class_docstr: Search implementation of :class:`~nni.nas.strategy.DARTS`.
  
  The dataloader is expected to be a CombinedLoader with two keys: ``train`` and ``val``.
  
  See Also
  --------
  nni.nas.strategy.DARTS
  nni.nas.pytorch.oneshot.base_lightning.BaseOneShotLightningModule
class_docstr_tok: ["Search","implementation","of",":","class",":","`","~nni.nas.strategy.DARTS","`",".","The","dataloader","is","expected","to","be","a","CombinedLoader","with","two","keys",":","``","train","``","and","``","val","``",".","See","Also","--","--","--","--","nni.nas.strategy.DARTS","nni.nas.pytorch.oneshot.base_lightning.BaseOneShotLightningModule"]
code: def configure_architecture_optimizers(self):
      ctrl_params = self.arch_parameters()
      if not ctrl_params:
          raise ValueError(
              "No architecture parameters found. Nothing to search."
          )
      ctrl_optim = torch.optim.Adam(
          ctrl_params,
          self.arc_learning_rate,
          betas=(0.5, 0.999),
          weight_decay=1.0e-3,
      )
  
      return ctrl_optim
  
imports: from __future__ import annotations
  import logging
  import pytorch_lightning
  import torch
  import torch.nn
  import torch.optim
  from .base_lightning import BaseOneShotLightningModule
  from .supermodule.differentiable import GumbelSoftmax
  from .profiler import ExpectationProfilerPenalty
label_desc: Use image node_id 6 for calling the DartsLightningModule obj's underlying member method code with example usage: obj.configure_architecture_optimizers() and returns: ctrl_optim