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During the inference phase ,there were copy mismatches in the CFG and errors in the noise sampling sapce. #19

@Jerry-Auto

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@Jerry-Auto
  1. 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.
  2. 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.
  3. x_init = torch.randn((B, self.action_num, self.planner_params['action_len'], self.planner_params['state_dim']), device=self.device)
    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)

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