vai_q_tensorflow2 supports data type conversions for float models, including Float16, BFloat16,
Float, and Double. The following codes show how to perform the data type conversions
with vai_q_tensorflow2
API.
model = tf.keras.models.load_model(‘float_model.h5’)
from tensorflow_model_optimization.quantization.keras import vitis_quantize
quantizer = vitis_quantize.VitisQuantizer(model)
quantized_model = quantizer.quantize_model(convert_datatype='float16'
**kwargs) - convert_datatype
- A string object, indicates the target data type for the float model. Options are 'float16', 'bfloat16', 'float32', and 'float64'. Default value is 'float16'