class_docstr: Copy paste from the original DINO paper. We use this to verify our
  implementation.
  
  The only change from the original code is that distributed training is no
  longer assumed.
  
  Source: https://github.com/facebookresearch/dino/blob/cb711401860da580817918b9167ed73e3eef3dcf/main_dino.py#L363
class_docstr_tok: ["Copy","paste","from","the","original","DINO","paper",".","We","use","this","to","verify","our","implementation",".","The","only","change","from","the","original","code","is","that","distributed","training","is","no","longer","assumed",".","Source",":","https",":","\/\/github.com\/facebookresearch\/dino\/blob\/cb711401860da580817918b9167ed73e3eef3dcf\/main_dino.py","#","L363"]
code: def __init__(
      self,
      out_dim,
      ncrops,
      warmup_teacher_temp,
      teacher_temp,
      warmup_teacher_temp_epochs,
      nepochs,
      student_temp=0.1,
      center_momentum=0.9,
  ):
      super().__init__()
      self.student_temp = student_temp
      self.center_momentum = center_momentum
      self.ncrops = ncrops
      self.register_buffer("center", torch.zeros(1, out_dim))
      # we apply a warm up for the teacher temperature because
      # a too high temperature makes the training instable at the beginning
      self.teacher_temp_schedule = np.concatenate(
          (
              np.linspace(
                  warmup_teacher_temp,
                  teacher_temp,
                  warmup_teacher_temp_epochs,
              ),
              np.ones(nepochs - warmup_teacher_temp_epochs)
              * teacher_temp,
          )
      )
  
file_path: lightly/tests/loss/test_DINOLoss.py
imports: import copy
  import itertools
  import unittest
  import numpy
  import torch
  import torch.nn.functional
  from torch import nn
  from lightly.loss import DINOLoss
  from lightly.models.utils import deactivate_requires_grad
label_desc: Use image node_id 1 to create a new OriginalDINOLoss object from inherited base classes: nn with example: obj = OriginalDINOLoss(out_dim, ncrops, warmup_teacher_temp, teacher_temp, warmup_teacher_temp_epochs, nepochs, student_temp, center_momentum)