code: def __init__(self, n_in, n_out, dropout=0):
      super().__init__()
  
      self.linear = nn.Linear(n_in, n_out)
      self.activation = nn.GELU()
      self.dropout = nn.Dropout(dropout)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
  from transformers import AutoModel
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: nn with example: obj = MLP(n_in, n_out, dropout)