code: def wavlm_large(
      encoder_projection_dropout: float = 0.1,
      encoder_attention_dropout: float = 0.1,
      encoder_ff_interm_dropout: float = 0.0,
      encoder_dropout: float = 0.1,
      encoder_layer_drop: float = 0.1,
      aux_num_out: Optional[int] = None,
  ) -> Wav2Vec2Model:
      """Builds "large" WaveLM model :cite:`chen2022wavlm`. The architecture is compatible
      with Wav2Vec2 model :cite:`baevski2020wav2vec`, and so the output class is
      :class:`~torchaudio.models.Wav2Vec2Model`.
  
      Args:
          encoder_projection_dropout (float):
              See :py:func:`~torchaudio.models.wav2vec2_model`.
          encoder_attention_dropout (float):
              See :py:func:`~torchaudio.models.wav2vec2_model`.
          encoder_ff_interm_dropout (float):
              See :py:func:`~torchaudio.models.wav2vec2_model`.
          encoder_dropout (float):
              See :py:func:`~torchaudio.models.wav2vec2_model`.
          encoder_layer_drop (float):
              See :py:func:`~torchaudio.models.wav2vec2_model`.
          aux_num_out (int, optional):
              See :py:func:`~torchaudio.models.wav2vec2_model`.
  
      Returns:
          Wav2Vec2Model:
              The resulting model.
      """
      return wavlm_model(
          extractor_mode="layer_norm",
          extractor_conv_layer_config=None,
          extractor_conv_bias=False,
          encoder_embed_dim=1024,
          encoder_projection_dropout=encoder_projection_dropout,
          encoder_pos_conv_kernel=128,
          encoder_pos_conv_groups=16,
          encoder_num_layers=24,
          encoder_num_heads=16,
          encoder_num_buckets=320,
          encoder_max_distance=800,
          encoder_attention_dropout=encoder_attention_dropout,
          encoder_ff_interm_features=4096,
          encoder_ff_interm_dropout=encoder_ff_interm_dropout,
          encoder_dropout=encoder_dropout,
          encoder_layer_norm_first=True,
          encoder_layer_drop=encoder_layer_drop,
          aux_num_out=aux_num_out,
      )
  
imports: import math
  from typing import List, Optional, Tuple
  import torch
  from torch import Tensor
  from torch.nn import Module
  from .None import components
label_desc: Use image node_id 15 for calling a global function with example usage: wavlm_large(encoder_projection_dropout, encoder_attention_dropout, encoder_ff_interm_dropout, encoder_dropout, encoder_layer_drop, aux_num_out) and returns: wavlm_model