def reports (test_loader, y_test, name, net, device): count = 0 for inputs, _ in test_loader: inputs = inputs.to(device) outputs = net(inputs) outputs = np.argmax(outputs.detach().cpu().numpy(), axis=1) if count == 0: y_pred = outputs count = 1 else: y_pred = np.concatenate( (y_pred, outputs) ) if name == 'IP': target_names = ['Wheat', 'Woods']

elif name == 'MNIST': target_names = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'] else: target_names = ['Class 0', 'Class 1', 'Class 2', 'Class 3', 'Class 4'] print(classification_report(y_test, y_pred, target_names=target_names))