Open raw scan, create subcloud(s), and fill in attributes.

Args: data_dict: points: optional, (N, 3 + C_in) gt_boxes: optional, (N, 7 + C) [x, y, z, dx, dy,

convert 2d range feature map to points feature

Args: input_dict (dict): all the values will be reduced average (bool): whether to do average or sum Reduce the values in the

Args: points: (B, N, 3 + C) angle: (B), angle along z-axis, angle increases x ==> y Returns:

Helper function to synchronize (barrier) among all processes when using distributed training

Cross entropy loss