code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      fromlower = self.upconv(self.submodule(x))
      att = self.attention(g=fromlower, x=x)
      att_m: torch.Tensor = self.merge(
          torch.cat((att, fromlower), dim=1)
      )
      return att_m
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  import torch
  import torch.nn
  from monai.networks.blocks.convolutions import Convolution
  from monai.networks.layers.factories import Norm
label_desc: Use image node_id 2 for calling the AttentionLayer obj's underlying member method code with example usage: obj.forward(x) and returns: att_m