kandi X-RAY | mobile-pruning Summary
kandi X-RAY | mobile-pruning Summary
mobile-pruning is a Python library. mobile-pruning has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However mobile-pruning build file is not available. You can download it from GitHub.
mobile-pruning
mobile-pruning
Support
Quality
Security
License
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Support
mobile-pruning has a low active ecosystem.
It has 6 star(s) with 1 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
mobile-pruning has no issues reported. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of mobile-pruning is current.
Quality
mobile-pruning has no bugs reported.
Security
mobile-pruning has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
mobile-pruning is licensed under the GPL-3.0 License. This license is Strong Copyleft.
Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
Reuse
mobile-pruning releases are not available. You will need to build from source code and install.
mobile-pruning 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 mobile-pruning and discovered the below as its top functions. This is intended to give you an instant insight into mobile-pruning implemented functionality, and help decide if they suit your requirements.
- Train a trained model
- Get loaders
- Load a checkpoint
- Save checkpoint
- Perform the forward transformation
- Calculates the weighted weight of the log likelihood
- Adjust the shape of src_shape
- Compute the KL divergence of a tensor
- Creates a torch nn ModuleList
- Create a list of LinearBottleneckIBs
- Make the bottleneck module
- Create a train stage
- Create an hdf5 file
- Check if filename has extension
- Copy the experiment from one log file to another
- Create a CUDA device from a config file
- Update a config
- Returns the probability density of the model
Get all kandi verified functions for this library.
mobile-pruning Key Features
No Key Features are available at this moment for mobile-pruning.
mobile-pruning Examples and Code Snippets
No Code Snippets are available at this moment for mobile-pruning.
Community Discussions
No Community Discussions are available at this moment for mobile-pruning.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install mobile-pruning
You can download it from GitHub.
You can use mobile-pruning 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.
You can use mobile-pruning 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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