code: def __init__(self, num_classes=1):
      super(MyNet, self).__init__()
  
      self.conv1 = paddle.nn.Conv2D(
          in_channels=3, out_channels=32, kernel_size=(3, 3)
      )
      self.pool1 = paddle.nn.MaxPool2D(kernel_size=2, stride=2)
  
      self.conv2 = paddle.nn.Conv2D(
          in_channels=32, out_channels=64, kernel_size=(3, 3)
      )
      self.pool2 = paddle.nn.MaxPool2D(kernel_size=2, stride=2)
  
      self.conv3 = paddle.nn.Conv2D(
          in_channels=64, out_channels=64, kernel_size=(3, 3)
      )
  
      self.flatten = paddle.nn.Flatten()
  
      self.linear1 = paddle.nn.Linear(in_features=1024, out_features=64)
      self.linear2 = paddle.nn.Linear(
          in_features=64, out_features=num_classes
      )
  
file_path: VisualDL/demo/components/profiler_test.py
imports: import numpy
  import paddle
  import paddle.nn.functional
  import paddle.profiler
  from paddle.vision.transforms import ToTensor
label_desc: Use image node_id 1 to create a new MyNet object from inherited base classes: paddle.nn with example: obj = MyNet(num_classes)