tqdm to replace training loop

For a nicer progress bar, replace for _ in range(1000) with tqdm.

losses = []
with tqdm.notebook.tqdm(range(1000)) as tepoch:
	for _ in tepoch:
		tepoch.set_description(f"Epoch")
		optimizer.zero_grad()
		output = model(X_train)
		loss = -mll(output, y_train)
		loss.backward()
		optimizer.step()
		losses.append(loss.item())
		tepoch.set_postfix(loss=loss.item())