code: def test_append_input_tensor(self):
      from typing import List
  
      class Net(nn.Module):
          def __init__(self, num_nodes):
              super().__init__()
              self.ops = nn.ModuleList()
              self.num_nodes = num_nodes
              for _ in range(num_nodes):
                  self.ops.append(nn.Linear(16, 16))
  
          def forward(self, x: List[torch.Tensor]):
              state = x
              for ops in self.ops:
                  state.append(ops(state[-1]))
              return state[-1]
  
      model = Net(4)
      x = torch.rand((1, 16), dtype=torch.float)
      self.run_test(model, ([x],), check_value=False)
  
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 2 for calling the TestModels obj's underlying member method code with example usage: obj.test_append_input_tensor() and returns: state