Wrong prediction of C Simulation compared to QKeras? about hls4ml HOT 3 OPEN

I realized that the weights in the C++ code are much larger then the ones of QKeras. In fact by a factor 64. Is this correct?

//Numpy array shape [3, 3, 1, 1]
//Min -0.669433593750
//Max 0.915435791016
//Number of zeros 0

#ifndef W2_H_
#define W2_H_

#ifndef __SYNTHESIS__
weight2_t w2[9];
#else
weight2_t w2[9] = {-29.462890625, 22.447265625, 58.587890625, 26.078125000, -19.662109375, -8.080078125, -23.574218750, -42.843750000, -10.302734375};
#endif

#endif

from hls4ml.

I found the reason for the scaled weights. In QKeras, if the quantizer's alpha is none, the weights are scaled by a certain factor equal to the data type scale. And hls4ml puts this layer to normalize the scaling factor:

nnet::normalize<layer2_t, result_t, config4>(layer2_out, layer4_out, s4, b4); // fused_convbn_0_alpha

However, the fact that the scaling creates the overflow seems a bug to me.

To avoid this I specifically set alpha=1: quantized_bits(16,6,alpha=1)

from hls4ml.