code: def check_min_version(min_version):
      if version.parse(__version__) < version.parse(min_version):
          if "dev" in min_version:
              error_message = (
                  "This example requires a source install from HuggingFace Transformers (see "
                  "`https://huggingface.co/transformers/installation.html#installing-from-source`),"
              )
          else:
              error_message = f"This example requires a minimum version of {min_version},"
          error_message += f" but the version found is {__version__}.\n"
          raise ImportError(
              error_message
              + "Check out https://huggingface.co/transformers/examples.html for the examples corresponding to other "
              "versions of HuggingFace Transformers."
          )
  
imports: from packaging import version
  from ..None import __version__
  from .constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_STANDARD_MEAN, IMAGENET_STANDARD_STD
  from .doc import add_code_sample_docstrings, add_end_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, copy_func, replace_return_docstrings
  from .generic import ContextManagers, ExplicitEnum, ModelOutput, PaddingStrategy, TensorType, cached_property, expand_dims, find_labels, flatten_dict, is_jax_tensor, is_numpy_array, is_tensor, is_tf_tensor, is_torch_device, is_torch_tensor, reshape, squeeze, tensor_size, to_numpy, to_py_obj, transpose, working_or_temp_dir
  from .hub import CLOUDFRONT_DISTRIB_PREFIX, DISABLE_TELEMETRY, HF_MODULES_CACHE, HUGGINGFACE_CO_PREFIX, HUGGINGFACE_CO_RESOLVE_ENDPOINT, PYTORCH_PRETRAINED_BERT_CACHE, PYTORCH_TRANSFORMERS_CACHE, S3_BUCKET_PREFIX, TRANSFORMERS_CACHE, TRANSFORMERS_DYNAMIC_MODULE_NAME, EntryNotFoundError, PushToHubMixin, RepositoryNotFoundError, RevisionNotFoundError, cached_file, default_cache_path, define_sagemaker_information, download_url, extract_commit_hash, get_cached_models, get_file_from_repo, get_full_repo_name, has_file, http_user_agent, is_offline_mode, is_remote_url, move_cache, send_example_telemetry
  from .import_utils import ENV_VARS_TRUE_AND_AUTO_VALUES, ENV_VARS_TRUE_VALUES, TORCH_FX_REQUIRED_VERSION, USE_JAX, USE_TF, USE_TORCH, DummyObject, OptionalDependencyNotAvailable, _LazyModule, ccl_version, is_accelerate_available, is_apex_available, is_bitsandbytes_available, is_bs4_available, is_coloredlogs_available, is_datasets_available, is_detectron2_available, is_faiss_available, is_flax_available, is_ftfy_available, is_in_notebook, is_ipex_available, is_jumanpp_available, is_kenlm_available, is_librosa_available, is_more_itertools_available, is_ninja_available, is_onnx_available, is_pandas_available, is_phonemizer_available, is_protobuf_available, is_psutil_available, is_py3nvml_available, is_pyctcdecode_available, is_pytesseract_available, is_pytorch_quantization_available, is_rjieba_available, is_sacremoses_available, is_safetensors_available, is_sagemaker_dp_enabled, is_sagemaker_mp_enabled, is_scatter_available, is_scipy_available, is_sentencepiece_available, is_sklearn_available, is_soundfile_availble, is_spacy_available, is_speech_available, is_sudachi_available, is_tensorflow_probability_available, is_tensorflow_text_available, is_tf2onnx_available, is_tf_available, is_timm_available, is_tokenizers_available, is_torch_available, is_torch_bf16_available, is_torch_bf16_cpu_available, is_torch_bf16_gpu_available, is_torch_cuda_available, is_torch_fx_available, is_torch_fx_proxy, is_torch_onnx_dict_inputs_support_available, is_torch_tensorrt_fx_available, is_torch_tf32_available, is_torch_tpu_available, is_torchaudio_available, is_torchdynamo_available, is_training_run_on_sagemaker, is_vision_available, requires_backends, tf_required, torch_only_method, torch_required, torch_version
label_desc: Use image node_id 1 for calling a global function with example usage: check_min_version(min_version) without return types