Method agents_to_batch

star/models/CNNNet.py:379–385

(feats)

    @staticmethod
    def agents_to_batch(feats):
        agent_num = feats.shape[1]
        feat_list = []
        for i in range(agent_num):
            feat_list.append(feats[:, i, :, :, :])
        feat_mat = torch.cat(tuple(feat_list), 0)
        return feat_mat

    def ego_late_fusion(self, pred, gt, trans_matrices, num_agent_tensor, batch_size):
        """ aggregation, ego use ground truth input, used specifically in inference time"""