code: def get_accuracy(self, cls_score, labels):
      fine_cls_score = cls_score[:, : self.num_classes]
  
      pos_inds = labels < self.num_classes
      acc_classes = accuracy(fine_cls_score[pos_inds], labels[pos_inds])
      acc = dict()
      acc["acc_classes"] = acc_classes
      return acc
  
imports: import warnings
  import torch
  import torch.nn
  import torch.nn.functional
  from mmdet.registry import MODELS
  from .accuracy import accuracy
  from .utils import weight_reduce_loss
label_desc: Use image node_id 4 for calling the CrossEntropyCustomLoss obj's underlying member method code with example usage: obj.get_accuracy(cls_score, labels) and returns: acc