class_docstr: builtin Darts Search Space
  Compared to Darts example, DartsSearchSpace removes Auxiliary Head, which
  is considered as a trick rather than part of model.
  
  Attributes
  ---
  in_channels: int
      the number of input channels
  channels: int
      the number of initial channels expected
  n_classes: int
      classes for final classification
  n_layers: int
      the number of cells contained in this network
  factory_func: function
      return a callable instance for demand cell structure.
      user should pass in ``__init__`` of the cell class with required parameters (see nni.nas.DartsCell for detail)
  n_nodes: int
      the number of nodes contained in each cell
  stem_multiplier: int
      channels multiply coefficient when passing a cell
code: def drop_path_prob(self, p):
      for module in self.modules():
          if isinstance(module, DropPath):
              module.p = p
  
imports: import torch.nn
  from nni.nas.pytorch.search_space_zoo.darts_ops import DropPath
label_desc: Use image node_id 3 for calling the DartsStackedCells obj's underlying member method code with example usage: obj.drop_path_prob(p) without return types