Comments (3)
After training a model, you can get the weights for each layer by calling the .get_weights() method. The "weights" are the numerical values of the parameters of the layer, as a list of arrays.
all_weights = []
for layer in model.layers:
w = layer.get_weights()
all_weights.append(w)
You can then visualize these weights, or use them to initialize new layers (pass a "weights" argument to each layer). Check out the code itself for more detail, until there is a documentation available.
from keras.
Thanks for your help.
from keras.
how can I save the features of the last fully connected layer (before the softmak layer) of the trained model?
from keras.
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from keras.