code: def __init__(self, num_classes=1001):
      super(InceptionV4, self).__init__()
      # Special attributs
      self.input_space = None
      self.input_size = (299, 299, 3)
      self.mean = None
      self.std = None
      # Modules
      self.features = nn.Sequential(
          BasicConv2d(3, 32, kernel_size=3, stride=2),  # 0, layer0
          BasicConv2d(32, 32, kernel_size=3, stride=1),  # 1, layer0
          BasicConv2d(32, 64, kernel_size=3, stride=1, padding=1),  # 2
          Mixed_3a(),  # 3
          Mixed_4a(),  # 4
          Mixed_5a(),  # 5
          Inception_A(),  # 6
          Inception_A(),  # 7
          Inception_A(),  # 8
          Inception_A(),  # 9
          Reduction_A(),  # 10 # Mixed_6a
          Inception_B(),  # 11
          Inception_B(),  # 12
          Inception_B(),  # 13
          Inception_B(),  # 14
          Inception_B(),  # 15
          Inception_B(),  # 16
          Inception_B(),  # 17
          Reduction_B(),  # 18  # Mixed_7a
          Inception_C(),  # 19
          Inception_C(),  # 20
          Inception_C(),  # 21
      )
      self.last_linear = nn.Linear(1536, num_classes)
  
imports: from __future__ import print_function, division, absolute_import
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.model_zoo
label_desc: Use image node_id 1 to create a new InceptionV4 object from inherited base classes: nn with example: obj = InceptionV4(num_classes)