keras.layers.add(inputs)

>>> a = input1 = keras.layers.Input(shape = (16,)) 
>>> x1 = keras.layers.Dense(8, activation = 'relu')(a) 
>>> a = keras.layers.Input(shape = (16,)) 
>>> x1 = keras.layers.Dense(8, activation='relu')(a) 
>>> b = keras.layers.Input(shape = (32,)) 
>>> x2 = keras.layers.Dense(8, activation = 'relu')(b) 
>>> summ = = keras.layers.add([x1, x2]) 
>>> summ = keras.layers.add([x1, x2]) 
>>> model = keras.models.Model(inputs = [a,b],outputs = summ)

keras.layers.subtract(inputs)

subtract_result = keras.layers.subtract([x1, x2]) 
result = keras.layers.Dense(4)(subtract_result) 
model = keras.models.Model(inputs = [a,b], outputs = result)

keras.layers.multiply(inputs)

mul_result = keras.layers.multiply([x1, x2]) 
result = keras.layers.Dense(4)(mul_result) 
model = keras.models.Model(inputs = [a,b], outputs = result)

keras.layers.maximum(inputs)

keras.layers.minimum(inputs)

keras.layers.concatenate(inputs, axis = -1)

keras.layers.dot(inputs, axes, normalize = False)