Involution | PyTorch reimplementation of the paper Involution | Computer Vision library

by ChristophReich1996 Python Version: Current License: MIT

X-Ray Key Features Code Snippets(1)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | Involution Summary

Involution is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Pytorch applications. Involution 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.

Unofficial PyTorch reimplementation of the paper Involution: Inverting the Inherence of Convolution for Visual Recognition by Duo Li, Jie Hu, Changhu Wang et al. published at CVPR 2021. Please note that the official implementation provides a more memory efficient CuPy implementation of the 2D involution.

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Involution has a low active ecosystem.

It has 63 star(s) with 14 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 6 have been closed. On average issues are closed in 2 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Involution is current.

Quality

Involution has no bugs reported.

Security

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

License

Involution 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

Involution 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, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Initialize Convolution 3d .
Compute the input tensor .
Return a human - readable representation of the kernel .

Get all kandi verified functions for this library.

Involution Key Features

No Key Features are available at this moment for Involution.

Involution Examples and Code Snippets

Generator for involution changes .

python

Lines of Code : 29

License : No License

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def InvolutionChanges(n):
    """Generate change sequence for involutions on n items.
    Uses a variation of the Steinhaus-Johnson-Trotter idea,
    in which we first recurse for n-1, generating involutions
    in which the last item is fixed, and t

Community Discussions

Trending Discussions on Involution

Is it possible to prove this defined function is an involution in z3?

Boolean Expression with Laws

QUESTION

Is it possible to prove this defined function is an involution in z3?

Asked 2021-Jan-29 at 20:04

I'm trying to understand how to define an assertion in such a way that it proves certain mathematical qualities of an already defined function. As discussed in this post SMT solvers are not well-suited for induction, which is often needed to prove a mathematical quality.

In my case, I have a recursive function definition for the identity function f(x) = x (just as a simple example):

...

ANSWER

Answered 2021-Jan-29 at 20:04

There isn't really much you can do here. Ideally, the strategy would be to define and prove the base case and the inductive-step separately, and then argue (at the meta-level) that the property is true for all strings.

For the base-case things are easy enough. I'd define:

Source https://stackoverflow.com/questions/65954675

QUESTION

Boolean Expression with Laws

Asked 2019-Oct-18 at 10:28

Hello can somebody help me? How this boolean expression simplified?

...

ANSWER

Answered 2019-Oct-18 at 10:28

Boolean Expression: abcd + d can be simplified as -

Source https://stackoverflow.com/questions/58448567

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

Vulnerabilities

No vulnerabilities reported

Install Involution

The 2D and 3D involution can be easily installed by using pip.

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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