code: def state_dict(self) -> Dict[str, Any]:
      return {
          "train_scheduler_state": self._train_scheduler.state_dict(),
          "eval_scheduler_state": self._eval_scheduler.state_dict()
          if self._eval_scheduler is not None
          else {},
      }
  
imports: import logging
  import math
  from typing import Any, Callable, Dict
  from torch.optim import Optimizer
  from torch.optim.lr_scheduler import CosineAnnealingWarmRestarts, LambdaLR, ReduceLROnPlateau, SequentialLR
  from ludwig.constants import MINIMIZE, TRAINING, VALIDATION
  from ludwig.modules.metric_registry import get_metric_objective
  from ludwig.schema.lr_scheduler import LRSchedulerConfig
  from ludwig.utils.metric_utils import TrainerMetric
  from ludwig.utils.trainer_utils import ProgressTracker
label_desc: Use image node_id 4 for calling the LRScheduler obj's underlying member method code with example usage: obj.state_dict() and returns: dict