code: def forward(self, x):
      x_shape = paddle.shape(x)
      H, W = x_shape[2], x_shape[3]
  
      qq = (
          self.to_q(x)
          .reshape([0, self.num_heads, self.key_dim, -1])
          .transpose([0, 1, 3, 2])
      )
      kk = self.to_k(x).reshape([0, self.num_heads, self.key_dim, -1])
      vv = (
          self.to_v(x)
          .reshape([0, self.num_heads, self.d, -1])
          .transpose([0, 1, 3, 2])
      )
  
      attn = paddle.matmul(qq, kk)
      attn = F.softmax(attn, axis=-1)
  
      xx = paddle.matmul(attn, vv)
  
      xx = xx.transpose([0, 1, 3, 2]).reshape([0, self.dh, H, W])
      xx = self.proj(xx)
      return xx
  
imports: from functools import partial
  from collections import defaultdict
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import paddleseg
  from paddleseg import utils
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager
  from paddleseg.models.backbones.transformer_utils import Identity, DropPath
  from ppmatting.models.layers import MLFF
  from ppmatting.models.losses import MRSD, GradientLoss
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: xx