code: def __init__(self, pos_eps=0.01, neg_eps=0.01, **kwargs):
      super().__init__(mat_based_loss=False, **kwargs)
      self.pos_eps = pos_eps
      self.neg_eps = neg_eps
      self.add_to_recordable_attributes(
          list_of_names=["pos_eps", "neg_eps"], is_stat=False
      )
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/losses/intra_pair_variance_loss.py
imports: import torch
  from ..distances import CosineSimilarity
  from ..losses import GenericPairLoss
  from ..utils import loss_and_miner_utils
label_desc: Use image node_id 1 to create a new IntraPairVarianceLoss object from inherited base classes: GenericPairLoss with example: obj = IntraPairVarianceLoss(pos_eps, neg_eps)