I get an output containing approx. 50% zeros using randn inputs, which seems to be expected:
model = DenseBlock(5, 3, 1)
x = torch.randn(8, 3, 24, 24)
out = model(x)
print((out == 0.).float().sum() / out.nelement())
> tensor(0.4957)