code: def __init__(
      self,
      margin=0.2,
      nu=0,
      beta=1.2,
      triplets_per_anchor="all",
      learn_beta=False,
      num_classes=None,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.margin = margin
      self.nu = nu
      self.learn_beta = learn_beta
      self.initialize_beta(beta, num_classes)
      self.triplets_per_anchor = triplets_per_anchor
      self.add_to_recordable_attributes(
          list_of_names=["margin", "nu", "beta"], is_stat=False
      )
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/losses/margin_loss.py
imports: import torch
  from ..reducers import DivisorReducer
  from ..utils import common_functions
  from ..utils import loss_and_miner_utils
  from .base_metric_loss_function import BaseMetricLossFunction
label_desc: Use image node_id 1 to create a new MarginLoss object from inherited base classes: BaseMetricLossFunction with example: obj = MarginLoss(margin, nu, beta, triplets_per_anchor, learn_beta, num_classes)