class_docstr: Structure that holds a list of images (of possibly
  varying sizes) as a single tensor.
  This works by padding the images to the same size,
  and storing in a field the original sizes of each image
docstr: Move the tensor and mask to the specified device.
code: def to(self, device, non_blocking: bool):
      """
      Move the tensor and mask to the specified device.
      """
      # type: (Device) -> MultiDimensionalTensor # noqa
      cast_tensor = self.tensor.to(device, non_blocking=non_blocking)
      cast_mask = self.mask.to(device, non_blocking=non_blocking)
      return MultiDimensionalTensor(
          cast_tensor, cast_mask, self.image_sizes
      )
  
file_path: vissl/vissl/data/collators/collator_helper.py
imports: from typing import List, Tuple
  import torch
label_desc: Use image node_id 5 for calling the MultiDimensionalTensor obj's underlying member method code with example usage: obj.to(device, non_blocking) and returns: MultiDimensionalTensor