class_docstr: The full search space proposed by `NAS-Bench-201 <https://arxiv.org/abs/2001.00326>`__.
  
  It's a stack of :class:`~nni.nas.hub.pytorch.modules.NasBench201Cell`.
  
  Parameters
  ----------
  stem_out_channels
      The output channels of the stem.
  num_modules_per_stack
      The number of modules (cells) in each stack. Each cell is a :class:`~nni.nas.hub.pytorch.modules.NasBench201Cell`.
  num_labels
      Number of categories for classification.
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code: def forward(self, inputs):
      feature = self.stem(inputs)
      for cell in self.cells:
          feature = cell(feature)
  
      out = self.lastact(feature)
      out = self.global_pooling(out)
      out = out.view(out.size(0), -1)
      logits = self.classifier(out)
  
      return logits
  
imports: from typing import Callable, Dict
  import torch
  import torch.nn
  from nni.nas.nn.pytorch import ModelSpace
  from .modules.nasbench201 import NasBench201Cell
label_desc: Use image node_id 3 for calling the NasBench201 obj's underlying member method code with example usage: obj.forward(inputs) and returns: logits