code: def __init__(
      self, n_state, config
  ):  # in MLP: n_state=3072 (4 * n_embd)
      super(MLP, self).__init__()
      self.c_fc = Conv1D(n_state, 1, config.embedding_dim)
      self.c_proj = Conv1D(config.embedding_dim, 1, n_state)
      self.act = _ACTIVATION_FUNCTIONS[config.activation_function]
      self.dropout = torch.nn.Dropout(
          config.residual_dropout_probability
      )
  
imports: from __future__ import with_statement
  from __future__ import division
  from __future__ import absolute_import
  import copy
  import io
  import json
  import logging
  import math
  import re
  import tarfile
  import numpy
  import torch
  from torch.nn import Parameter
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.file_utils import cached_path
  from allennlp.common.from_params import FromParams
  from io import open
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: torch.nn with example: obj = MLP(n_state, config)