code: def maybe_get_classifier_loss(self, logits, labels, curr_loss_name):
      if self.loss_weights.get(curr_loss_name, 0) > 0:
          return self.loss_funcs[curr_loss_name](
              logits, c_f.to_device(labels, logits)
          )
      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 6 for calling the CascadedEmbeddings obj's underlying member method code with example usage: obj.maybe_get_classifier_loss(logits, labels, curr_loss_name) and returns: int, self