cac 1.0.0

Description:

cac 1.0.0

What's CAC
This repository contains a library of Content-Aware Computing (CAC) by Fujitsu.
CAC is a software technology that aims at easy, high-speed, lightweight, and accurate deep learning processing.
Contents
1. Gradient-Skip
Gradient-Skip is an approach for CNNs to skip backward calculations for layers that enouch converged.
This reduces calculations in backward and communications of gradient.
You can use Gradient-Skip by simply replacing the optimizer with our SGD.
Python Source
Example
2. Automatic Pruner
Automatic Pruner is a pruning tool for neural networks, which can determine the pruning rate of each layer automatically.
Python Source
Example
3. Synchronous-Relaxation
Relaxed Synchronization technique removes slow processes from the group of distributed training and prevent limiting overall training speed due to slow processes.
Python Source
Example
Requirements
Python 3.6 or later
CUDA 10 or later
PyTorch 1.6 or later
Apex
Quick Start
Linux
git clone https://github.com/FujitsuLaboratories/CAC.git
cd CAC
python setup.py install

CAC will be registered in PyPI at a later date and will be able to pip install
pip install -v --disable-pip-version-check --no-cache-dir ./