ff6c598abad81aec828e6a5967d2c6cfc5779a19,hyperopt/theano_gp.py,GP_BanditAlgo,K_fn,#GP_BanditAlgo#Any#Any#,503

Before Change

        if self.multiplicative_kernels:
            return tensor.mul(*gram_matrices)
        else:
            return tensor.add(*gram_matrices)

    def prepare_GP_training_data(self, X_IVLs, Ys, Ys_var):
        if self.constant_liar_global_mean:
            y_mean = numpy.mean(Ys["ok"][:self.n_startup_jobs])

After Change

            nx1 = self.s_n_train
        else:
            nx1 = self.s_n_test
        base = tensor.alloc(fill_val, self.s_n_train, nx1)
        for kern, iv0, iv1 in zip(self.kernels, x0, x1):
            gram = kern.K(
                    iv0.vals.dimshuffle(0, "x"),
                    iv1.vals.dimshuffle(0, "x"))
            base = modif(base, gram, iv0.idxs, iv1.idxs)

        return base

    def prepare_GP_training_data(self, ivls):

        y_mean = numpy.mean(ivls["losses"]["ok"].vals)

Instances