ee82275868049880a4ca9d4a9c05236c58bfe2d2,elfi/methods/methods.py,BayesianOptimization,prepare_new_batch,#BayesianOptimization#Any#,364

Before Change

    def prepare_new_batch(self, batch_index):
        context = self.model.computation_context
        pending_batches = context.output_supply[self.model.parameters[0]]

        // TODO: take values from the pool
        pending_params = []
        for output in pending_batches.values():

After Change

            new_param = self.init_acquisition.acquire(1, pending_params, t)

        // Save the next evaluation location to the pool
        self.pool.add_batch(batch_index, dict(zip(self.parameters, new_param[0])))

    def extract_result(self):
        param, min_value = stochastic_optimization(self.target_model.predict_mean,
                                                   self.target_model.bounds)

Instances