code: def __call__(self, data):
      if self.size_divisor > 1:
          h, w = data["img"].shape[:2]
          tar_size = self.get_target_size((w, h))
          if tar_size != (w, h):
              op = paddleseg.transforms.Padding(tar_size)
              data = op(data)
      return data
  
imports: from collections import Counter
  import numpy
  import paddleseg
  import paddlepanseg.transforms.functional
  from paddlepanseg.cvlibs import manager
  from paddlepanseg.cvlibs.info_dicts import InfoDict
  from paddlepanseg.utils import encode_pan_id
  from .test_transforms import trim_for_test
label_desc: Use image node_id 2 for calling the PadToDivisible obj's underlying member method code with example usage: obj.__call__(data) and returns: data