code: def test_nested_shape_mismatch(self):
      class NestedShapeMismatch(Typing):
          @property
          def input_types(self):
              return {
                  "x": [[NeuralType(("D",), ElementType())]]
              }  # Each element of nest will have 4 values
  
          @property
          def output_types(self):
              return {
                  "y": [[NeuralType(("D",), ElementType())]]
              }  # Each element of nest will have 4 values
  
          @typecheck()
          def __call__(self, x):
              # v-- this is to satisfy 1 output constraint, python will otherwise interpret x as a 3 output value
              return x
  
      def bb(dim=4):
          return torch.zeros(dim)
  
      obj = NestedShapeMismatch()
  
      # Arbitrary nest 1 (should pass)
      data = [[bb(), bb(), bb()], [bb()], [bb(), bb()]]
      result = obj(x=data)
  
      recursive_assert_shape(result, torch.Size([4]))
      recursive_assert_homogeneous_type(
          result, NeuralType(("D",), ElementType())
      )
  
      # Arbitrary nest 2 (should pass)
      def bb(dim=4):
          return torch.zeros(dim, dim)
  
      data = [[bb(), bb(), bb()], [bb()], [bb(), bb()]]
      # Fails since input shape is incorrect
      with pytest.raises(TypeError):
          _ = obj(x=data)
  
      # Arbitrary nest 3
      def bb(dim=4):
          return torch.zeros(dim)
  
      data = [[[bb(), bb(), bb()]], [[bb()], [bb(), bb()]]]
      # Check should fail since nest level is 3!
      with pytest.raises(TypeError):
          result = obj(x=data)
  
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 26 for calling the TestNeuralTypeCheckSystem obj's underlying member method code with example usage: obj.test_nested_shape_mismatch() and returns: torch, torch, torch, dict, dict, x