code: def _get_params(self, sample):
      _, height, width = v2._utils.query_chw(sample)
      padding = [
          0,
          0,
          max(self.size - width, 0),
          max(self.size - height, 0),
      ]
      needs_padding = any(padding)
      return dict(padding=padding, needs_padding=needs_padding)
  
file_path: vision/references/segmentation/v2_extras.py
imports: import torch
  from torchvision import tv_tensors
  from torchvision.transforms import v2
label_desc: Use image node_id 2 for calling the PadIfSmaller obj's underlying member method code with example usage: obj._get_params(sample) and returns: dict