Hi Thomas,
Thanks a lot for your quick reaction. I was not aware of the existence of Module.named_parameters() and indeed it helped me understanding what was going on. The new output is:
conv.0.weight <class 'torch.nn.parameter.Parameter'> torch.Size([6, 3, 5, 5])
conv.0.bias <class 'torch.nn.parameter.Parameter'> torch.Size([6])
conv.3.weight <class 'torch.nn.parameter.Parameter'> torch.Size([16, 6, 5, 5])
conv.3.bias <class 'torch.nn.parameter.Parameter'> torch.Size([16])
fc.0.weight <class 'torch.nn.parameter.Parameter'> torch.Size([120, 400])
fc.0.bias <class 'torch.nn.parameter.Parameter'> torch.Size([120])
fc.2.weight <class 'torch.nn.parameter.Parameter'> torch.Size([84, 120])
fc.2.bias <class 'torch.nn.parameter.Parameter'> torch.Size([84])
fc.4.weight <class 'torch.nn.parameter.Parameter'> torch.Size([10, 84])
fc.4.bias <class 'torch.nn.parameter.Parameter'> torch.Size([10])

So these additional lines refer to the bias parameters. By the way I didn’t expect the bias to be constant for every channel so I learnt something else…
Best regards,
Adrien