code: def test_type_specs(self):
      class SpecialOutputType:
          pass
  
      class WrongOutputType:
          pass
  
      class ClassWithTypeSpec:
          @property
          def output_specs(self) -> Type:
              return SpecialOutputType
  
          @check_output_specs("output_specs", cache=False)
          def forward_pass(self, input_data) -> Any:
              return SpecialOutputType()
  
          @check_output_specs("output_specs", cache=False)
          def forward_fail(self, input_data) -> Any:
              return WrongOutputType()
  
      module = ClassWithTypeSpec()
      output = module.forward_pass(torch.rand(2, 4))
      self.assertIsInstance(output, SpecialOutputType)
      self.assertRaises(
          SpecCheckingError,
          lambda: module.forward_fail(torch.rand(2, 3)),
      )
  
imports: import abc
  import time
  import unittest
  from typing import Dict, Any, Type
  import numpy
  import torch
  from ray.rllib.core.models.specs.checker import SpecCheckingError
  from ray.rllib.core.models.specs.checker import convert_to_canonical_format, check_input_specs, check_output_specs
  from ray.rllib.core.models.specs.specs_base import TensorSpec, TypeSpec
  from ray.rllib.core.models.specs.specs_dict import SpecDict
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.nested_dict import NestedDict
label_desc: Use image node_id 8 for calling the TestCheckSpecs obj's underlying member method code with example usage: obj.test_type_specs() and returns: SpecialOutputType, SpecialOutputType, WrongOutputType