infi | building input filters for trained models

by yuanmu97 Python Version: Current License: MIT

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

kandi X-RAY | infi Summary

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

InFi is a library for building input filters for trained models to be deployed, so as to improve the resource efficiency in the inference phase.

Support

Quality

Security

License

Reuse

Support

infi has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of infi is current.

Quality

infi has no bugs reported.

Security

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

License

infi is licensed under the MIT License. This license is Permissive.

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

Reuse

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

infi has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of infi

Get all kandi verified functions for this library.

infi Key Features

No Key Features are available at this moment for infi.

infi Examples and Code Snippets

No Code Snippets are available at this moment for infi.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install infi

InFi has been tested on Python 3.7, TensorFlow 2.4, and MindSpore 1.5. You need to install at least one of TensorFlow or MindSpore. If you'd like to play with jupyter notebook examples, you need to install Jupyter-Lab.
We use the speech recognition workload on Hollywood2 dataset as an example to show how to train and evaluate InFi-Skip. You can download the raw data (infi_dataset_hollywood2) from google drive. The full code can be found in examples/.

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: