Keras Custom model with two Input

Keras: Multiple Inputs and Mixed Data

Python

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41

# define two sets of inputs inputA = Input(shape=(32,)) inputB = Input(shape=(128,))   # the first branch operates on the first input x = Dense(8, activation="relu")(inputA) x = Dense(4, activation="relu")(x) x = Model(inputs=inputA, outputs=x)   # the second branch opreates on the second input y = Dense(64, activation="relu")(inputB) y = Dense(32, activation="relu")(y) y = Dense(4, activation="relu")(y) y = Model(inputs=inputB, outputs=y)   # combine the output of the two branches combined = concatenate([x.output, y.output])   # apply a FC layer and then a regression prediction on the # combined outputs z = Dense(2, activation="relu")(combined) z = Dense(1, activation="linear")(z)   # our model will accept the inputs of the two branches and # then output a single value model = Model(inputs=[x.input, y.input], outputs=z)

Keras Functional API : https://keras.io/getting-started/functional-api-guide/