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The dataset uses repeat_interleave,but flag and x are directly repeated,resulting in inconsisitent coping.for example,[1,2,3,4] to[1,1,2,2,3,3,4,4] and[1,2,3,4,1,2,3,4],mismatched.
the initial noise sampling space must be consistent with that used during training;that is ,sampling must be performed before segmentation,and then segmentation must occur, rather than sampling directly,in the segmented sapce.
to x_0 = torch.randn((B,1,self.planner_params['future_len'], self.planner_params['state_dim']), device=self.device)
x_init = traj_chunking(x_0, self.planner_params['action_len'], self.planner_params['action_overlap'])
x_init = torch.cat(x_init, dim=1)