CopyNet | incorporating copying mechanism in sequence-to-sequence | Data Labeling library

by MultiPath Python Version: Current License: MIT

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

kandi X-RAY | CopyNet Summary

CopyNet is a Python library typically used in Artificial Intelligence, Data Labeling, Tensorflow, Neural Network applications. CopyNet has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However CopyNet build file is not available. You can download it from GitHub.

incorporating copying mechanism in sequence-to-sequence learning.

Support

Quality

Security

License

Reuse

Support

CopyNet has a low active ecosystem.

It has 175 star(s) with 65 fork(s). There are 11 watchers for this library.

It had no major release in the last 6 months.

There are 5 open issues and 1 have been closed. On average issues are closed in 7 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of CopyNet is current.

Quality

CopyNet has no bugs reported.

Security

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

License

CopyNet 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

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

CopyNet has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

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

Calculate the Lecun of a shape
Determine fan_in and out of shape
Generate a shared shared X
Calculate erase and add to the erase space
Sigmoid function
Compute the dot product of a matrix
Generate a shared orthogonal x
Compute the shared shared shared shared feature
Return a shared zeros
Create an array of shared zeros
Return a shared one
Creates a shared array with shared ones
Deprecated
Softmax of x
Convert probabilities to classes
Convert categorical probabilities to the largest class
Calculate the characteristic density of a shape
Create a normal distribution
Return the density of a shape
Create an identity matrix
Return a glorot normal
Get the erase and add the erase and add it to the diagonal
R Calculate a uniform shape
Softmax function

Get all kandi verified functions for this library.

CopyNet Key Features

No Key Features are available at this moment for CopyNet.

CopyNet Examples and Code Snippets

No Code Snippets are available at this moment for CopyNet.

Community Discussions

Trending Discussions on CopyNet

apply same JavaScript code to several canvas?

QUESTION

apply same JavaScript code to several canvas?

Asked 2019-Nov-19 at 17:15

I'm trying to apply some JavaScript to canvas, all canvas have the same height and width properties. Since I'm a very beginner in JavaScript and I've never really manipulated canvas on HTML, is it possible to do that by simply using one JavaScript file ?

I've found another question that is really similar to my problem here : how to use same script.js file for calling different CSS class using multiple Ids

but even when i try the provided solution the code is even more broken as before.

Here is my HTML display for testing

...

ANSWER

Answered 2019-Nov-19 at 17:15

The minimal intrusion is probably to copy your canvas pixels to your destination canvas.

Since the update draws your canvas, we can assume that after each updates, the canvas is to be copied:

Source https://stackoverflow.com/questions/58938135

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

Vulnerabilities

No vulnerabilities reported

Install CopyNet

You can download it from GitHub.
You can use CopyNet 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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