code: def __init__(
      self,
      dim,
      num_heads=8,
      qkv_bias=False,
      attn_drop=0.0,
      proj_drop=0.0,
  ):
      super().__init__()
      self.num_heads = num_heads
      head_dim = dim // num_heads
      self.scale = head_dim**-0.5
  
      self.qkv = nn.Linear(dim, dim * 3, bias_attr=qkv_bias)
      self.attn_drop = nn.Dropout(attn_drop)
      self.proj = nn.Linear(dim, dim)
      self.proj_drop = nn.Dropout(proj_drop)
  
imports: import math
  from functools import partial
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.utils import utils, logger
  from paddleseg.cvlibs.param_init import normal_init, trunc_normal_init, constant_init
  from paddleseg.models.backbones.transformer_utils import to_2tuple, DropPath
  from paddleseg.models.layers.vit_adapter_layers import SpatialPriorModule, InteractionBlock, deform_inputs
  from paddleseg.models.layers.ms_deformable_attention import MSDeformAttn
label_desc: Use image node_id 1 to create a new Attention object from inherited base classes: nn with example: obj = Attention(dim, num_heads, qkv_bias, attn_drop, proj_drop)