python - Reset keras-tuner between searches

Question

In order to test my code, I would like to launch multiple hyperparameter searches in succession. For each search, I create a new tuner (HyperBand) that I compile and retrieve its best hyperparameters found.

class HyperparametersSearch:
def __init__(self, activation_functions, ...):
    self.choices_activation_functions = activation_functions
    ...

    def search():
        tuner = kt.Hyperband(
            build_model,
            objective="val_loss",
            max_epochs=10,
            hyperband_iterations=5,
        )
        tuner.search(
            x=self.X_train,
            y=self.y_train,
            validation_data=(self.X_val, self.y_val),
            callbacks=[EarlyStopping(patience=5)],
        )
        return tuner.get_best_hyperparameters(1)[0]


    def build_model(self, hp) -> Model:
        input_layer = Input(
            shape=(
                self.steps_in,
                self.nb_features,
            )
        )
        current_layer = input_layer
        activation_functions = hp.Choice("activation_function", self.choices_activation_functions)
        current_layer = self.__generate_block_structure(
            hp, current_layer, activation_functions, None,
        )
        flat_layer = Flatten()(current_layer)
        output_layer: Dense = Dense(units=self.nb_steps_out)(
            flat_layer
        )

        model = Model(input_layer, output_layer)
        optimizer = Adam(
            learning_rate=hp.Float("learning_rate", 1e-5, 3e-5, sampling="log")
        )

        model.compile(
            optimizer=optimizer,
            loss="mae",
            metrics=None,
        )
        return model

search_1 = HyperparametersSearch(activation_functions=["relu", "selu"])
hp_search_1 = search_1.search()
keras.backend.clear_session()

search_2 = HyperparametersSearch(activation_functions=["logcosh", "selu"])  # not performed
hp_search_2 = search_2.search()  # return same as hp_search_1, with relu activation_function
keras.backend.clear_session()

I realise that between each search, the process is not reset:

• During the first search, I find some of the best hyperparameters.
• I then launch my second search, the search process doesn't even start and returns the same best hyperparameters found for the first one.

I used keras.backend.clear_session() between search processes in order to reset keras-tuner, but it does not work..

Would anyone have an idea to allow several hyperparameter searches in a succession?

Thanks

Answer 1

等待大神答复