b6240c06fb49020e2d51703a1fcfddba7e27297d,bindsnet/network/network.py,Network,run,#Network#Any#Any#,229

Before Change

                    // Overwrite the None with a specific time.
                    t_slice[input_time_dim[l]] = t
                    // Pull out that individual time slice and ensure the memory is contiguous.
                    self.layers[l].forward(x=inpts[l][t_slice].contiguous())
                else:
                    self.layers[l].forward(x=inpts[l])

After Change

            reward = self.reward_fn.compute(**kwargs)

        // Dynamic setting of batch size.
        if inpts != {}:
            for key in inpts:
                if inpts[key].size(0) != self.batch_size:
                    self.batch_size = inpts[key].size(0)

                    for l in self.layers:
                        self.layers[l].set_batch_size(self.batch_size)

                    for m in self.monitors:
                        self.monitors[m].reset_()

                break

        // Effective number of timesteps.
        timesteps = int(time / self.dt)

        // Get input to all layers.
        inpts.update(self.get_inputs())

Instances