




'''simple docstring'''






import os

from bleurt import score  # From: git+https://github.com/google-research/bleurt.git

import datasets


__UpperCAmelCase       =							datasets.logging.get_logger(__name__)


__UpperCAmelCase       =							"\\n@inproceedings{bleurt,\n  title={BLEURT: Learning Robust Metrics for Text Generation},\n  author={Thibault Sellam and Dipanjan Das and Ankur P. Parikh},\n  booktitle={ACL},\n  year={2020},\n  url={https://arxiv.org/abs/2004.04696}\n}\n"

__UpperCAmelCase       =							"\\nBLEURT a learnt evaluation metric for Natural Language Generation. It is built using multiple phases of transfer learning starting from a pretrained BERT model (Devlin et al. 2018)\nand then employing another pre-training phrase using synthetic data. Finally it is trained on WMT human annotations. You may run BLEURT out-of-the-box or fine-tune\nit for your specific application (the latter is expected to perform better).\n\nSee the project's README at https://github.com/google-research/bleurt#readme for more information.\n"

__UpperCAmelCase       =							"\nBLEURT score.\n\nArgs:\n    `predictions` (list of str): prediction/candidate sentences\n    `references` (list of str): reference sentences\n    `checkpoint` BLEURT checkpoint. Will default to BLEURT-tiny if None.\n\nReturns:\n    'scores': List of scores.\nExamples:\n\n    >>> predictions = [\"hello there\", \"general kenobi\"]\n    >>> references = [\"hello there\", \"general kenobi\"]\n    >>> bleurt = datasets.load_metric(\"bleurt\")\n    >>> results = bleurt.compute(predictions=predictions, references=references)\n    >>> print([round(v, 2) for v in results[\"scores\"]])\n    [1.03, 1.04]\n"

__UpperCAmelCase       =							{
    "bleurt-tiny-128": "https://storage.googleapis.com/bleurt-oss/bleurt-tiny-128.zip",
    "bleurt-tiny-512": "https://storage.googleapis.com/bleurt-oss/bleurt-tiny-512.zip",
    "bleurt-base-128": "https://storage.googleapis.com/bleurt-oss/bleurt-base-128.zip",
    "bleurt-base-512": "https://storage.googleapis.com/bleurt-oss/bleurt-base-512.zip",
    "bleurt-large-128": "https://storage.googleapis.com/bleurt-oss/bleurt-large-128.zip",
    "bleurt-large-512": "https://storage.googleapis.com/bleurt-oss/bleurt-large-512.zip",
    "BLEURT-20-D3": "https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D3.zip",
    "BLEURT-20-D6": "https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D6.zip",
    "BLEURT-20-D12": "https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D12.zip",
    "BLEURT-20": "https://storage.googleapis.com/bleurt-oss-21/BLEURT-20.zip",
}




@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION    ,    _KWARGS_DESCRIPTION  )
class 		a__    (							datasets.Metric  ):





							'''simple docstring'''






							def   __SCREAMING_SNAKE_CASE							(		self       )	->							str:
														return datasets.MetricInfo(
														    description=_DESCRIPTION ,   citation=_CITATION ,   homepage='''https://github.com/google-research/bleurt''' ,   inputs_description=_KWARGS_DESCRIPTION ,   features=datasets.Features(
														        {
														            '''predictions''': datasets.Value('''string''' ,   id='''sequence'''       ),
														            '''references''': datasets.Value('''string''' ,   id='''sequence'''       ),
														        }       ) ,   codebase_urls=['''https://github.com/google-research/bleurt'''] ,   reference_urls=['''https://github.com/google-research/bleurt''', '''https://arxiv.org/abs/2004.04696'''] ,   )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_       )	->							List[Any]:
														# check that config name specifies a valid BLEURT model
														if self.config_name == "default":
																					logger.warning(
																					    '''Using default BLEURT-Base checkpoint for sequence maximum length 128. '''
																					    '''You can use a bigger model for better results with e.g.: datasets.load_metric(\'bleurt\', \'bleurt-large-512\').'''       )
																					lowerCAmelCase__	       =     "bleurt-base-128"

														if self.config_name.lower() in CHECKPOINT_URLS:
																					lowerCAmelCase__	       =     self.config_name.lower()

														elif self.config_name.upper() in CHECKPOINT_URLS:
																					lowerCAmelCase__	       =     self.config_name.upper()

														else:
																					raise KeyError(
																					    F"""{self.config_name} model not found. You should supply the name of a model checkpoint for bleurt in {CHECKPOINT_URLS.keys()}"""       )

														# download the model checkpoint specified by self.config_name and set up the scorer
														lowerCAmelCase__	       =     dl_manager.download_and_extract(CHECKPOINT_URLS[checkpoint_name]       )
														lowerCAmelCase__	       =     score.BleurtScorer(os.path.join(UpperCAmelCase_ ,   UpperCAmelCase_       )       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_       )	->							Optional[int]:
														lowerCAmelCase__	       =     self.scorer.score(references=UpperCAmelCase_ ,   candidates=UpperCAmelCase_       )
														return {"scores": scores}



'''simple docstring'''






import argparse
import json
import subprocess


def  _snake_case       (					A			,   A	)						->   Tuple:
							lowerCAmelCase__	       =     []

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

							lowerCAmelCase__	       =     status['''runners''']
							for runner in runners:
														if runner["name"] in target_runners:
																					if runner["status"] == "offline":
																												offline_runners.append(A	)

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

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


if __name__ == "__main__":


		def  _snake_case       (					A	)						->   Optional[Any]:
									return values.split(''','''	)

		__UpperCAmelCase       =							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.'''
		)
		__UpperCAmelCase       =							parser.parse_args()






		get_runner_status(args.target_runners, args.token)