SemiNAS | repository contains the code

by renqianluo Python Version: Current License: Apache-2.0

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

kandi X-RAY | SemiNAS Summary

SemiNAS is a Python library. SemiNAS has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However SemiNAS build file is not available. You can download it from GitHub.

This repository contains the code used for Semi-Supervised Neural Architecture Search, by Renqian Luo, Xu Tan, Rui Wang, Tao Qin, En-Hong Chen, Tie-Yan Liu.

Support

Quality

Security

License

Reuse

Support

SemiNAS has a low active ecosystem.

It has 12 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

SemiNAS has no issues reported. On average issues are closed in 10 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of SemiNAS is current.

Quality

SemiNAS has no bugs reported.

Security

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

License

SemiNAS is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

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

Build model configuration
Builds a model
Build a layer from a given layer configuration
Build a NASNet from a configuration dictionary
Build a new MobileResidualResidualResidualResidualBlock from the given configuration
Train the model
Compute accuracy
Sample from arch_pool
Move tensor to GPU
Generate synthetic controller data
Calculate the objective function for validation
Convert sequence to archiv
Run child validation
Save a checkpoint
Perform the forward pass through the encoder
Infer the model
Calculate the number of flops
Load a checkpoint
Helper function for controller inference
Return the configuration for the NASNet
Create the directory for the experiment
Train controller
Reads all the files in the zip archive
Read images
Weighted weight function
Finds all the classes in a zip file

Get all kandi verified functions for this library.

SemiNAS Key Features

No Key Features are available at this moment for SemiNAS.

SemiNAS Examples and Code Snippets

No Code Snippets are available at this moment for SemiNAS.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install SemiNAS

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

Find more information at: