71d61f102189f8b7337567ca34ad590f2ddf4808,snntoolbox/simulation/target_simulators/INI_ttfs_target_sim.py,SNN,simulate,#SNN#,34

Before Change

                guesses_b = np.argmin(first_spiketimes_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 all(np.count_nonzero(output_b_l_t, (1, 2)) >= self.top_k):
                print("Finished early.")

After Change

                    echo("{:.2%}_".format(current_acc))
            else:
                sys.stdout.write("\r{:>7.2%}".format(current_acc))
                sys.stdout.flush()

            if self.config.getboolean("conversion", "softmax_to_relu") and \
                    all(np.count_nonzero(output_b_l_t, (1, 2)) >= self.top_k):
                print("Finished early.")

Instances