class_docstr: Transforms an image into multiple views.
  
  Args:
      transforms:
          A sequence of transforms. Every transform creates a new view.
class_docstr_tok: ["Transforms","an","image","into","multiple","views",".","Args",":","transforms",":","A","sequence","of","transforms",".","Every","transform","creates","a","new","view","."]
docstr: Transforms an image into multiple views.
  
  Every transform in self.transforms creates a new view.
  
  Args:
      image:
          Image to be transformed into multiple views.
  
  Returns:
      List of views.
docstr_tok: ["Transforms","an","image","into","multiple","views",".","Every","transform","in","self.transforms","creates","a","new","view",".","Args",":","image",":","Image","to","be","transformed","into","multiple","views",".","Returns",":","List","of","views","."]
code: def __call__(
      self, image: Union[Tensor, Image]
  ) -> Union[List[Tensor], List[Image]]:
      """Transforms an image into multiple views.
  
      Every transform in self.transforms creates a new view.
  
      Args:
          image:
              Image to be transformed into multiple views.
  
      Returns:
          List of views.
  
      """
      return [transform(image) for transform in self.transforms]
  
imports: from typing import List, Sequence, Union
  from PIL.Image import Image
  from torch import Tensor
  from torchvision import transforms
label_desc: Use image node_id 2 for calling the MultiViewTransform obj's underlying member method code with example usage: obj.__call__(image) and returns: unknown