code: def __init__(self):
      super(ResNeXt50, self).__init__()
      with self.init_scope():
          self.conv1 = L.Convolution2D(
              3, 64, 7, 2, 3, initialW=initializers.HeNormal()
          )
          self.bn1 = L.BatchNormalization(64)
          self.res2 = Block(3, 64, 128, 256, 1, groups=32)
          self.res3 = Block(4, 256, 256, 512, groups=32)
          self.res4 = Block(6, 512, 512, 1024, groups=32)
          self.res5 = Block(3, 1024, 1024, 2048, groups=32)
          self.fc = L.Linear(2048, 1000)
  
imports: import chainer
  import chainer.functions
  from chainer import initializers
  import chainer.links
label_desc: Use image node_id 1 to create a new ResNeXt50 object from inherited base classes: chainer with example: obj = ResNeXt50()