docstr: Gets called at the end of a stage.
docstr_tok: ["Gets","called","at","the","end","of","a","stage","."]
code: def on_stage_end(self, stage, stage_loss, epoch):
      """Gets called at the end of a stage."""
      if stage == sb.Stage.TRAIN:
          self.train_loss = stage_loss
      else:
          per = self.per_metrics.summarize("error_rate")
  
      if stage == sb.Stage.VALID:
          old_lr, new_lr = self.hparams.lr_annealing(per)
          sb.nnet.schedulers.update_learning_rate(
              self.optimizer, new_lr
          )
          self.hparams.train_logger.log_stats(
              stats_meta={"epoch": epoch, "lr": old_lr},
              train_stats={"loss": self.train_loss},
              valid_stats={"loss": stage_loss, "PER": per},
          )
          self.checkpointer.save_and_keep_only(
              meta={"PER": per},
              min_keys=["PER"],
          )
  
      elif stage == sb.Stage.TEST:
          self.hparams.train_logger.log_stats(
              stats_meta={
                  "Epoch loaded": self.hparams.epoch_counter.current
              },
              test_stats={"loss": stage_loss, "PER": per},
          )
          if if_main_process():
              with open(self.hparams.test_wer_file, "w") as w:
                  w.write("CTC loss stats:\n")
                  self.ctc_metrics.write_stats(w)
                  w.write("\nPER stats:\n")
                  self.per_metrics.write_stats(w)
                  print(
                      "CTC and PER stats written to ",
                      self.hparams.test_wer_file,
                  )
  
file_path: speechbrain/recipes/TIMIT/ASR/CTC/train.py
imports: import os
  import sys
  import logging
  import speechbrain
  from hyperpyyaml import load_hyperpyyaml
  from speechbrain.utils.distributed import run_on_main, if_main_process
label_desc: Use image node_id 4 for calling the ASR_Brain obj's underlying member method code with example usage: obj.on_stage_end(stage, stage_loss, epoch) without return types