code: def init_shaw_embedding(embed: StandardEmbedding) -> None:
      """Initialize ``embed`` for use in :class:`ShawRelativePositionSDPA`."""
      nn.init.xavier_uniform_(embed.weight)
  
file_path: fairseq2/src/fairseq2/nn/transformer/shaw_attention.py
imports: from typing import Optional, Tuple, final
  import torch
  import torch.nn
  from torch import Tensor
  from fairseq2.nn.embedding import StandardEmbedding
  from fairseq2.nn.padding import PaddingMask
  from fairseq2.nn.transformer.attention import SDPA, create_default_sdpa
  from fairseq2.nn.transformer.attention_mask import AttentionMask, CustomAttentionMask
  from fairseq2.typing import DataType, Device, finaloverride
label_desc: Use image node_id 1 for calling a global function with example usage: init_shaw_embedding(embed) without return types