code: def input_prototype(self, use_gpu=False):
      input_prototype = self.model.input_prototype()
      if use_gpu:
          input_prototype = input_prototype.cuda()
      return (
          input_prototype.state.float_features,
          input_prototype.src_seq.float_features,
          input_prototype.tgt_out_seq.float_features,
          input_prototype.src_src_mask,
          input_prototype.tgt_out_idx,
      )
  
imports: import copy
  import logging
  from typing import List
  import torch
  import torch.nn
  import torch.nn.functional
  from reagent.core import types
  from reagent.core.torch_utils import gather
  from reagent.model_utils.seq2slate_utils import subsequent_mask
  from reagent.models.base import ModelBase
  from reagent.models.seq2slate import Decoder, DecoderLayer, Embedder, Encoder, EncoderLayer, MultiHeadedAttention, PositionalEncoding, PositionwiseFeedForward
label_desc: Use image node_id 2 for calling the Seq2SlateRewardNetJITWrapper obj's underlying member method code with example usage: obj.input_prototype(use_gpu) and returns: input_prototype,  input_prototype,  input_prototype,  input_prototype,  input_prototype