code: def train(
      self,
      resume_from_checkpoint: Optional[Union[str, bool]] = None,
      trial: Union["optuna.Trial", Dict[str, Any]] = None,
      **kwargs,
  ):
      return super().train(
          resume_from_checkpoint=resume_from_checkpoint,
          trial=trial,
          **kwargs,
      )
  
imports: import torch
  import torch.nn
  from dataclasses import dataclass, field
  from typing import Union, List, Dict, Tuple, Any, Optional
  from torch.cuda.amp import autocast
  from transformers import Seq2SeqTrainer, Seq2SeqTrainingArguments
  from transformers.trainer_pt_utils import LabelSmoother
  from transformers.trainer import *
  from ..seq2seq.constraint_decoder import get_constraint_decoder
label_desc: Use image node_id 3 for calling the ConstraintSeq2SeqTrainer obj's underlying member method code with example usage: obj.train(resume_from_checkpoint, trial) and returns: super