I have built a simple neural network,
model = Sequential()
model.add(Dense(20, input_dim=5, activation='sigmoid'))
model.add(Dense(1, activation='sigmoid'))
and I would get its weights by:
summary = model.summary()
W_Input_Hidden = model.layers[0].get_weights()[0]
W_Output_Hidden = model.layers[1].get_weights()[0]
print(summary)
print('INPUT-HIDDEN LAYER WEIGHTS:')
print(W_Input_Hidden)
print('HIDDEN-OUTPUT LAYER WEIGHTS:')
print(W_Output_Hidden)
but, in this way, I only get the weights matrices (5x20 , 1x20) without the biases. How can I get the biases values?
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