pytorch-normalizing-flows

by ritheshkumar95 Python Version: Current License: No License

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

kandi X-RAY | pytorch-normalizing-flows Summary

pytorch-normalizing-flows is a Python library. pytorch-normalizing-flows has no bugs, it has no vulnerabilities and it has low support. However pytorch-normalizing-flows build file is not available. You can download it from GitHub.

pytorch-normalizing-flows

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Quality

Security

License

Reuse

Support

pytorch-normalizing-flows has a low active ecosystem.

It has 18 star(s) with 0 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

pytorch-normalizing-flows has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pytorch-normalizing-flows is current.

Quality

pytorch-normalizing-flows has 0 bugs and 0 code smells.

Security

pytorch-normalizing-flows has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pytorch-normalizing-flows code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pytorch-normalizing-flows 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

pytorch-normalizing-flows releases are not available. You will need to build from source code and install.

pytorch-normalizing-flows has no build file. You will be need to create the build yourself to build the component from source.

pytorch-normalizing-flows saves you 81 person hours of effort in developing the same functionality from scratch.

It has 208 lines of code, 15 functions and 3 files.

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

Top functions reviewed by kandi - BETA

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

Train the model
A generator that yields numpy arrays
Evaluate the model
Evaluates the training data
Return binarized MNIST dataset
Generate samples

Get all kandi verified functions for this library.

pytorch-normalizing-flows Key Features

No Key Features are available at this moment for pytorch-normalizing-flows.

pytorch-normalizing-flows Examples and Code Snippets

No Code Snippets are available at this moment for pytorch-normalizing-flows.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install pytorch-normalizing-flows

You can download it from GitHub.
You can use pytorch-normalizing-flows 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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