Quantize
from tensorflow_model_optimization.quantization.keras import vitis_quantize
quantizer = vitis_quantize.VitisQuantizer(model)
quantized_model = quantizer.quantize_model(calib_dataset=calib_dataset)
Evaluate the Quantized Model
quantized_model.compile(loss=your_loss, metrics=your_metrics)
quantized_model.evaluate(eval_dataset)
Load the Quantized Model
from tensorflow_model_optimization.quantization.keras import vitis_quantize
with vitis_quantize.quantize_scope():
model = keras.models.load_model('./quantized_model.h5')
Dump the Quantized Model
from tensorflow_model_optimization.quantization.keras import vitis_quantize
with vitis_quantize.quantize_scope():
quantized_model = keras.models.load_model('./quantized_model.h5')
vitis_quantize.VitisQuantizer.dump_model(quantized_model, dump_dataset)