class_docstr: DDP version of MultiScaleSampler
  
  Args:
      opts: command line argument
      n_data_samples: Number of samples in the dataset
      is_training: Training or validation mode. Default: False
class_docstr_tok: ["DDP","version","of","MultiScaleSampler","Args",":","opts",":","command","line","argument","n_data_samples",":","Number","of","samples","in","the","dataset","is_training",":","Training","or","validation","mode",".","Default",":","False"]
code: def extra_repr(self) -> str:
      extra_repr_str = super().extra_repr()
      extra_repr_str += (
          f"\n\t base_im_size=(h={self.crop_size_h}, w={self.crop_size_w})"
          f"\n\t base_batch_size={self.batch_size_gpu0}"
          f"\n\t scales={self.img_batch_tuples}"
      )
      return extra_repr_str
  
imports: import argparse
  import random
  from typing import Iterator, Tuple
  from common import DEFAULT_IMAGE_HEIGHT, DEFAULT_IMAGE_WIDTH
  from data.sampler import SAMPLER_REGISTRY
  from data.sampler.base_sampler import BaseSampler, BaseSamplerDDP
  from data.sampler.utils import image_batch_pairs
  from utils import logger
label_desc: Use image node_id 3 for calling the MultiScaleSamplerDDP obj's underlying member method code with example usage: obj.extra_repr() and returns: extra_repr_str