code: def __init__(self, n_class, profile="normal"):
      super(MobileNet, self).__init__()
  
      # original
      if profile == "normal":
          in_planes = 32
          cfg = [
              64,
              (128, 2),
              128,
              (256, 2),
              256,
              (512, 2),
              512,
              512,
              512,
              512,
              512,
              (1024, 2),
              1024,
          ]
      # 0.5 AMC
      elif profile == "0.5flops":
          in_planes = 24
          cfg = [
              48,
              (96, 2),
              80,
              (192, 2),
              200,
              (328, 2),
              352,
              368,
              360,
              328,
              400,
              (736, 2),
              752,
          ]
      else:
          raise NotImplementedError
  
      self.conv1 = conv_bn(3, in_planes, stride=2)
  
      self.features = self._make_layers(in_planes, cfg, conv_dw)
  
      self.classifier = nn.Sequential(
          nn.Linear(cfg[-1], n_class),
      )
  
      self._initialize_weights()
  
file_path: nni/test/ut/sdk/models/pytorch_models/mobilenet.py
imports: import torch.nn
  import math
label_desc: Use image node_id 1 to create a new MobileNet object from inherited base classes: nn with example: obj = MobileNet(n_class, profile)