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

Before Change

            for l in range(self.num_classes):
                spike = 0
                for t in range(self._num_timesteps):
                    if output_b_l_t[b, l, t]:
                        spike = True
                    output_b_l_t[b, l, t] = spike

        self.avg_rate /= self.batch_size * np.sum(self.num_neurons) * \
            self._num_timesteps

After Change

                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.")
                break

Instances