docstr: Freezes the wav2vec2 optimizer according to the warmup steps
docstr_tok: ["Freezes","the","wav2vec2","optimizer","according","to","the","warmup","steps"]
code: def freeze_optimizers(self, optimizers):
      """Freezes the wav2vec2 optimizer according to the warmup steps"""
      valid_optimizers = {}
      if (
          not self.hparams.wav2vec2_frozen
          and self.optimizer_step >= self.hparams.wav2vec2_freeze_steps
      ):
          valid_optimizers["wav2vec_optimizer"] = optimizers[
              "wav2vec_optimizer"
          ]
      valid_optimizers["model_optimizer"] = optimizers[
          "model_optimizer"
      ]
      return valid_optimizers
  
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 3 for calling the S2UT obj's underlying member method code with example usage: obj.freeze_optimizers(optimizers) and returns: valid_optimizers