code: def set_default_w2v_encoder_args(args):
      args.no_pretrained_weights = getattr(
          args, "no_pretrained_weights", False
      )
      args.dropout_input = getattr(args, "dropout_input", 0)
      args.final_dropout = getattr(args, "final_dropout", 0)
      args.apply_mask = getattr(args, "apply_mask", False)
      args.dropout = getattr(args, "dropout", 0)
      args.attention_dropout = getattr(args, "attention_dropout", 0)
      args.activation_dropout = getattr(args, "activation_dropout", 0)
      args.encoder_proj = getattr(args, "encoder_proj", False)
      args.remove_weight_norm = getattr(
          args, "remove_weight_norm", False
      )
  
      args.mask_length = getattr(args, "mask_length", 10)
      args.mask_prob = getattr(args, "mask_prob", 0.5)
      args.mask_selection = getattr(args, "mask_selection", "static")
      args.mask_other = getattr(args, "mask_other", 0)
      args.no_mask_overlap = getattr(args, "no_mask_overlap", False)
      args.mask_channel_length = getattr(
          args, "mask_channel_length", 10
      )
      args.mask_channel_prob = getattr(args, "mask_channel_prob", 0.5)
      args.mask_channel_before = getattr(
          args, "mask_channel_before", False
      )
      args.mask_channel_selection = getattr(
          args, "mask_channel_selection", "static"
      )
      args.mask_channel_other = getattr(args, "mask_channel_other", 0)
      args.no_mask_channel_overlap = getattr(
          args, "no_mask_channel_overlap", False
      )
  
      args.freeze_finetune_updates = getattr(
          args, "freeze_finetune_updates", 0
      )
      args.feature_grad_mult = 0.1
      args.layerdrop = getattr(args, "layerdrop", 0.0)
  
      args.normalize = getattr(args, "normalize", False)
      args.finetune_w2v_params = getattr(
          args, "finetune_w2v_params", "all"
      )
      args.w2v_freezing_updates = getattr(
          args, "w2v_freezing_updates", None
      )
      args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 1024)
  
imports: import copy
  import logging
  from typing import Dict, List, Optional, Tuple
  import numpy
  import torch
  import torch.nn
  from torch import Tensor
  from fairseq import checkpoint_utils, utils
  from fairseq.data.data_utils import lengths_to_padding_mask
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqEncoderModel, FairseqLanguageModel, register_model, register_model_architecture
  from fairseq.models.speech_to_speech.modules.ctc_decoder import CTCDecoder
  from fairseq.models.speech_to_text.hub_interface import S2THubInterface
  from fairseq.models.transformer import Embedding, TransformerDecoder, TransformerModelBase
  from fairseq.models.wav2vec import Wav2VecEncoder
  from fairseq.modules.layer_norm import LayerNorm
label_desc: Use image node_id 6 for calling a global function with example usage: set_default_w2v_encoder_args(args) without return types