08f049c9fc5fc0f3da5a830de72a583007cdec66,elfi/methods/methods.py,BayesianOptimization,__init__,#BayesianOptimization#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,319

Before Change

        target_model = \
            target_model or GPyRegression(len(self.model.parameters), bounds=bounds)

        if not isinstance(initial_evidence, int):
            // Add precomputed data
            raise NotImplementedError("Initial evidence must be an integer")

        if initial_evidence > 0:
            self.init_acquisition = UniformAcquisition(target_model)
        else:
            self.init_acquisition = None

After Change

        if not isinstance(initial_evidence, int):
            // Add precomputed batch data
            params = self.to_array(initial_evidence, self.parameters)
            target_model.update(params, initial_evidence[self.target])
            initial_evidence = len(params)

        // TODO: check if this can be removed
        if initial_evidence % self.batch_size != 0:
            raise ValueError("Initial evidence must be divisible by the batch size")

        self.acquisition_method = acquisition_method or LCBSC(target_model)

        self.target_model = target_model
        self.n_initial_evidence = initial_evidence

Instances