code: def __init__(
      self,
      dim,
      mlp_ratio=4.0,
      act_layer=nn.ReLU,
      norm_layer=nn.LayerNorm,
      drop=0.0,
      drop_path=0.0,
      use_layer_scale=True,
      layer_scale_init_value=1e-5,
      resolution=7,
      stride=None,
  ):
      super().__init__()
  
      self.token_mixer = Attention4D(
          dim, resolution=resolution, act_layer=act_layer, stride=stride
      )
      mlp_hidden_dim = int(dim * mlp_ratio)
      self.mlp = Mlp(
          in_features=dim,
          hidden_features=mlp_hidden_dim,
          act_layer=act_layer,
          drop=drop,
          mid_conv=True,
      )
  
      self.drop_path = (
          DropPath(drop_path) if drop_path > 0.0 else nn.Identity()
      )
      self.use_layer_scale = use_layer_scale
      if use_layer_scale:
          param_value = layer_scale_init_value * paddle.ones(
              [dim]
          ).unsqueeze(-1).unsqueeze(-1)
          self.layer_scale_1 = self.create_parameter(
              shape=param_value.shape,
              dtype=str(param_value.numpy().dtype),
              default_initializer=nn.initializer.Assign(param_value),
          )
  
          self.layer_scale_2 = self.create_parameter(
              shape=param_value.shape,
              dtype=str(param_value.numpy().dtype),
              default_initializer=nn.initializer.Assign(param_value),
          )
  
imports: import math
  import itertools
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.utils import utils
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models.backbones.transformer_utils import *
label_desc: Use image node_id 1 to create a new AttnFFN object from inherited base classes: nn with example: obj = AttnFFN(dim, mlp_ratio, act_layer, norm_layer, drop, drop_path, use_layer_scale, layer_scale_init_value, resolution, stride)