docstr: At the end of the optimizer step, apply noam annealing.
docstr_tok: ["At","the","end","of","the","optimizer","step",",","apply","noam","annealing","."]
code: def on_fit_batch_end(self, batch, outputs, loss, should_step):
      """At the end of the optimizer step, apply noam annealing."""
      if should_step:
          if not self.hparams.wav2vec2_frozen:
              self.hparams.lr_annealing_wav2vec(
                  self.wav2vec_optimizer, self.optimizer_step
              )
          if not self.hparams.mbart_frozen:
              self.hparams.lr_annealing_mbart(
                  self.mbart_optimizer, self.optimizer_step
              )
  
file_path: speechbrain/recipes/IWSLT22_lowresource/AST/transformer/train_with_w2v_mbart.py
imports: import sys
  import torch
  import logging
  import speechbrain
  from speechbrain.utils.distributed import run_on_main
  from hyperpyyaml import load_hyperpyyaml
  from sacremoses import MosesDetokenizer
  from torch.nn.parallel import DistributedDataParallel
label_desc: Use image node_id 3 for calling the ST obj's underlying member method code with example usage: obj.on_fit_batch_end(batch, outputs, loss, should_step) without return types