A standalone package to do the vitis quantization step.
Project description
Vitis Quantizer
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 tensorflow-model-optimization
package.
Working in the docker image is annoying and this code should be standalone.
Install
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
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.
Project details
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vitis-quantizer-0.1.3.tar.gz
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