4461f2d4c1f140667b8fe9305efffb4351e54460,snntoolbox/simulation/target_simulators/INI_target_sim.py,SNN,simulate,#SNN#,112

Before Change

                            spike = 1
                        output_b_l_t[b, l, t] = spike

        return np.cumsum(np.asarray(output_b_l_t, bool), 2)

    def reset(self, sample_idx):

After Change

                    and sim_step % 1 == 0:
                if self.config.getboolean("conversion", "use_isi_code"):
                    first_spiketimes_b_l = np.argmax(output_b_l_t, 2)
                    undecided_b = np.sum(first_spiketimes_b_l, 1) == 0
                    first_spiketimes_b_l[np.nonzero(np.sum(
                        output_b_l_t, 2) == 0)] = self._num_timesteps
                    guesses_b = np.argmin(first_spiketimes_b_l, 1)
                else:
                    spike_sums_b_l = np.sum(output_b_l_t, 2)
                    undecided_b = np.sum(spike_sums_b_l, 1) == 0
                    guesses_b = np.argmax(spike_sums_b_l, 1)
                none_class_b = -1 * np.ones(self.batch_size)
                clean_guesses_b = np.where(undecided_b, none_class_b, guesses_b)
                echo("{:.2%}_".format(np.mean(kwargs[str("truth_b")] ==
                                              clean_guesses_b)))

            if self.config.getboolean("conversion", "use_isi_code") and \

Instances