rcnn-text-classification | Tensorflow Implementation of Recurrent | Machine Learning library

by roomylee Python Version: Current License: No License

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

kandi X-RAY | rcnn-text-classification Summary

rcnn-text-classification is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Neural Network applications. rcnn-text-classification has no bugs, it has no vulnerabilities and it has low support. However rcnn-text-classification build file is not available. You can download it from GitHub.

Tensorflow Implementation of "Recurrent Convolutional Neural Network for Text Classification" (AAAI 2015)

Support

Quality

Security

License

Reuse

Support

rcnn-text-classification has a low active ecosystem.

It has 132 star(s) with 48 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 6 open issues and 7 have been closed. On average issues are closed in 40 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of rcnn-text-classification is current.

Quality

rcnn-text-classification has 0 bugs and 0 code smells.

Security

rcnn-text-classification has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

rcnn-text-classification code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

rcnn-text-classification 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

rcnn-text-classification releases are not available. You will need to build from source code and install.

rcnn-text-classification 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.

rcnn-text-classification saves you 124 person hours of effort in developing the same functionality from scratch.

It has 313 lines of code, 11 functions and 4 files.

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

Top functions reviewed by kandi - BETA

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

Train the model
Cleans a string
Generator for batches of data
Load data and labels
Evaluate the model
Load data and labels from files

Get all kandi verified functions for this library.

rcnn-text-classification Key Features

No Key Features are available at this moment for rcnn-text-classification.

rcnn-text-classification Examples and Code Snippets

No Code Snippets are available at this moment for rcnn-text-classification.

Community Discussions

Trending Discussions on rcnn-text-classification

Use of PyTorch permute in RCNN

QUESTION

Use of PyTorch permute in RCNN

Asked 2021-Jan-14 at 21:57

I am looking at an implementation of RCNN for text classification using PyTorch. Full Code. There are two points where the dimensions of tensors are permuted using the permute function. The first is after the LSTM layer and before tanh. The second is after a linear layer and before a max pooling layer.

Could you please explain why the permutation is necessary or useful?

Relevant Code

...

ANSWER

Answered 2021-Jan-05 at 05:11

What permute function does is rearranges the original tensor according to the desired ordering, note permute is different from reshape function, because when apply permute, the elements in tensor follow the index you provide where in reshape it's not.

Example code:

Source https://stackoverflow.com/questions/65571264

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

Vulnerabilities

No vulnerabilities reported

Install rcnn-text-classification

You can download it from GitHub.
You can use rcnn-text-classification 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 .

Find more information at: