class_docstr: This loss allows to distill a SwAV model
class_docstr_tok: ["This","loss","allows","to","distill","a","SwAV","model"]
code: def _init_teacher_scores_queue(self):
      self.local_queue_length = 0
      queue = (
          torch.rand(
              self.local_queue_max_length, self.num_prototypes[0]
          )
          * 2
          - 1
      )
      self.register_buffer("local_queue", queue)
  
imports: import logging
  import os
  import pprint
  from typing import List, Optional, Union
  import numpy
  import torch
  import torch.nn.functional
  from classy_vision.generic.distributed_util import all_reduce_max, get_cuda_device_index, get_rank, get_world_size
  from classy_vision.losses import ClassyLoss, register_loss
  from fvcore.common.file_io import PathManager
  from torch import nn
  from vissl.config import AttrDict
  from vissl.losses.distibuted_sinkhornknopp import distributed_sinkhornknopp
label_desc: Use image node_id 2 for calling the SwAVDistillationCriterion obj's underlying member method code with example usage: obj._init_teacher_scores_queue() without return types