code: def maybe_do_batch_mining(self, data, labels):
      if "subset_batch_miner" in self.mining_funcs:
          with torch.no_grad():
              self.set_to_eval()
              embeddings = self.compute_embeddings(data)
              idx = self.mining_funcs["subset_batch_miner"](
                  embeddings, labels
              )
              self.set_to_train()
              data, labels = data[idx], labels[idx]
      return data, labels
  
imports: import torch
  import tqdm
  from ..utils import common_functions
  from ..utils import loss_tracker
  from ..utils.key_checker import KeyChecker, KeyCheckerDict
label_desc: Use image node_id 15 for calling the BaseTrainer obj's underlying member method code with example usage: obj.maybe_do_batch_mining(data, labels) and returns: data,  labels