PRCV2019 | # Using efficientNet pre_model from : https : //github

by daixiangzi Python Version: Current License: No License

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

kandi X-RAY | PRCV2019 Summary

PRCV2019 is a Python library. PRCV2019 has no bugs, it has no vulnerabilities and it has low support. However PRCV2019 build file is not available. You can download it from GitHub.

#Using efficientNet pre_model from :

Support

Quality

Security

License

Reuse

Support

PRCV2019 has a low active ecosystem.

It has 10 star(s) with 2 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

PRCV2019 has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of PRCV2019 is current.

Quality

PRCV2019 has no bugs reported.

Security

PRCV2019 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

PRCV2019 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

PRCV2019 releases are not available. You will need to build from source code and install.

PRCV2019 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 PRCV2019 and discovered the below as its top functions. This is intended to give you an instant insight into PRCV2019 implemented functionality, and help decide if they suit your requirements.

Main worker function
Train the model
Save a checkpoint
Adjust the learning rate
Create a model from pretrained pretrained weights
Get parameters for a given model
Construct an optimal network
Create an instance of an EfficientNet
Returns the size of a given model
Return the parameters for a given model
Checks that the model_name is valid
Forward forward computation
Extract features from inputs
Forward convolution layer
Drop - connected tensor
Encodes a list of blocks
Encode a block

Get all kandi verified functions for this library.

PRCV2019 Key Features

No Key Features are available at this moment for PRCV2019.

PRCV2019 Examples and Code Snippets

No Code Snippets are available at this moment for PRCV2019.

Community Discussions

No Community Discussions are available at this moment for PRCV2019.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install PRCV2019

You can download it from GitHub.
You can use PRCV2019 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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