code: def make_from_optimizer(
      self, optimizer: torch.optim.Optimizer
  ) -> torch.optim.lr_scheduler._LRScheduler:
      torch_lr_scheduler_class = getattr(
          torch.optim.lr_scheduler, type(self).__name__
      )
      assert is_torch_lr_scheduler(
          torch_lr_scheduler_class
      ), f"{torch_lr_scheduler_class} is not a scheduler."
  
      filtered_args = {
          k: getattr(self, k)
          for k in inspect.signature(
              torch_lr_scheduler_class
          ).parameters
          if k != "optimizer"
      }
  
      self.decode_lambdas(filtered_args)
  
      return torch_lr_scheduler_class(
          optimizer=optimizer, **filtered_args
      )
  
file_path: ReAgent/reagent/optimizer/scheduler.py
imports: import inspect
  from typing import Any, Dict
  import torch
  from reagent.core.dataclasses import dataclass
  from reagent.core.registry_meta import RegistryMeta
  from .utils import is_torch_lr_scheduler
label_desc: Use image node_id 1 for calling the LearningRateSchedulerConfig obj's underlying member method code with example usage: obj.make_from_optimizer(optimizer) and returns: torch_lr_scheduler_class