code: def __init__(
      self,
      embed_dims=256,
      feedforward_channels=1024,
      act_fn=nn.ReLU,
      ffn_drop=0.0,
      dropout_layer=None,
      add_identity=True,
  ):
      super().__init__()
      self.embed_dims = embed_dims
      self.feedforward_channels = feedforward_channels
      self.activate = act_fn()
  
      layers = []
      in_channels = embed_dims
      layers.append(
          nn.Sequential(
              nn.Linear(in_channels, feedforward_channels),
              self.activate,
              nn.Dropout(ffn_drop),
          )
      )
      layers.append(nn.Linear(feedforward_channels, embed_dims))
      layers.append(nn.Dropout(ffn_drop))
      self.layers = nn.Sequential(*layers)
      self.dropout_layer = (
          nn.Dropout() if dropout_layer else nn.Identity()
      )
      self.add_identity = add_identity
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg import utils
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  from .upernet import UPerNetHead
label_desc: Use image node_id 1 to create a new FFN object from inherited base classes: nn with example: obj = FFN(embed_dims, feedforward_channels, act_fn, ffn_drop, dropout_layer, add_identity)