code: def test_output_container_neural_types_no_tuple_wrap(self):
      class NodeA(Typing):
          @property
          def input_types(self):
              # Nest depth level of 2
              return {"x": NeuralType(("B",), ElementType())}
  
          @property
          def output_types(self):
              return {"y": [NeuralType(("B", "D"), LogitsType())]}
  
          @typecheck()
          def __call__(self, x):
              y = torch.randn(x.shape[0], 4)
              y = [y, y, y]
              return y
  
      nodeA = NodeA()
      # Input nest level of 1
      outA = nodeA(x=torch.zeros(10))
  
      assert len(outA) == 3
      for i in range(len(outA)):
          assert outA[i].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 31 for calling the TestNeuralTypeCheckSystem obj's underlying member method code with example usage: obj.test_output_container_neural_types_no_tuple_wrap() and returns: dict, dict, y