Estimating Predictive Uncertainty for unlabeled data
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So by default the dropout is only used in training time. Then in test time the dropout probability is set to 0. But there is a easy way to enable it so that it stays 'on' even during the test time. 
    import keras

inputs = keras.Input(shape=(10,))
x = keras.layers.Dense(3)(inputs)
outputs = keras.layers.Dropout(0.5)(x, training=True)

model = keras.Model(inputs, outputs)


By setting training=True it remains active in during test time. This can be called Monte Carlo dropout or more popularly dropout at inference time. I hope it helps.