class_docstr: modified from https://github.com/MalongTech/research-ms-loss/
  Args:
      alpha: The exponential weight for positive pairs
      beta: The exponential weight for negative pairs
      base: The shift in the exponent applied to both positive and negative pairs
code: def get_default_distance(self):
      return CosineSimilarity()
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/losses/multi_similarity_loss.py
imports: from ..distances import CosineSimilarity
  from ..utils import common_functions
  from ..utils import loss_and_miner_utils
  from .generic_pair_loss import GenericPairLoss
label_desc: Use image node_id 3 for calling the MultiSimilarityLoss obj's underlying member method code with example usage: obj.get_default_distance() and returns: CosineSimilarity