A standalone package to do the vitis quantization step.
THIS IS NOT AN OFFICIAL XILINX PACKAGE
A pip installable package to do the vitis model quantization for tensorflow 2.
This is a migration of the code here
to a standalone pip package that won't conflict with the
Working in the docker image is annoying and this code should be standalone.
pip install vitis-quantizer
Build from source:
python3 setup.py bdist_wheel pip install dist/vitis_quantizer-0.1.0-py3-none-any.whl
Usage is the same as Vitis AI models.
import tensorflow as tf import vitis_quantizer # Train/Get/Make a keras model somehow model = tf.keras.models.load_model("/path/to/keras/model") quantizer = vitis_quantizer.VitisQuantizer(model) with vitis_quantizer.quantize_scope(): quantized_model = quantizer.quantize_model(calib_dataset=dataset) quantized_model.save("/path/to/save/quantized/model")
After you have the quantized model saved, use vitis compile.sh script.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
vitis-quantizer-0.1.3.tar.gz (171.6 kB view hashes)