class_docstr: Generates multiple views for each image in the batch.
  
  Attributes:
      transforms:
          List of transformation functions. Each function is used to generate
          one view of the back.
class_docstr_tok: ["Generates","multiple","views","for","each","image","in","the","batch",".","Attributes",":","transforms",":","List","of","transformation","functions",".","Each","function","is","used","to","generate","one","view","of","the","back","."]
code: def __init__(self, transforms: List[torchvision.transforms.Compose]):
      _deprecation_warning_collate_functions()
      super().__init__()
      self.transforms = transforms
  
imports: import math
  from multiprocessing import Value
  from typing import List, Optional, Tuple, Union
  from warnings import warn
  import torch
  import torch.nn
  import torchvision
  import torchvision.transforms
  from PIL import Image
  from lightly.transforms import GaussianBlur, Jigsaw, RandomSolarization
  from lightly.transforms.random_crop_and_flip_with_grid import RandomResizedCropAndFlip
  from lightly.transforms.rotation import random_rotation_transform
  from lightly.transforms.utils import IMAGENET_NORMALIZE
label_desc: Use image node_id 1 to create a new MultiViewCollateFunction object from inherited base classes: nn with example: obj = MultiViewCollateFunction(transforms)