For layers without parameters (like ReLU and Dropout) it doesn’t matter. But for layers with parameters (like Linear), the two are very different. The first is a feed-forward net with 300 total parameters. The second is a sort of recurrent network with only 100 parameters. Generally, you want the first. (If you are trying to use recurrent networks you should look at the RNN classes)