code: def test_input_container_neural_types(self):
      class NodeA(Typing):
          @property
          def input_types(self):
              return {"x": [NeuralType(("B",), ElementType())]}
  
          @property
          def output_types(self):
              return {"y": NeuralType(("B", "D"), LogitsType())}
  
          @typecheck()
          def __call__(self, x: list()):
              x1, x2, x3 = x  # unpack x
              y = torch.randn(x1.shape[0], 4)
              return y
  
      nodeA = NodeA()
      outA = nodeA(
          x=[torch.zeros(10), torch.zeros(10), torch.zeros(10)]
      )
  
      assert outA.neural_type.compare(
          NeuralType(("B", "D"), LogitsType())
      )
  
imports: from typing import List, NamedTuple
  import pytest
  import torch
  from nemo.core import Typing, typecheck
  from nemo.core.neural_types import *
label_desc: Use image node_id 28 for calling the TestNeuralTypeCheckSystem obj's underlying member method code with example usage: obj.test_input_container_neural_types() and returns: dict, dict, y