions on attention_keras

ConvLSTMCell in tensorflow 2

QUESTION

ConvLSTMCell in tensorflow 2

Asked 2020-Jan-14 at 08:03

After upgrade to tensorflow version 2 from 1, all modules from tf.contrib were depreciated.

In order to apply attention method, I need every cell's state.

Initially, what I did in tf version 1 was:

...

ANSWER

Answered 2020-Jan-14 at 07:43

I think that what you are looking for is here: https://www.tensorflow.org/api_docs/python/tf/keras/layers/ConvLSTM2D?version=stable

You can import it in your code like:

Source https://stackoverflow.com/questions/59729239

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

Vulnerabilities

No vulnerabilities reported

Install attention_keras

You can download it from GitHub.
You can use attention_keras 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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