以我跑过的模型为例：
原始model.predict
clock1 = time.time()
Y_pred = model.predict(X_test)
print('model.predict(X_test) time is'，time.time() - clock1, 's')
输出：
model.predict(X_test) time is 880.3435561656952 s
解决方法1
clock2 = time.time()
Y_pred = = model(X_test, training=False)
Y_pred = = np.array(Y_pred )
print('model(X_test, training=False) time is'，time.time() - clock2, 's')
输出：
model(X_test, training=False) time is 0.2510557174682617 s
解决方法2
clock3= time.time()
Pre = model.predict(x=tf.data.Dataset.from_tensors(X_test))
print('model.predict(x=tf.data.Dataset.from_tensors(X_test)) time is', time.time() - clock3, 's')
输出：
model.predict(x=tf.data.Dataset.from_tensors(X_test)) time is 0.26605892181396484 s
参考：https://blog.csdn.net/qq_41726670/article/details/117771138
