code: def _get_config_wavlm(cfg):
      config = {
          "extractor_mode": f"{cfg.feat_extract_norm}_norm",
          "extractor_conv_layer_config": list(
              zip(cfg.conv_dim, cfg.conv_kernel, cfg.conv_stride)
          ),
          "extractor_conv_bias": cfg.conv_bias,
          "encoder_embed_dim": cfg.hidden_size,
          "encoder_projection_dropout": cfg.feat_proj_dropout,
          "encoder_pos_conv_kernel": cfg.num_conv_pos_embeddings,
          "encoder_pos_conv_groups": cfg.num_conv_pos_embedding_groups,
          "encoder_num_layers": cfg.num_hidden_layers,
          "encoder_num_heads": cfg.num_attention_heads,
          "encoder_num_buckets": cfg.num_buckets,
          "encoder_max_distance": cfg.max_bucket_distance,
          "encoder_attention_dropout": cfg.attention_dropout,
          "encoder_ff_interm_features": cfg.intermediate_size,
          "encoder_ff_interm_dropout": cfg.activation_dropout,
          "encoder_dropout": cfg.hidden_dropout,
          "encoder_layer_norm_first": cfg.do_stable_layer_norm,
          "encoder_layer_drop": cfg.layerdrop,
      }
      return config
  
file_path: audio/src/torchaudio/models/wav2vec2/utils/import_huggingface.py
imports: import logging
  from typing import Any, Dict
  import torch
  from torch.nn import Module
  from ..model import wav2vec2_model, Wav2Vec2Model, wavlm_model
label_desc: Use image node_id 2 for calling a global function with example usage: _get_config_wavlm(cfg) and returns: config