They will be returned to their original place.
Have a look at this example:
# Create input with 1s and 2s
x = Variable(torch.cat((torch.ones(1, 1, 10, 10), torch.ones(1, 1, 10, 10)*2), dim=0))
softmax = nn.Softmax(dim=0)
y = softmax(x.view(-1)).view(2, 1, 10, 10)
print(y)
y.sum()

Now, the whole Tensor is normalized, such that its sum is 1.