code: def load_state_dict(self, d: Dict[str, Any]):
      self._train_scheduler.load_state_dict(d["train_scheduler_state"])
      if self._eval_scheduler is not None:
          self._eval_scheduler.load_state_dict(
              d["eval_scheduler_state"]
          )
  
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 5 for calling the LRScheduler obj's underlying member method code with example usage: obj.load_state_dict(d) without return types