您传递给模型的 Numpy 数组列表不是模型预期的大小

Question

我试图通过像这样传递它们来在 Keras 中获得三种不同的损失函数

input_img = Input(shape=(728,))
encoded = Dense(450, activation='relu')(input_img)
encoded = Dense(250, activation='relu')(encoded)
encoded= Dense(20, activation='relu')(encoded)

decoded = Dense(250, activation='relu')(encoded)
decoded = Dense(450, activation='relu')(decoded)
decoded = Dense(728, activation='sigmoid')(decoded)
loss1 = Dense(728, activation='sigmoid', name='p1')(decoded)
loss2 = Dense(728, activation='sigmoid', name='p2')(decoded)
loss3 = Dense(728, activation='sigmoid', name='p3')(decoded)

我定义了三个不同的损失函数，编译成功

autoencoder = Model(inputs = [input_img], outputs=[loss1,loss2,loss3])
autoencoder.compile(optimizer='Adam', loss = [w_loss,b_loss, loss], metrics = [w_loss,b_loss], loss_weights=[1., 1., 1.])

然后我拟合模型

history_modified = autoencoder.fit(X_train, X_train, epochs=200, batch_size= 100, shuffle=True, validation_data=(X_test, X_test))

X_train 维度为 (100000, 728)，X_test 维度为 (50000,728)

我得到的错误是

Error when checking model target: the list of Numpy arrays that you are passing to your model is not the size the model expected. Expected to see 3 array(s), but instead got the following list of 1 arrays: [array([[0., 0., 0., ..., 0., 0., 0.],

我不知道究竟是什么导致了这个问题，但我认为这可能与层以及我如何拥有多个损失函数有关。

Answer 1

正如错误所说，目标的形状有问题。理想情况下，由于模型有三个输出(loss1,loss2,loss3)，输出中应该有三个数组来比较三个输出数组。您必须在目标中仅传递一个数组，因此会出现此错误。