code: def forward(self, *args, **kwargs):
      op_results = torch.stack(
          [op(*args, **kwargs) for op in self.op_choices.values()]
      )
      alpha_shape = [-1] + [1] * (len(op_results.size()) - 1)
      return torch.sum(
          op_results * F.softmax(self.alpha, -1).view(*alpha_shape), 0
      )
  
imports: import logging
  import torch
  import torch.optim
  import torch.nn
  import torch.nn.functional
  from .None import register_nas_algo
  from .base import BaseNAS
  from ..estimator.base import BaseEstimator
  from ..space import BaseSpace
  from ..utils import replace_layer_choice, replace_input_choice
label_desc: Use image node_id 2 for calling the DartsLayerChoice obj's underlying member method code with example usage: obj.forward() and returns: torch