envs/thor_beacons.py [288:304]:
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                    beacon_mask[t, ch, 1][pos_mask] = 1

        #-----------------------------------------------------------------------------------------------------------------#

        frames = np.stack([hist['frame'] for hist in beacon_history], 0)
        frames = torch.from_numpy(frames).float().permute(0, 3, 1, 2)/255
        poses = torch.Tensor([hist['pose'] for hist in beacon_history])
        frames, beacon_mask = resize_results(frames, beacon_mask, out_sz)
        
        return frames, beacon_mask, poses, info


    def reset(self):
        obs = super().reset()
        self.beacons = []
        self.history = []
        return obs
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envs/thor_beacons.py [397:412]:
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                    beacon_mask[t, ch, 1][pos_mask] = 1


        frames = np.stack([hist['frame'] for hist in beacon_history], 0)
        frames = torch.from_numpy(frames).float().permute(0, 3, 1, 2)/255
        poses = torch.Tensor([hist['pose'] for hist in beacon_history])
        frames, beacon_mask = resize_results(frames, beacon_mask, out_sz)
            
        return frames, beacon_mask, poses, info


    def reset(self):
        obs = super().reset()
        self.beacons = []
        self.history = []
        return obs
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