您可以通过以下方式使用Keras功能API轻松实现此目标。

from tensorflow.python.keras import layers,models,applications

# Multiple inputs
in1 = layers.Input(shape=(128,128,3))
in2 = layers.Input(shape=(128,3))
in3 = layers.Input(shape=(128,3))

# CNN output
cnn = applications.xception.Xception(include_top=False)


out1 = cnn(in1)
out2 = cnn(in2)
out3 = cnn(in3)

# Flattening the output for the dense layer
fout1 = layers.Flatten()(out1)
fout2 = layers.Flatten()(out2)
fout3 = layers.Flatten()(out3)

# Getting the dense output
dense = layers.Dense(100,activation='softmax')

dout1 = dense(fout1)
dout2 = dense(fout2)
dout3 = dense(fout3)

# Concatenating the final output
out = layers.Concatenate(axis=-1)([dout1,dout2,dout3])

# Creating the model
model = models.Model(inputs=[in1,in2,in3],outputs=out)
model.summary()```