Sentence-VAE | Generating Sentences from a Continuous Space | Machine Learning library

by timbmg Python Version: Current License: No License

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

kandi X-RAY | Sentence-VAE Summary

Sentence-VAE is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Neural Network applications. Sentence-VAE has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

PyTorch Re-Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015

Support

Quality

Security

License

Reuse

Support

Sentence-VAE has a low active ecosystem.

It has 570 star(s) with 156 fork(s). There are 11 watchers for this library.

It had no major release in the last 6 months.

There are 11 open issues and 15 have been closed. On average issues are closed in 71 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Sentence-VAE is current.

Quality

Sentence-VAE has 0 bugs and 0 code smells.

Security

Sentence-VAE has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Sentence-VAE code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Sentence-VAE 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

Sentence-VAE releases are not available. You will need to build from source code and install.

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

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

Sentence-VAE saves you 207 person hours of effort in developing the same functionality from scratch.

It has 507 lines of code, 29 functions and 5 files.

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

Top functions reviewed by kandi - BETA

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

Performs the forward computation
Convert x into a variable
Initiate inference
Saves the given sample to the given index
Sample from distribution
Create the vocabulary
Create vocabulary
Load data
Loads the vocab
Return the expierment name
Convert index to word
Linear interpolation
Get i2w index

Get all kandi verified functions for this library.

Sentence-VAE Key Features

No Key Features are available at this moment for Sentence-VAE.

Sentence-VAE Examples and Code Snippets

No Code Snippets are available at this moment for Sentence-VAE.

Community Discussions

Trending Discussions on Sentence-VAE

How is KL-divergence in pytorch code related to the formula?

QUESTION

How is KL-divergence in pytorch code related to the formula?

Asked 2020-May-04 at 20:57

In VAE tutorial, kl-divergence of two Normal Distributions is defined by:

And in many code, such as here, hereand here, the code is implemented as:

...

ANSWER

Answered 2020-May-04 at 20:57

The expressions in the code you posted assume X is an uncorrelated multi-variate Gaussian random variable. This is apparent by the lack of cross terms in the determinant of the covariance matrix. Therefore the mean vector and covariance matrix take the forms

Using this we can quickly derive the following equivalent representations for the components of the original expression

Substituting these back into the original expression gives

Source https://stackoverflow.com/questions/61597340

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

Vulnerabilities

No vulnerabilities reported

Install Sentence-VAE

You can download it from GitHub.
You can use Sentence-VAE 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: