How to make separate Keras model with dependent weights?
Question:
I have to create a network with keras like in the picture below, where NN – individual neural networks.
The problem is, that they all must have same weights
I can’t use shared layers (at least to my understanding), because then one network will get all the inputs in it and I need each to get specially one
Is there any way of doing this?
Answers:
Use the functional api. You can reuse a layer for different inputs. For example:
inp1 = Input(...)
inp2 = Input(...)
layer1 = Dense(...)
a1 = layer1(inp1)
a2 = layer1(inp2)
layer1 will be applied on inp1 and on inp2. It is just one layer instance, the same weights will be used for inp1 and inp2.
I have to create a network with keras like in the picture below, where NN – individual neural networks.
The problem is, that they all must have same weights
I can’t use shared layers (at least to my understanding), because then one network will get all the inputs in it and I need each to get specially one
Is there any way of doing this?
Use the functional api. You can reuse a layer for different inputs. For example:
inp1 = Input(...)
inp2 = Input(...)
layer1 = Dense(...)
a1 = layer1(inp1)
a2 = layer1(inp2)
layer1 will be applied on inp1 and on inp2. It is just one layer instance, the same weights will be used for inp1 and inp2.