code: def test_nn_sequential_inherit(self):
      class ConvBNReLU(nn.Sequential):
          def __init__(self):
              super().__init__(
                  nn.Conv2d(3, 3, 1, 1, bias=False),
                  nn.BatchNorm2d(3),
                  nn.ReLU(inplace=False),
              )
  
      class Net(nn.Module):
          def __init__(self):
              super().__init__()
              self.conv_bn_relu = ConvBNReLU()
  
          def forward(self, x):
              return self.conv_bn_relu(x)
  
      model = Net()
      x = torch.rand((1, 3, 224, 224), dtype=torch.float)
      self.run_test(model, (x,))
  
file_path: nni/test/algo/nas/graph_converter/test_convert_models.py
imports: import unittest
  import torch
  import nni.nas.nn.pytorch.layers
  from .convert_mixin import ConvertMixin, ConvertWithShapeMixin
label_desc: Use image node_id 5 for calling the TestModels obj's underlying member method code with example usage: obj.test_nn_sequential_inherit() and returns: self