Type weirdness in ResNet9 submission code

[Guan-t7]

hw4/tests/hw4/test_conv.py

Lines 471 to 483 in 1ef8c3b

	def one_iter_of_cifar10_training(dataloader, model, niter=1, loss_fn=ndl.nn.SoftmaxLoss(), opt=None, device=None):
	np.random.seed(4)
	model.train()
	correct, total_loss = 0, 0
	i = 1
	for batch in dataloader:
	opt.reset_grad()
	X, y = batch
	X,y = ndl.Tensor(X, device=device), ndl.Tensor(y, device=device)
	out = model(X)
	correct += np.sum(np.argmax(out.numpy(), axis=1) == y.numpy())
	loss = loss_fn(out, y)
	total_loss += loss.data.numpy() * y.shape[0]

Is it intended that correct is a float scalar and total_loss is a np array? They're heterogenous but later fed into ndl.Tensor ctor, leading to Error.