text: from .simsiam_aug import SimSiamTransform
  from .eval_aug import Transform_single
  from .byol_aug import BYOL_transform
  from .simclr_aug import SimCLRTransform
  def get_aug(name='simsiam', image_size=224, train=True, train_classifier=None):
  
      if train==True:
          if name == 'simsiam' or name == 'simsiam_shallow':
              augmentation = SimSiamTransform(image_size)
          elif name == 'byol':
              augmentation = BYOL_transform(image_size)
          elif name == 'simclr':
              augmentation = SimCLRTransform(image_size)
          else:
              raise NotImplementedError
      elif train==False:
          if train_classifier is None:
              raise Exception
          augmentation = Transform_single(image_size, train=train_classifier)
      else:
          raise Exception
      
      return augmentation
  
  
  
  
  
  
  
  
  