code: def check_gpt2_output(output: tuple[int, int, int] | t.Any) -> bool:
      expected_shape = (1, 6, 768)
      if isinstance(output, tuple):
          return output == expected_shape
      elif isinstance(
          output, tf.TensorShape
      ):  # eh a special case for tf.
          return output == tf.TensorShape(expected_shape)
      else:
          return output.last_hidden_state.shape == expected_shape
  
imports: from __future__ import annotations
  import importlib
  import typing
  import numpy
  import requests
  import tensorflow
  import transformers
  from datasets import load_dataset
  from PIL import Image
  from transformers import Pipeline
  from transformers.pipelines import get_supported_tasks
  from transformers.pipelines import get_task
  from transformers.testing_utils import nested_simplify
  from transformers.trainer_utils import set_seed
  from transformers.utils import is_tf_available
  from transformers.utils import is_torch_available
  import bentoml
  from bentoml._internal.frameworks.transformers import SimpleDefaultMapping
  from bentoml._internal.frameworks.transformers import TaskDefinition
  from bentoml._internal.frameworks.transformers import convert_to_autoclass
  from bentoml._internal.frameworks.transformers import delete_pipeline
  from bentoml._internal.frameworks.transformers import register_pipeline
  from .None import FrameworkTestModel
  from .None import FrameworkTestModelConfiguration
  from .None import FrameworkTestModelInput
label_desc: Use image node_id 8 for calling a global function with example usage: check_gpt2_output(output) and returns: unknown, unknown, unknown