Thank you. I tried the solution that you suggested but it seems that this object does not share the same memory as the initial model.
Here is an example code:
net = nn.ModuleList()
net.append(nn.Conv2d(3, 8, 3))
net.append(nn.Conv2d(8, 8, 3))
net.append(nn.Conv2d(8, 1, 3)) 

unrolled = torch.cat([param.view(-1) for param in net.parameters()])
unrolled.fill_(3.14)
print(net[0].weight[0,0,0,0])
print(unrolled[0])

Outputs:
tensor(0.0684, grad_fn=SelectBackward)
tensor(3.1400, grad_fn=SelectBackward)