Is there any way to see the architecture of a neural network with custom layers?
I'm using a model that contains a custom position encoding, then a keras_nlp.layers.TransformerEncoder layer, and finally the classic GlobalAveragePooling1D and Dense layers.
I have tried with Keras Visualizer but I get the following error:
keras visualizer: layer not supported for visualizing
I guess it's because the custom layer.
The model.summary() gives me the correct data of my model, but I would like to see the architecture of the neural network similar to the following photo:
