code: def __init__(self):
      super(ResNet50, 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, 64, 256, 1)
          self.res3 = Block(4, 256, 128, 512)
          self.res4 = Block(6, 512, 256, 1024)
          self.res5 = Block(3, 1024, 512, 2048)
          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 ResNet50 object from inherited base classes: chainer with example: obj = ResNet50()