code: def __init__(self, config):
      super().__init__()
      self.c_fc = nn.Linear(
          config.n_embd, 4 * config.n_embd, bias=config.bias
      )
      self.c_proj = nn.Linear(
          4 * config.n_embd, config.n_embd, bias=config.bias
      )
      self.dropout = nn.Dropout(config.dropout)
      self.gelu = nn.GELU()
  
imports: import math
  from dataclasses import dataclass
  import torch
  import torch.nn
  from torch.nn import functional
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: nn with example: obj = MLP(config)