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Ternary Weight Networks

A PyTorch implementation of Ternary Weight Networks

Training

This repository contains two example scripts to get started: main_mnist.py and main_cifar10.py.

MNIST

For MNIST we use a ternary version of the LeNet5 architecture and train for 10 epochs

python3 main_mnist.py

CIFAR10

For CIFAR10 we use a ternary version of the MobileNetV2 architecture and train for 200 epochs

python3 main_cifar10.py

Results

Dataset Model Ternary Test Acc FP32 Test Acc
MNIST LeNet5 99.14% 99.25%
CIFAR10 MobileNetV2 93.38% 94.52%

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