def eval(model, x, y):
y_pred = np.argmax(model.predict(x), axis=1)
y_test = np.squeeze(y)
bca = utils.bca(y_test, y_pred)
acc = np.sum(y_pred == y_test).astype(np.float32) / len(y_pred)
return acc, bca
# print(v.shape)
y_adv_pre = np.argmax(model.predict(adv_x), axis=1)
adv_acc = np.sum(y_adv_pre == y_test) / len(y_adv_pre)
print('raw acc: ', raw_acc)
print('rand_acc: ', rand_acc)
print('adv_acc: ', adv_acc)
# print(y_adv_pre)
# print(y_test)
# exit()
raw_accs.append(raw_acc)
rand_accs.append(rand_acc)
adv_accs.append(adv_acc)
raw_bca = utils.bca(y_test, y_test_pre)
rand_bca = utils.bca(y_test, y_rand_pre)
adv_bca = utils.bca(y_test, y_adv_pre)
raw_bcas.append(raw_bca)
rand_bcas.append(rand_bca)
adv_bcas.append(adv_bca)
np.savez(os.path.join(checkpoint_path, 'adv_v.npz'), v=v)
K.clear_session()
print(raw_accs)
print(rand_accs)
print(adv_accs)
print('\n')
print(raw_bcas)
print(rand_bcas)
