code: def forward(self, data):
      # here the residual connection is applied before the layernorm,
      # which is different from the PositionwiseFFN(pre_norm=True)
      out = self.layer_norm(data)
      out = self.activation(self.ffn_1(out))
      out = self.ffn_2(out)
      out = self.hidden_dropout(out)
      out = out + data
      return out
  
imports: import os
  from typing import Tuple
  import mxnet
  from mxnet import use_np, np, npx
  from mxnet.gluon import HybridBlock, nn
  from .base import BACKBONE_REGISTRY
  from ..base import get_model_zoo_home_dir, get_repo_model_zoo_url, get_model_zoo_checksum_dir
  from ..utils.config import CfgNode
  from ..utils.misc import load_checksum_stats, download
  from ..utils.registry import Registry
  from ..initializer import TruncNorm
  from ..attention_cell import MultiHeadAttentionCell
  from ..layers import get_activation, PositionalEmbedding
  from ..data.tokenizers import HuggingFaceByteBPETokenizer
label_desc: Use image node_id 2 for calling the GPT2FFN obj's underlying member method code with example usage: obj.forward(data) and returns: out