import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links







def 						A__  (					__A   , __A=7	):







    '''simple docstring'''
    _lowerCamelCase     :		List[Any] 						=						None
    if token is not None:
        _lowerCamelCase     :		Tuple 						=						{"""Accept""": """application/vnd.github+json""", """Authorization""": F"""Bearer {token}"""}

    # The id of a workflow (not of a workflow run)
    _lowerCamelCase     :		int 						=						"""636036"""

    _lowerCamelCase     :		Optional[int] 						=						F"""https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"""
    # On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
    url += F"""?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"""

    _lowerCamelCase     :		List[Any] 						=						requests.get(__A   , headers=__A	).json()

    return result["workflow_runs"]







def 						A__  (					__A	):







    '''simple docstring'''
    _lowerCamelCase     :		Union[str, Any] 						=						get_daily_ci_runs(__A	)
    _lowerCamelCase     :		Optional[Any] 						=						None
    for workflow_run in workflow_runs:
        if workflow_run["status"] == "completed":
            _lowerCamelCase     :		str 						=						workflow_run["""id"""]
            break

    return workflow_run_id







def 						A__  (					__A   , __A   , __A	):







    '''simple docstring'''
    _lowerCamelCase     :		str 						=						get_last_daily_ci_runs(__A	)
    if workflow_run_id is not None:
        _lowerCamelCase     :		Tuple 						=						get_artifacts_links(worflow_run_id=__A   , token=__A	)
        for artifact_name in artifact_names:
            if artifact_name in artifacts_links:
                _lowerCamelCase     :		Optional[Any] 						=						artifacts_links[artifact_name]
                download_artifact(
                    artifact_name=__A   , artifact_url=__A   , output_dir=__A   , token=__A	)







def 						A__  (					__A   , __A   , __A	):







    '''simple docstring'''
    get_last_daily_ci_artifacts(__A   , __A   , __A	)

    _lowerCamelCase     :		List[str] 						=						{}
    for artifact_name in artifact_names:
        _lowerCamelCase     :		str 						=						os.path.join(__A   , F"""{artifact_name}.zip"""	)
        if os.path.isfile(__A	):
            _lowerCamelCase     :		Tuple 						=						{}
            with zipfile.ZipFile(__A	) as z:
                for filename in z.namelist():
                    if not os.path.isdir(__A	):
                        # read the file
                        with z.open(__A	) as f:
                            _lowerCamelCase     :		Any 						=						f.read().decode("""UTF-8"""	)

    return results





import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp







def 						A__  (					):







    '''simple docstring'''
    _lowerCamelCase     :		Optional[int] 						=						ArgumentParser(
        description=(
            """PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes"""
        )	)

    # Optional arguments for the launch helper
    parser.add_argument("""--num_cores"""   , type=__A   , default=1   , help="""Number of TPU cores to use (1 or 8)."""	)

    # positional
    parser.add_argument(
        """training_script"""   , type=__A   , help=(
            """The full path to the single TPU training """
            """program/script to be launched in parallel, """
            """followed by all the arguments for the """
            """training script"""
        )   , )

    # rest from the training program
    parser.add_argument("""training_script_args"""   , nargs=__A	)

    return parser.parse_args()







def 						A__  (					):







    '''simple docstring'''
    _lowerCamelCase     :		List[str] 						=						parse_args()

    # Import training_script as a module.
    _lowerCamelCase     :		List[Any] 						=						Path(args.training_script	)
    sys.path.append(str(script_fpath.parent.resolve()	)	)
    _lowerCamelCase     :		Optional[Any] 						=						script_fpath.stem
    _lowerCamelCase     :		Dict 						=						importlib.import_module(__A	)

    # Patch sys.argv
    _lowerCamelCase     :		Union[str, Any] 						=						[args.training_script] + args.training_script_args + ["""--tpu_num_cores""", str(args.num_cores	)]

    xmp.spawn(mod._mp_fn   , args=()   , nprocs=args.num_cores	)


if __name__ == "__main__":
    main()




