code: def initialize_beta(self, beta, num_classes):
      self.beta = torch.tensor([float(beta)])
      if num_classes:
          self.beta = torch.ones(num_classes) * self.beta
      if self.learn_beta:
          self.beta = torch.nn.Parameter(self.beta)
  
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 6 for calling the MarginLoss obj's underlying member method code with example usage: obj.initialize_beta(beta, num_classes) without return types