title: How PyTorch model layer weights get initialized implicitly?
body: <p>I basically defined a model with a Conv2D and linear layer with PyTorch and trained it with a sample dataset. The model seems to run and converge. But I am wondering I did not explicitly initialize the model layer weights (normal or Xavier). Does that mean when I call model.train() before each epoch training, the layer weights will get initialized randomly by default ? If so, how can I explicitly change the type of initializations ?</p>