class_docstr: From DETR source: https://github.com/facebookresearch/detr
  (detr/models/detr.py)
class_docstr_tok: ["From","DETR","source",":","https",":","\/\/github.com\/facebookresearch\/detr","(","detr\/models\/detr.py",")"]
docstr: Create the criterion.
  Parameters:
      num_classes: number of object categories, omitting the special no-object category
      matcher: module able to compute a matching between targets and proposals
      weight_dict: dict containing as key the names of the losses and as values their relative weight.
      eos_coef: relative classification weight applied to the no-object category
      losses: list of all the losses to be applied. See get_loss for list of available losses.
docstr_tok: ["Create","the","criterion",".","Parameters",":","num_classes",":","number","of","object","categories",",","omitting","the","special","no-object","category","matcher",":","module","able","to","compute","a","matching","between","targets","and","proposals","weight_dict",":","dict","containing","as","key","the","names","of","the","losses","and","as","values","their","relative","weight",".","eos_coef",":","relative","classification","weight","applied","to","the","no-object","category","losses",":","list","of","all","the","losses","to","be","applied",".","See","get_loss","for","list","of","available","losses","."]
code: def __init__(
      self, num_classes, matcher, weight_dict, eos_coef, losses
  ):
      """Create the criterion.
      Parameters:
          num_classes: number of object categories, omitting the special no-object category
          matcher: module able to compute a matching between targets and proposals
          weight_dict: dict containing as key the names of the losses and as values their relative weight.
          eos_coef: relative classification weight applied to the no-object category
          losses: list of all the losses to be applied. See get_loss for list of available losses.
      """
  
      super().__init__()
      self.num_classes = num_classes
      self.matcher = matcher
      self.weight_dict = weight_dict
      self.eos_coef = eos_coef
      self.losses = losses
      empty_weight = torch.ones(self.num_classes + 1)
      empty_weight[-1] = self.eos_coef
      self.register_buffer("empty_weight", empty_weight)
  
imports: from typing import List, Optional, Tuple, Union
  import torch
label_desc: Use image node_id 1 to create a new SetCriterion object from inherited base classes: torch.nn with example: obj = SetCriterion(num_classes, matcher, weight_dict, eos_coef, losses)