Keras Graph断开连接，嵌入了多个输入

如何解决Keras Graph断开连接，嵌入了多个输入

这是我要构建的模型： 一个具有4个输入的模型，这些输入将它们嵌入并放入计分结果中

import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
H = keras.Input(shape=(1,),name="H") 
R = keras.Input(shape=(1,name="R") 
T = keras.Input(shape=(1,name="T") 
N = keras.Input(shape=(1,name="N") 

embedding = keras.layers.Embedding(10000,100)
embedding_r = keras.layers.Embedding(1000,100)

H = embedding(H)
R = embedding_r(R)
T = embedding(T)
N = embedding(N)

H = keras.layers.Flatten()(H)
R = keras.layers.Flatten()(R)
T = keras.layers.Flatten()(T)
N = keras.layers.Flatten()(N)

H_plus_R = keras.layers.Concatenate()([H,R])
T_plus_N = keras.layers.Concatenate()([N,T])

H_plus_R = keras.layers.Dense(100,activation='relu')(H_plus_R)
T_plus_N = keras.layers.Dense(100,activation='relu')(T_plus_N)

score = keras.layers.Concatenate()([T_plus_N,H_plus_R])
score = keras.layers.Dense(1,activation='relu')(score)

model = tf.keras.Model(
    inputs=[H,R,T,N],outputs=score,)

model.summary()

我明白了，这意味着输入和输出没有连接，但是它们是：

ValueError                                Traceback (most recent call last)
<ipython-input-8-90804bccaf4f> in <module>()
     32 model = tf.keras.Model(
     33     inputs=[H,---> 34     outputs=score,35 )
     36 

5 frames
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/functional.py in _map_graph_network(inputs,outputs)
    929                              'The following previous layers '
    930                              'were accessed without issue: ' +
--> 931                              str(layers_with_complete_input))
    932         for x in nest.flatten(node.outputs):
    933           computable_tensors.add(id(x))

ValueError: Graph disconnected: cannot obtain value for tensor Tensor("R_7:0",shape=(None,1),dtype=float32) at layer "embedding_13". The following previous layers were accessed without issue: []

我该如何解决？

解决方法

嵌入输入后，您将覆盖H，R，T和N，并尝试使用其他变量名