code: def forward_ffn(self, tgt):
      tgt2 = self.linear2(
          self.dropout3(self.activation(self.linear1(tgt)))
      )
      tgt = tgt + self.dropout4(tgt2)
      tgt = self.norm3(tgt)
      return tgt
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from ppdet.core.workspace import register
  from ..layers import MultiHeadAttention
  from .position_encoding import PositionEmbedding
  from .utils import _get_clones, get_valid_ratio
  from ..initializer import linear_init_, constant_, xavier_uniform_, normal_
label_desc: Use image node_id 4 for calling the DeformableTransformerDecoderLayer obj's underlying member method code with example usage: obj.forward_ffn(tgt) and returns: tgt