8 bit quantization is used by default. However, it can be changed by using ``G_NUM_BITS`` global variable.
The following code snippet performs 4 bit quantization.

.. code:: python

    import tensorflow_quantization
    # get pretrained model
    .....

    # perform 4 bit quantization
    tensorflow_quantization.G_NUM_BITS = 4
    q_model = quantize_model(nn_model_original)

    # fine-tune model
    .....
    
Check ``test_end_to_end_workflow_4bit()`` test case from ``quantize_test.py`` test module.

If True, the absolute value of quantized minimum is the same as the quantized maximum value. For example,
minimum of -127 is used for 8 bit quantization instead of -128. TensorRT |tred| only supports G_NARROW_RANGE=True.

If True, 0.0 is always in the center of real min, max i.e. zero point is always 0. 
TensorRT |tred| only supports G_SYMMETRIC=True.