docstr: initialize with the necessary elements
docstr_tok: ["initialize","with","the","necessary","elements"]
code: def __init__(self):
      """
      initialize with the necessary elements
      """
      super(Plato2, self).__init__()
      args = self.setup_args()
  
      if args.num_layers == 24:
          n_head = 16
          hidden_size = 1024
      elif args.num_layers == 32:
          n_head = 32
          hidden_size = 2048
      else:
          raise ValueError(
              "The pre-trained model only support 24 or 32 layers, "
              "but received num_layers=%d." % args.num_layers
          )
  
      self.plato_reader = PlatoReader(args)
      nsp_reader = NSPReader(args)
      self.model = Plato2InferModel(
          nsp_reader, args.num_layers, n_head, hidden_size
      )
      state_dict = paddle.load(args.init_from_ckpt)
      self.model.set_state_dict(state_dict)
      self.model.eval()
      self.Example = namedtuple("Example", ["src", "data_id"])
      self.latent_type_size = args.latent_type_size
      self._interactive_mode = False
  
imports: import argparse
  import contextlib
  import os
  import sys
  from collections import namedtuple
  import paddle
  import paddle.nn
  import paddlehub
  from .model import Plato2InferModel
  from .readers.nsp_reader import NSPReader
  from .readers.plato_reader import PlatoReader
  from .utils import gen_inputs
  from .utils.args import parse_args
  from .utils.args import str2bool
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
  from paddlehub.module.nlp_module import DataFormatError
label_desc: Use image node_id 1 to create a new Plato2 object from inherited base classes: nn, hub with example: obj = Plato2()