Hi,
thank you so much for your answer and please excuse me, but there are 2 scales that seems connected to the weights. The one inside the tensor parameters and the one of the layer. In my example:



 dassima:

(u'conv_3x3_32a.weight', tensor([[
          [[ 0.0367,  0.0294, -0.1065],
          [ 0.0918,  0.1065, -0.0331],
          [-0.0147,  0.0184, -0.1028]]],
.......
          [[[ 0.1249,  0.0661, -0.0257],
          [ 0.0735, -0.0257, -0.1028],
          [ 0.0441, -0.0698, -0.0771]]]], size=(40, 1, 3, 3),
       dtype=torch.qint8, quantization_scheme=torch.per_tensor_affine,
       scale=0.00367316859774, zero_point=0)



and



 dassima:

(u'conv_3x3_32a.scale', tensor(0.0031))


so number 0.00367316859774  and 0.0031 which generate different results. If the 0.0031 does the actual conversion from 32FP to 8INT, what does 0.00367316859774 ?