def make_predictions(self, net, data, labels, num_classes):
		data = np.require(data, requirements='C')
		labels = np.require(labels, requirements='C')

		preds = np.zeros((data.shape[1], num_classes), dtype=np.single)
		softmax_idx = net.get_layer_idx('probs', check_type='softmax')

		t0 = time.time()
		net.libmodel.startFeatureWriter(
			[data, labels, preds], softmax_idx)
		net.finish_batch()
		print "Predicted %s cases in %.2f seconds." % (
			labels.shape[1], time.time() - t0)

		if net.multiview_test:
			# We have to deal with num_samples * num_views
			# predictions.
			num_views = net.test_data_provider.num_views
			num_samples = num_views / labels.shape[1]
			split_sections = range(
				num_samples, num_samples * num_views, num_samples)
			preds = np.split(preds, split_sections, axis=0)
			labels = np.split(labels, split_sections, axis=1)
			preds = reduce(np.add, preds)
			labels = labels[0]

		return preds, labels
dataset/ETHPy150Open zygmuntz/kaggle-cifar/shownet.py/ShowConvNet.make_predictions/swapped operands of `/`