cca.pytorch | CCAs for looking into DNNs

by moskomule Python Version: Current License: No License

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

kandi X-RAY | cca.pytorch Summary

cca.pytorch is a Python library. cca.pytorch has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

CCAs for looking into DNNs

Support

Quality

Security

License

Reuse

Support

cca.pytorch has a low active ecosystem.

It has 55 star(s) with 7 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 6 have been closed. On average issues are closed in 50 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of cca.pytorch is current.

Quality

cca.pytorch has 0 bugs and 0 code smells.

Security

cca.pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

cca.pytorch code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

cca.pytorch 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

cca.pytorch 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.

cca.pytorch saves you 73 person hours of effort in developing the same functionality from scratch.

It has 190 lines of code, 18 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 cca.pytorch and discovered the below as its top functions. This is intended to give you an instant insight into cca.pytorch implemented functionality, and help decide if they suit your requirements.

Compute the CCA distance between two tensors
Reshape a tensor
2D concatenation of two tensors
Returns the value of the predicted value
Compute the Euclidean distance between two series
Compute the covariance matrix
Svd of x and y
Reduction reduction op
Zero mean of tensor
Compute the Poisson distance between two points
Load data from dataset
Plot the given history of layers

Get all kandi verified functions for this library.

cca.pytorch Key Features

No Key Features are available at this moment for cca.pytorch.

cca.pytorch Examples and Code Snippets

No Code Snippets are available at this moment for cca.pytorch.

Community Discussions

No Community Discussions are available at this moment for cca.pytorch.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install cca.pytorch

You can download it from GitHub.
You can use cca.pytorch 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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