Is it possible to perform batch normalization in a network that is only linear layers?
For example:
class network(nn.Module):
    def __init__(self):
        super(network, self).__init__()
        self.linear1 = nn.Linear(in_features=40, out_features=320)
        self.linear2 = nn.Linear(in_features=320, out_features=2)

    def forward(input):  # Input is a 1D tensor
        y = F.relu(self.linear1(input))
        # Would it be possible to do a batch normalization of y overhere? If so how?
        y = F.softmax(self.linear2(input))
        return y