GVB | Gradually Vanishing Bridge for Adversarial Domain Adaptation | Machine Learning library

by cuishuhao Python Version: Current License: MIT

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

kandi X-RAY | GVB Summary

GVB is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Generative adversarial networks applications. GVB 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.

Code release for "Gradually Vanishing Bridge for Adversarial Domain Adaptation" (CVPR 2020).

Support

Quality

Security

License

Reuse

Support

GVB has a low active ecosystem.

It has 67 star(s) with 8 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 2 have been closed. On average issues are closed in 1 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of GVB is current.

Quality

GVB has 0 bugs and 0 code smells.

Security

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

GVB code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

GVB 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

GVB 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.

GVB saves you 674 person hours of effort in developing the same functionality from scratch.

It has 1561 lines of code, 113 functions and 14 files.

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

Top functions reviewed by kandi - BETA

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

Train the image
Test for 10 - crop images
Test the image classification
Calculate CDAN network
Compute the GVB
Compute DAN
Test image
Create image target
Generate a training image
Calculates the entropy of the input tensor
Hook for applying the gradient transformation
Set the cuda matrix
Calculate the coefficients for a single iteration
Compute the gradient of the layer

Get all kandi verified functions for this library.

GVB Key Features

No Key Features are available at this moment for GVB.

GVB Examples and Code Snippets

No Code Snippets are available at this moment for GVB.

Community Discussions

Trending Discussions on GVB

Why is the perl hash overwriting previous data?

QUESTION

Why is the perl hash overwriting previous data?

Asked 2020-Oct-21 at 02:52

So, I'm writing data into my hash which is %errordata. It looks like this

...

ANSWER

Answered 2020-Oct-21 at 02:52

Perl hash assumes that each key is unique. If you would like to store more than one value or data structure under one key you need apply some logic how to achieve desired result.

Please see the following demo code to sort teachers and students from incoming data.

Source https://stackoverflow.com/questions/64455726

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

Vulnerabilities

No vulnerabilities reported

Install GVB

You can download it from GitHub.
You can use GVB 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.