code: def _trace_modules(self, model):
      input_ids = torch.tensor(
          [
              [
                  19,
                  669,
                  18,
                  420,
                  8,
                  664,
                  57,
                  42,
                  8,
                  664,
                  21,
                  3028,
                  195,
                  4445,
                  331,
                  1293,
                  34,
                  21,
                  10,
                  6174,
                  1100,
                  6,
                  69,
                  104,
                  42,
                  32,
                  2621,
                  1638,
                  144,
                  4,
                  6174,
                  558,
                  108,
                  4419,
                  1091,
                  28,
                  4,
                  1668,
                  9,
                  1509,
                  1621,
                  279,
                  35,
                  867,
                  2734,
                  85,
                  11,
                  2216,
                  2734,
                  85,
                  203,
                  2244,
                  7,
                  6,
                  15,
                  8102,
                  7,
                  57,
                  8629,
                  5,
                  model.config.eos_token_id,
              ]
          ],
          device=model.device,
          dtype=torch.long,
      )
      attention_mask = torch.tensor(
          [[True] * input_ids.shape[-1]],
          device=model.device,
          dtype=torch.bool,
      )
      self.encoder = _create_traced_encoder(
          model.get_encoder(), input_ids, attention_mask
      )
      encoder_outputs = model.get_encoder()(
          input_ids, attention_mask=attention_mask, return_dict=True
      )
      decoder = model.model.decoder
      decoder_outputs = decoder(
          input_ids,
          attention_mask,
          encoder_outputs["last_hidden_state"],
          None,
          None,
          None,
      )
      self.decoder_no_past = _create_traced_decoder(
          model.model.decoder,
          input_ids,
          encoder_outputs["last_hidden_state"],
          attention_mask,
      )
      self.decoder_with_past = _create_traced_decoder(
          model.model.decoder,
          input_ids,
          encoder_outputs["last_hidden_state"],
          attention_mask,
          decoder_outputs[1],
      )
  
imports: import copy
  import itertools
  from typing import List, Optional, Tuple
  import torch
  import torch.nn.functional
  from transformers import BartConfig
  from transformers.generation import GenerationMixin
label_desc: Use image node_id 2 for calling the BARTGenerator obj's underlying member method code with example usage: obj._trace_modules(model) without return types