docstr: Called during ``on_fit_start()``, initialize optimizers
  after parameters are fully configured (e.g. DDP, jit).
docstr_tok: ["Called","during","``","on_fit_start","(",")","``",",","initialize","optimizers","after","parameters","are","fully","configured","(","e.g",".","DDP",",","jit",")","."]
code: def init_optimizers(self):
      """Called during ``on_fit_start()``, initialize optimizers
      after parameters are fully configured (e.g. DDP, jit).
      """
      self.optimizers_dict = {}
  
      # Initializes the wav2vec2 optimizer if the model is not wav2vec2_frozen
      if not self.hparams.wav2vec2_frozen:
          self.wav2vec_optimizer = self.hparams.wav2vec_opt_class(
              self.modules.wav2vec2.parameters()
          )
          self.optimizers_dict[
              "wav2vec_optimizer"
          ] = self.wav2vec_optimizer
  
      self.model_optimizer = self.hparams.opt_class(
          self.hparams.model.parameters()
      )
      self.optimizers_dict["model_optimizer"] = self.model_optimizer
  
      if self.checkpointer is not None:
          self.checkpointer.add_recoverable(
              "wav2vec_optimizer", self.wav2vec_optimizer
          )
          self.checkpointer.add_recoverable(
              "model_optimizer", self.model_optimizer
          )
  
imports: import sys
  import torch
  import logging
  import pathlib
  from hyperpyyaml import load_hyperpyyaml
  import speechbrain
  from speechbrain.inference.vocoders import UnitHIFIGAN
  from speechbrain.inference.ASR import EncoderDecoderASR
  import tqdm
  import torchaudio
  import numpy
  from torch.nn.parallel import DistributedDataParallel
label_desc: Use image node_id 4 for calling the S2UT obj's underlying member method code with example usage: obj.init_optimizers() without return types