code: def embedding_regularization_loss(self, embeddings):
      if self.embedding_regularizer is None:
          loss = 0
      else:
          loss = (
              self.embedding_regularizer(embeddings)
              * self.embedding_reg_weight
          )
      return {
          "losses": loss,
          "indices": None,
          "reduction_type": "already_reduced",
      }
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/losses/mixins.py
imports: import torch
  from ..utils import common_functions
label_desc: Use image node_id 2 for calling the EmbeddingRegularizerMixin obj's underlying member method code with example usage: obj.embedding_regularization_loss(embeddings) and returns: dict