



import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links





def 					__snake_case     (      _UpperCAmelCase       ,			_UpperCAmelCase=7    ):
    __a							=    None
    if token is not None:
        __a							=    {'''Accept''': '''application/vnd.github+json''', '''Authorization''': f'Bearer {token}'}

    # The id of a workflow (not of a workflow run)
    __a							=    '''636036'''

    __a							=    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}'

    __a							=    requests.get(_UpperCAmelCase       ,			headers=_UpperCAmelCase    ).json()

    return result["workflow_runs"]





def 					__snake_case     (      _UpperCAmelCase    ):
    __a							=    get_daily_ci_runs(_UpperCAmelCase    )
    __a							=    None
    for workflow_run in workflow_runs:
        if workflow_run["status"] == "completed":
            __a							=    workflow_run['''id''']
            break

    return workflow_run_id





def 					__snake_case     (      _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase    ):
    __a							=    get_last_daily_ci_runs(_UpperCAmelCase    )
    if workflow_run_id is not None:
        __a							=    get_artifacts_links(worflow_run_id=_UpperCAmelCase       ,			token=_UpperCAmelCase    )
        for artifact_name in artifact_names:
            if artifact_name in artifacts_links:
                __a							=    artifacts_links[artifact_name]
                download_artifact(
                    artifact_name=_UpperCAmelCase       ,			artifact_url=_UpperCAmelCase       ,			output_dir=_UpperCAmelCase       ,			token=_UpperCAmelCase    )





def 					__snake_case     (      _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase    ):
    get_last_daily_ci_artifacts(_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase    )

    __a							=    {}
    for artifact_name in artifact_names:
        __a							=    os.path.join(_UpperCAmelCase       ,			f'{artifact_name}.zip'    )
        if os.path.isfile(_UpperCAmelCase    ):
            __a							=    {}
            with zipfile.ZipFile(_UpperCAmelCase    ) as z:
                for filename in z.namelist():
                    if not os.path.isdir(_UpperCAmelCase    ):
                        # read the file
                        with z.open(_UpperCAmelCase    ) as f:
                            __a							=    f.read().decode('''UTF-8'''    )

    return results










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__snake_case						:Tuple						=					{
    '''configuration_bloom''': ['''BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BloomConfig''', '''BloomOnnxConfig'''],
}
try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __snake_case						:List[Any]						=					['''BloomTokenizerFast''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __snake_case						:Any						=					[
     '''BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''BloomForCausalLM''',
     '''BloomModel''',
     '''BloomPreTrainedModel''',
     '''BloomForSequenceClassification''',
     '''BloomForTokenClassification''',
     '''BloomForQuestionAnswering''',
 ]

if TYPE_CHECKING:
 from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_bloom_fast import BloomTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_bloom import (
      BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
      BloomForCausalLM,
      BloomForQuestionAnswering,
      BloomForSequenceClassification,
      BloomForTokenClassification,
      BloomModel,
      BloomPreTrainedModel,
  )

else:
 import sys

 __snake_case						:Any						=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





