code: def __init__(self, config, pre_process=True, post_process=True):
      super(DINOPretrainModel, self).__init__()
      args = get_args()
      self.config = config
      self.out_dim = 65536
  
      self.dino_loss = DINOLoss(
          self.out_dim,
          args.dino_local_crops_number + 2,
          args.dino_warmup_teacher_temp,
          args.dino_teacher_temp,
          args.dino_warmup_teacher_temp_epochs,
          300,
      )
  
      self.pre_process = pre_process
      self.post_process = post_process
      self.momentum_teacher = 0.996
  
      (
          student_backbone,
          num_features,
      ) = get_student_backbone_and_num_features(
          config, pre_process, post_process
      )
  
      self.student = MultiCropWrapper(
          student_backbone,
          DINOHead(
              num_features,
              self.out_dim,
              norm_last_layer=args.dino_norm_last_layer,
          ),
      )
  
      self.momentum_schedule = cosine_scheduler(
          self.momentum_teacher,
          1,
          args.train_iters // args.iter_per_epoch,
          args.iter_per_epoch,
      )
  
      (
          teacher_backbone,
          num_features,
      ) = get_teacher_backbone_and_num_features(
          config, pre_process, post_process
      )
      self.teacher = MultiCropWrapper(
          teacher_backbone, DINOHead(num_features, self.out_dim)
      )
      self.teacher.load_state_dict(self.student.state_dict())
  
      for p in self.teacher.parameters():
          if (
              hasattr(p, "requires_grad")
              and p.requires_grad is not None
          ):
              p.requires_grad = False
  
imports: import math
  import apex
  import einops
  import torch
  import numpy
  import torch.nn.functional
  from torch.nn.init import trunc_normal_
  from megatron import get_args, print_rank_0
  from megatron.model.utils import get_linear_layer
  from megatron.model.vision.vit_backbone import VitBackbone
  from megatron.model.module import MegatronModule
  from megatron.model.vision.mit_backbone import mit_b5_avg
  from megatron.model.vision.esvit_swin_backbone import get_swin
label_desc: Use image node_id 1 to create a new DINOPretrainModel object from inherited base classes: MegatronModule with example: obj = DINOPretrainModel(config, pre_process, post_process)