class_docstr: Stores assignments between predicted and truth boxes.
  
  Attributes:
      num_gts (int): the number of truth boxes considered when computing this
          assignment
  
      gt_inds (LongTensor): for each predicted box indicates the 1-based
          index of the assigned truth box. 0 means unassigned and -1 means
          ignore.
  
      max_overlaps (FloatTensor): the iou between the predicted box and its
          assigned truth box.
  
      labels (None | LongTensor): If specified, for each predicted box
          indicates the category label of the assigned truth box.
class_docstr_tok: ["Stores","assignments","between","predicted","and","truth","boxes",".","Attributes",":","num_gts","(","int",")",":","the","number","of","truth","boxes","considered","when","computing","this","assignment","gt_inds","(","LongTensor",")",":","for","each","predicted","box","indicates","the","1-based","index","of","the","assigned","truth","box",".","0","means","unassigned","and","-1","means","ignore",".","max_overlaps","(","FloatTensor",")",":","the","iou","between","the","predicted","box","and","its","assigned","truth","box",".","labels","(","None","|","LongTensor",")",":","If","specified",",","for","each","predicted","box","indicates","the","category","label","of","the","assigned","truth","box","."]
code: def __init__(self, num_gts, gt_inds, max_overlaps, labels=None):
      self.num_gts = num_gts
      self.gt_inds = gt_inds
      self.max_overlaps = max_overlaps
      self.labels = labels
      # Interface for possible user-defined properties
      self._extra_properties = {}
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from ppdet.core.workspace import register
label_desc: Use image node_id 1 to create a new AssignResult object  with example: obj = AssignResult(num_gts, gt_inds, max_overlaps, labels)