class_docstr: Returns positive pairs that have distance greater than a margin and negative
  pairs that have distance less than a margin
code: def __init__(self, pos_margin=0.2, neg_margin=0.8, **kwargs):
      super().__init__(**kwargs)
      self.pos_margin = pos_margin
      self.neg_margin = neg_margin
      self.add_to_recordable_attributes(
          list_of_names=["pos_margin", "neg_margin"], is_stat=False
      )
      self.add_to_recordable_attributes(
          list_of_names=["pos_pair_dist", "neg_pair_dist"], is_stat=True
      )
  
imports: import torch
  from ..utils import loss_and_miner_utils
  from .base_miner import BaseMiner
label_desc: Use image node_id 1 to create a new PairMarginMiner object from inherited base classes: BaseMiner with example: obj = PairMarginMiner(pos_margin, neg_margin)