code: def maybe_get_metric_loss(
      self, embeddings, labels, indices_tuple, curr_loss_name
  ):
      if self.loss_weights.get(curr_loss_name, 0) > 0:
          return self.loss_funcs[curr_loss_name](
              embeddings, labels, indices_tuple
          )
      return 0
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/trainers/cascaded_embeddings.py
imports: from ..None import miners
  from ..utils import common_functions
  from .base_trainer import BaseTrainer
label_desc: Use image node_id 3 for calling the CascadedEmbeddings obj's underlying member method code with example usage: obj.maybe_get_metric_loss(embeddings, labels, indices_tuple, curr_loss_name) and returns: int, self