static_quant

ImageNet Quantization

This implements quantization of popular model architectures, such as ResNet on the ImageNet dataset.

Requirements

• Install requirements
• pip install -r requirements.txt
• Download the ImageNet dataset from http://www.image-net.org/
  • Then, move and extract the training and validation images to labeled subfolders, using the following shell script

Quantizaiton

To quant a model and validate accaracy, run main.py with the desired model architecture and the path to the ImageNet dataset:

export ImageNetDataPath=/path/to/imagenet
python main.py $ImageNetDataPath --pretrained -a resnet18 --tune --calib_iters 5

Use Dummy Data

ImageNet dataset is large and time-consuming to download. To get started quickly, run main.py using dummy data by "--dummy". Note that the loss or accuracy is useless in this case.

python main.py -a resnet18 --dummy -q -e