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following is my architecture:

model = Sequential()
model.add(Conv1D(filters=8, kernel_size=2, activation="relu", input_shape=(9, 1)))

# CNN Pooling
model.add(MaxPooling1D(pool_size=2))

# Flatten layer
model.add(Flatten())

# Fully connected Layer
model.add(Dense(16, activation="relu"))

# Decision Layer
model.add(Dense(1, activation="sigmoid"))

this is what i got from the code: enter image description here

but i want architecture like this: enter image description here

i dont know how many layers should i add can any one help me with this thanks.

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1 Answer 1

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You will probably have to use a graphical tool and create the diagram from scratch. I am not aware of a tool that can directly generate it from code. Bur your CNN is rather simple so it should be easily doable.

For instance :

https://alexlenail.me/NN-SVG/LeNet.html

https://github.com/HarisIqbal88/PlotNeuralNet

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