how to apply MC dropout to an LSTM network keras I have a simple LSTM network developped using keras:

model = Sequential()
model.add(LSTM(rnn_size,input_shape=(2,w),dropout = 0.25 , recurrent_dropout=0.25))
model.add(Dense(2))


I would like to apply the MC dropout method. How can I enable dropout in the test phase in order to compute the uncertainty?

Thanks.
Well, in order to enable dropout during test phase you can do something like this:

keras.layers.Dropout(0.5)(x, training=True)


Then you'll probably want to run it multiple times. If you don't care about the inference time just run forward pass multiple times and at the end calculate mean and variance of your output.