code: def __init__(self, n_heads, hidden_dim, dropout=0.1):
      super().__init__()
  
      self.self_attn = MultiHeadAttention(hidden_dim, n_heads)
      self.cross_attn = MultiHeadAttention(hidden_dim, n_heads)
      self.ff = FeedForwardLayer(hidden_dim)
  
      self.norm1 = LayerNorm(hidden_dim)
      self.norm2 = LayerNorm(hidden_dim)
      self.norm3 = LayerNorm(hidden_dim)
      self.dropout1 = nn.Dropout(dropout)
      self.dropout2 = nn.Dropout(dropout)
      self.dropout3 = nn.Dropout(dropout)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import math
  import copy
label_desc: Use image node_id 1 to create a new TransformerDecoderLayer object from inherited base classes: nn with example: obj = TransformerDecoderLayer(n_heads, hidden_dim, dropout)