
'''simple docstring'''
import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE=7       ):
    """simple docstring"""






    snake_case_ :    List[Any]     			=						None
    if token is not None:
        snake_case_ :    int     			=						{"Accept": "application/vnd.github+json", "Authorization": f'Bearer {token}'}

    # The id of a workflow (not of a workflow run)
    snake_case_ :    Optional[int]     			=						"636036"

    snake_case_ :    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}'

    snake_case_ :    Optional[int]     			=						requests.get(__SCREAMING_SNAKE_CASE,		headers=__SCREAMING_SNAKE_CASE       ).json()

    return result["workflow_runs"]

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    Optional[Any]     			=						get_daily_ci_runs(__SCREAMING_SNAKE_CASE       )
    snake_case_ :    int     			=						None
    for workflow_run in workflow_runs:
        if workflow_run["status"] == "completed":
            snake_case_ :    List[str]     			=						workflow_run["id"]
            break

    return workflow_run_id

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    List[Any]     			=						get_last_daily_ci_runs(__SCREAMING_SNAKE_CASE       )
    if workflow_run_id is not None:
        snake_case_ :    Any     			=						get_artifacts_links(worflow_run_id=__SCREAMING_SNAKE_CASE,		token=__SCREAMING_SNAKE_CASE       )
        for artifact_name in artifact_names:
            if artifact_name in artifacts_links:
                snake_case_ :    Any     			=						artifacts_links[artifact_name]
                download_artifact(
                    artifact_name=__SCREAMING_SNAKE_CASE,		artifact_url=__SCREAMING_SNAKE_CASE,		output_dir=__SCREAMING_SNAKE_CASE,		token=__SCREAMING_SNAKE_CASE       )


def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    get_last_daily_ci_artifacts(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )

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

    return results






'''simple docstring'''
import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


a_											=						logging.get_logger(__name__)






class    UpperCAmelCase_				:
 UpperCAmelCase_		    =						None


@experimental
def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    if ParallelBackendConfig.backend_name is None:
        return _map_with_multiprocessing_pool(
            __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )

    return _map_with_joblib(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    str     			=						num_proc if num_proc <= len(__SCREAMING_SNAKE_CASE       ) else len(__SCREAMING_SNAKE_CASE       )
    snake_case_ :    Optional[int]     			=						[]  # We organize the splits ourselve (contiguous splits)
    for index in range(__SCREAMING_SNAKE_CASE       ):
        snake_case_ :    List[str]     			=						len(__SCREAMING_SNAKE_CASE       ) // num_proc
        snake_case_ :    Optional[Any]     			=						len(__SCREAMING_SNAKE_CASE       ) % num_proc
        snake_case_ :    Optional[Any]     			=						div * index + min(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )
        snake_case_ :    Union[str, Any]     			=						start + div + (1 if index < mod else 0)
        split_kwds.append((function, iterable[start:end], types, index, disable_tqdm, desc)       )

    if len(__SCREAMING_SNAKE_CASE       ) != sum(len(i[1]       ) for i in split_kwds       ):
        raise ValueError(
            f'Error dividing inputs iterable among processes. '
            f'Total number of objects {len(__SCREAMING_SNAKE_CASE       )}, '
            f'length: {sum(len(i[1]       ) for i in split_kwds       )}'       )

    logger.info(
        f'Spawning {num_proc} processes for {len(__SCREAMING_SNAKE_CASE       )} objects in slices of {[len(i[1]       ) for i in split_kwds]}'       )
    snake_case_			, snake_case_ :    Tuple     			=						None, None
    if not disable_tqdm:
        snake_case_			, snake_case_ :    int     			=						(RLock(),), tqdm.set_lock
    with Pool(__SCREAMING_SNAKE_CASE,		initargs=__SCREAMING_SNAKE_CASE,		initializer=__SCREAMING_SNAKE_CASE       ) as pool:
        snake_case_ :    Union[str, Any]     			=						pool.map(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )
    logger.info(f'Finished {num_proc} processes'       )
    snake_case_ :    str     			=						[obj for proc_res in mapped for obj in proc_res]
    logger.info(f'Unpacked {len(__SCREAMING_SNAKE_CASE       )} objects'       )

    return mapped

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    import joblib

    with joblib.parallel_backend(ParallelBackendConfig.backend_name,		n_jobs=__SCREAMING_SNAKE_CASE       ):
        return joblib.Parallel()(
            joblib.delayed(__SCREAMING_SNAKE_CASE       )((function, obj, types, None, True, None)       ) for obj in iterable       )


@experimental
@contextlib.contextmanager
def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    Union[str, Any]     			=						backend_name

    if backend_name == "spark":
        from joblibspark import register_spark

        register_spark()

        # TODO: call create_cache_and_write_probe if "download" in steps
        # TODO: raise NotImplementedError when Dataset.map etc is called

    try:
        yield
    finally:
        snake_case_ :    Any     			=						None




