图表已断开连接：无法获取张量张量输入Keras Python的值

Question

我有以下代码：

# Declare the layers

inp1 = Input(shape=input_shape, name="input1")

inp2 = Input(shape=input_shape, name="input2")

# 128 -> 64

conv1_inp1 = Conv2D(start_neurons * 1, 3, activation="relu", padding="same")(inp1)

conv1_inp2 = Conv2D(start_neurons * 1, 3, activation="relu", padding="same")(inp2)

conv1 = Concatenate()([conv1_inp1, conv1_inp2])

conv1 = Conv2D(start_neurons * 1, 3, activation="relu", padding="same")(conv1)

conv1 = MaxPooling2D((2, 2))(conv1)

conv1 = Dropout(0.25)(conv1)

# 64 -> 32

conv2 = Conv2D(start_neurons * 2, (3, 3), activation="relu", padding="same")(conv1)

conv2 = Conv2D(start_neurons * 2, (3, 3), activation="relu", padding="same")(conv2)

pool2 = MaxPooling2D((2, 2))(conv2)

pool2 = Dropout(0.5)(pool2)

# 32 -> 16

conv3 = Conv2D(start_neurons * 4, (3, 3), activation="relu", padding="same")(pool2)

conv3 = Conv2D(start_neurons * 4, (3, 3), activation="relu", padding="same")(conv3)

pool3 = MaxPooling2D((2, 2))(conv3)

pool3 = Dropout(0.5)(pool3)

# 16 -> 8

conv4 = Conv2D(start_neurons * 8, (3, 3), activation="relu", padding="same")(pool3)

conv4 = Conv2D(start_neurons * 8, (3, 3), activation="relu", padding="same")(conv4)

pool4 = MaxPooling2D((2, 2))(conv4)

pool4 = Dropout(0.5)(pool4)

# Middle

convm = Conv2D(start_neurons * 16, (3, 3), activation="relu", padding="same")(pool4)

convm = Conv2D(start_neurons * 16, (3, 3), activation="relu", padding="same")(convm)

# 8 -> 16

deconv4 = Conv2DTranspose(start_neurons * 8, (3, 3), strides=(2, 2), padding="same")(convm)

uconv4 = Concatenate()([deconv4, conv4])

uconv4 = Dropout(0.5)(uconv4)

uconv4 = Conv2D(start_neurons * 8, (3, 3), activation="relu", padding="same")(uconv4)

uconv4 = Conv2D(start_neurons * 8, (3, 3), activation="relu", padding="same")(uconv4)

并产生此错误：

Graph disconnected: cannot obtain value for tensor Tensor("input_28:0", shape=(?, 128, 128, 1), dtype=float32) at layer "input_28". The following previous layers were accessed without issue: []

输入具有相同的形状，在某些论坛中，他们说问题出在以下事实：输入来自2个不同的来源，因此破坏了您之前的链接。

我真的不知道该如何解决。

谁能帮我？

Answer 1

这是图形断开连接的地方（uconv2调用时未定义）：# 32 -> 64deconv2 = Conv2DTranspose(start_neurons * 2, (3, 3), strides=(2, 2), padding="same")(uconv3)uconv2 = Conv2D(start_neurons * 2, (3, 3), activation="relu", padding="same")(uconv2)

Answer 2

解决此图错误的原因是我对此进行了更改：x_in = Input(shape=(10,), name="InputLayer")_ = order2_embs_model(x_in)...model = Model(inputs=x_in, outputs=Y, name='DeepFFM') 对此：model = Model(inputs=order2_embs_model.inputs, outputs=Y, name='DeepFFM')