code: def forward(self, x):
      B, H, W, _ = x.shape
      # qkv with shape (3, B, nHead, H * W, C)
      qkv = (
          self.qkv(x)
          .reshape(B, H * W, 3, self.num_heads, -1)
          .permute(2, 0, 3, 1, 4)
      )
      # q, k, v with shape (B * nHead, H * W, C)
      q, k, v = qkv.reshape(3, B * self.num_heads, H * W, -1).unbind(0)
  
      attn = (q * self.scale) @ k.transpose(-2, -1)
  
      if self.use_rel_pos:
          attn = add_decomposed_rel_pos(
              attn, q, self.rel_pos_h, self.rel_pos_w, (H, W), (H, W)
          )
  
      attn = attn.softmax(dim=-1)
      x = (
          (attn @ v)
          .view(B, self.num_heads, H, W, -1)
          .permute(0, 2, 3, 1, 4)
          .reshape(B, H, W, -1)
      )
      x = self.proj(x)
  
      return x
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import build_activation_layer, build_norm_layer
  from mmcv.cnn.bricks import DropPath
  from mmengine.logging import MMLogger
  from mmengine.model import BaseModule
  from mmengine.runner.checkpoint import CheckpointLoader
  from mmdet.registry import MODELS
label_desc: Use image node_id 2 for calling the Attention obj's underlying member method code with example usage: obj.forward(x) and returns: x