code: def forward(
      self,
      x: torch.Tensor,
      y: torch.Tensor,
      x_mask: torch.Tensor,
      y_mask: torch.Tensor,
  ) -> torch.Tensor:
      x = self.ln_mha[0](
          x + self.drop_mha[0](self.multi_head_attn[0](x, x, x, x_mask))
      )
      x = self.ln_mha[1](
          x + self.drop_mha[1](self.multi_head_attn[1](x, y, y, y_mask))
      )
      x = self.ln_fcn(x + self.drop_fcn(self.fcn(x)))
  
      return x
  
imports: import math
  from typing import Optional, Tuple, Type
  import torch
  from mmf.modules.layers import GatedTanh, ModalCombineLayer, TransformLayer
  from torch import nn
label_desc: Use image node_id 2 for calling the SelfGuidedAttention obj's underlying member method code with example usage: obj.forward(x, y, x_mask, y_mask) and returns: x