How to concatenate two layers in keras?

Michael Zippo

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I have an example of a neural network with two layers. The first layer takes two arguments and has one output. The second should take one argument as result of the first layer and one additional argument. It should looks like this:

x1  x2  x3
   /   /
  y1   /
     /
    y2

So, I"d created a model with two layers and tried to merge them but it returns an error: The first layer in a Sequential model must get an "input_shape" or "batch_input_shape" argument. on the line result.add(merged).

Model:

first = Sequential()
first.add(Dense(1, input_shape=(2,), activation="sigmoid"))

second = Sequential()
second.add(Dense(1, input_shape=(1,), activation="sigmoid"))

result = Sequential()
merged = Concatenate([first, second])
ada_grad = Adagrad(lr=0.1, epsilon=1e-08, decay=0.0)
result.add(merged)
result.compile(optimizer=ada_grad, loss=_loss_tensor, metrics=["accuracy"])

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Carlo Porretti

New York | 2023-03-24

Simply put and clear. Thank you for sharing. How to concatenate two layers in keras? and other issues with Network PHP module was always my weak point 😁. Will get back tomorrow with feedback

Cornwall Sikorski

Warsaw | 2023-03-24

I was preparing for my coding interview, thanks for clarifying this - How to concatenate two layers in keras? in Python is not the simplest one. Will use it in my bachelor thesis

Boris Danburry

California | 2023-03-24

io Python module is always a bit confusing 😭 How to concatenate two layers in keras? is not the only problem I encountered. Checked yesterday, it works!