The dropout layer is only supposed to be used during the training of the model, not during testing.
If I have a dropout layer in my Keras sequential model, do I need to do something to remove or silence it before I do model.predict()?
Keras Dropout Layer Model Predict
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1 Answers
No, you don't need to silence it or remove it. Keras automatically takes care of it.
It is clearly mentioned in the documentation. A Keras model has two modes:
- training
- testing
Regularization mechanisms, such as Dropout and L1/L2 weight regularization, are turned off at testing time.
Note: Also, Batch Normalization is a much-preferred technique for regularization, in my opinion, as compared to Dropout. Consider using it.
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