code: def __init__(
      self,
      units: int = 768,
      hidden_size: int = 3072,
      layer_norm_eps: float = 1e-5,
      hidden_dropout_prob: float = 0.1,
      weight_initializer=None,
      bias_initializer="zeros",
      activation="gelu(tanh)",
      dtype="float32",
  ):
      super().__init__()
      self._units = units
      self._hidden_size = hidden_size
      self._layer_norm_eps = layer_norm_eps
      self._hidden_dropout_prob = hidden_dropout_prob
      self._weight_initializer = weight_initializer
      self._bias_initializer = bias_initializer
      self._activation = activation
      self._dtype = dtype
      self.layer_norm = nn.LayerNorm(
          epsilon=self._layer_norm_eps, in_channels=self._units
      )
      self.ffn_1 = nn.Dense(
          units=self._hidden_size,
          in_units=self._units,
          flatten=False,
          weight_initializer=self._weight_initializer,
          bias_initializer=self._bias_initializer,
          dtype=self._dtype,
      )
      self.activation = get_activation(self._activation)
      self.ffn_2 = nn.Dense(
          units=self._units,
          in_units=self._hidden_size,
          flatten=False,
          weight_initializer=self._weight_initializer,
          bias_initializer=self._bias_initializer,
          dtype=self._dtype,
      )
      self.hidden_dropout = nn.Dropout(self._hidden_dropout_prob)
  
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 1 to create a new GPT2FFN object from inherited base classes: HybridBlock with example: obj = GPT2FFN(units, hidden_size, layer_norm_eps, hidden_dropout_prob, weight_initializer, bias_initializer, activation, dtype)