Bias not taken into account in compute_Linear_madd and compute_Linear_flops?

[atndel]

In compute_madds.py, for compute_Linear_madd, the number of additions computed is computed this way :

add = num_in_features - 1.

I guess it comes from the additions of the dot product between the input vector and the weights vector. But if the bias parameter of the torch.nn.Linear layer is True, an additional addition will be performed with that bias.So the correct formula should be
add = num_in_features, in case there is a bias.

There is the same problem with compute_Linear_flops in compute_flops,
inp.size()[1] * out.size()[1]
should be replaced by
(inp.size()[1]+1) * out.size()[1], if bias is True.