DGCNN | Dilate Gated Convolutional Neural Network For Machine | Natural Language Processing library

by Chiang97912 Python Version: Current License: MIT

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

kandi X-RAY | DGCNN Summary

DGCNN is a Python library typically used in Artificial Intelligence, Natural Language Processing, Tensorflow applications. DGCNN has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However DGCNN build file is not available. You can download it from GitHub.

DGCNN，全名为Dilate Gated Convolutional Neural Network，即“膨胀门卷积神经网络”，顾名思义，融合了两个比较新的卷积用法：膨胀卷积、门卷积，并增加了一些人工特征和trick，最终使得模型在轻、快的基础上达到最佳的效果。.

Support

Quality

Security

License

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Support

DGCNN has a low active ecosystem.

It has 31 star(s) with 16 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 526 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DGCNN is current.

Quality

DGCNN has no bugs reported.

Security

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

License

DGCNN 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

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

DGCNN 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.

Top functions reviewed by kandi - BETA

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

Build the model
Attention layer
Conv1d block
Creates output layer
Run optimizer
Embed embedding layer
Compute accuracy
Load questions from file
Convert a sentence to an index
Multihead attention layer
Mask inputs
Return the config
Parse config from a json file
Load word embeddings
Generate next batch

Get all kandi verified functions for this library.

DGCNN Key Features

No Key Features are available at this moment for DGCNN.

DGCNN Examples and Code Snippets

No Code Snippets are available at this moment for DGCNN.

Community Discussions

Trending Discussions on DGCNN

Stellargraph failing to work with data shuffle

tf.gather with indices of higher dimention than input data?

QUESTION

Stellargraph failing to work with data shuffle

Asked 2021-Jun-08 at 16:23

when I ran the StellarGraph's demo on graph classification using DGCNNs, I got the same result as in the demo.

However, when I tested what happens when I first shuffle the data using the following code:

...

ANSWER

Answered 2021-Jun-08 at 16:23

I found the problem. It wasn't anything to do with the shuffling algorithm, nor with StellarGraph's implementation. The problem was in the demo, at the following lines:

Source https://stackoverflow.com/questions/67779173

QUESTION

tf.gather with indices of higher dimention than input data?

Asked 2018-Dec-02 at 21:09

Reading Dynamic Graph CNN for Learning on Point Clouds code, I came across this snippet:

...

ANSWER

Answered 2018-Dec-02 at 21:09

An equivalent function in numpy is np.take, a simple example:

Source https://stackoverflow.com/questions/53578484

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

Vulnerabilities

No vulnerabilities reported

Install DGCNN

You can download it from GitHub.
You can use DGCNN 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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