code: def __init__(
      self,
      x_dim: int,
      y_dim: int,
      proj_dim: int = 32,
      n_heads: int = 16,
      multiplier: int = 4,
  ):
      # x_dim = size of the last dimension of x
      # y_dim = size of the last dimension of y
      super().__init__()
      self.norm_layer_x = torch.nn.LayerNorm(x_dim)
      self.norm_layer_y = torch.nn.LayerNorm(y_dim)
      self.module_list = torch.nn.ModuleList(
          [
              AttentionHead(x_dim, y_dim, proj_dim)
              for _ in range(n_heads)
          ]
      )
      self.linear = torch.nn.Linear(n_heads * proj_dim, x_dim)
  
      self.dense = AttentionDenseBlock(x_dim, multiplier)
  
file_path: nebuly/optimization/open_alpha_tensor/open_alpha_tensor/core/modules/attention.py
imports: import torch
  from torch.nn import functional
label_desc: Use image node_id 1 to create a new AlphaMultiHeadAttention object from inherited base classes: torch.nn with example: obj = AlphaMultiHeadAttention(x_dim, y_dim, proj_dim, n_heads, multiplier)