code: def calculate_loss(self, curr_batch):
      (anchors, posnegs), labels = curr_batch
      embeddings = (
          self.compute_embeddings(anchors),
          self.compute_embeddings(posnegs),
      )
  
      indices_tuple = self.maybe_mine_embeddings(embeddings, labels)
      self.losses["metric_loss"] = self.maybe_get_metric_loss(
          embeddings, labels, indices_tuple
      )
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/trainers/twostream_metric_loss.py
imports: import torch
  from ..utils import common_functions
  from ..utils import loss_and_miner_utils
  from .base_trainer import BaseTrainer
label_desc: Use image node_id 1 for calling the TwoStreamMetricLoss obj's underlying member method code with example usage: obj.calculate_loss(curr_batch) without return types