






"""simple docstring"""







import argparse
import json
import subprocess






def       _lowerCAmelCase       (      lowerCAmelCase	,      lowerCAmelCase		):







       '''simple docstring'''
       UpperCAmelCase	    =			[]

       UpperCAmelCase	    =			(
           F'''curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'''
           """ https://api.github.com/repos/huggingface/transformers/actions/runners"""
       )
       UpperCAmelCase	    =			subprocess.run(lowerCAmelCase	,      shell=lowerCAmelCase	,      stdout=subprocess.PIPE		)
       UpperCAmelCase	    =			output.stdout.decode("""utf-8"""		)
       UpperCAmelCase	    =			json.loads(lowerCAmelCase		)

       UpperCAmelCase	    =			status["""runners"""]
       for runner in runners:
              if runner["name"] in target_runners:
                     if runner["status"] == "offline":
                            offline_runners.append(lowerCAmelCase		)

    # save the result so we can report them on Slack
       with open("""offline_runners.txt"""	,      """w"""		) as fp:
              fp.write(json.dumps(lowerCAmelCase		)		)

       if len(lowerCAmelCase		) > 0:
              UpperCAmelCase	    =			"""\n""".join([x["""name"""] for x in offline_runners]		)
              raise ValueError(F'''The following runners are offline:\n{failed}'''		)


if __name__ == "__main__":






 def       _lowerCAmelCase       (      lowerCAmelCase		):







        '''simple docstring'''
        return values.split(""","""		)

 lowerCAmelCase_	:    str            =      argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     '''--target_runners''',
     default=None,
     type=list_str,
     required=True,
     help='''Comma-separated list of runners to check status.''',
 )

 parser.add_argument(
     '''--token''', default=None, type=str, required=True, help='''A token that has actions:read permission.'''
 )
 lowerCAmelCase_	:    str            =      parser.parse_args()





 get_runner_status(args.target_runners, args.token)








"""simple docstring"""







from . import __version__

# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
    CLOUDFRONT_DISTRIB_PREFIX,
    CONFIG_NAME,
    DISABLE_TELEMETRY,
    DUMMY_INPUTS,
    DUMMY_MASK,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    FEATURE_EXTRACTOR_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_PREFIX,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    MODEL_CARD_NAME,
    MULTIPLE_CHOICE_DUMMY_INPUTS,
    PYTORCH_PRETRAINED_BERT_CACHE,
    PYTORCH_TRANSFORMERS_CACHE,
    S3_BUCKET_PREFIX,
    SENTENCEPIECE_UNDERLINE,
    SPIECE_UNDERLINE,
    TF2_WEIGHTS_NAME,
    TF_WEIGHTS_NAME,
    TORCH_FX_REQUIRED_VERSION,
    TRANSFORMERS_CACHE,
    TRANSFORMERS_DYNAMIC_MODULE_NAME,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    WEIGHTS_INDEX_NAME,
    WEIGHTS_NAME,
    ContextManagers,
    DummyObject,
    EntryNotFoundError,
    ExplicitEnum,
    ModelOutput,
    PaddingStrategy,
    PushToHubMixin,
    RepositoryNotFoundError,
    RevisionNotFoundError,
    TensorType,
    _LazyModule,
    add_code_sample_docstrings,
    add_end_docstrings,
    add_start_docstrings,
    add_start_docstrings_to_model_forward,
    cached_property,
    copy_func,
    default_cache_path,
    define_sagemaker_information,
    get_cached_models,
    get_file_from_repo,
    get_full_repo_name,
    get_torch_version,
    has_file,
    http_user_agent,
    is_apex_available,
    is_bsa_available,
    is_coloredlogs_available,
    is_datasets_available,
    is_detectrona_available,
    is_faiss_available,
    is_flax_available,
    is_ftfy_available,
    is_in_notebook,
    is_ipex_available,
    is_librosa_available,
    is_offline_mode,
    is_onnx_available,
    is_pandas_available,
    is_phonemizer_available,
    is_protobuf_available,
    is_psutil_available,
    is_pyanvml_available,
    is_pyctcdecode_available,
    is_pytesseract_available,
    is_pytorch_quantization_available,
    is_rjieba_available,
    is_sagemaker_dp_enabled,
    is_sagemaker_mp_enabled,
    is_scipy_available,
    is_sentencepiece_available,
    is_seqio_available,
    is_sklearn_available,
    is_soundfile_availble,
    is_spacy_available,
    is_speech_available,
    is_tensor,
    is_tensorflow_probability_available,
    is_tfaonnx_available,
    is_tf_available,
    is_timm_available,
    is_tokenizers_available,
    is_torch_available,
    is_torch_bfaa_available,
    is_torch_cuda_available,
    is_torch_fx_available,
    is_torch_fx_proxy,
    is_torch_mps_available,
    is_torch_tfaa_available,
    is_torch_tpu_available,
    is_torchaudio_available,
    is_training_run_on_sagemaker,
    is_vision_available,
    replace_return_docstrings,
    requires_backends,
    to_numpy,
    to_py_obj,
    torch_only_method,
)
