



"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCAmelCase    : Optional[Any]							=							{
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase    : List[str]							=							["LxmertTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase    : int							=							[
     "LxmertEncoder",
     "LxmertForPreTraining",
     "LxmertForQuestionAnswering",
     "LxmertModel",
     "LxmertPreTrainedModel",
     "LxmertVisualFeatureEncoder",
     "LxmertXLayer",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase    : Optional[Any]							=							[
     "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TFLxmertForPreTraining",
     "TFLxmertMainLayer",
     "TFLxmertModel",
     "TFLxmertPreTrainedModel",
     "TFLxmertVisualFeatureEncoder",
 ]


if TYPE_CHECKING:
 from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
 from .tokenization_lxmert import LxmertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_lxmert_fast import LxmertTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_lxmert import (
      LxmertEncoder,
      LxmertForPreTraining,
      LxmertForQuestionAnswering,
      LxmertModel,
      LxmertPreTrainedModel,
      LxmertVisualFeatureEncoder,
      LxmertXLayer,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_lxmert import (
      TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFLxmertForPreTraining,
      TFLxmertMainLayer,
      TFLxmertModel,
      TFLxmertPreTrainedModel,
      TFLxmertVisualFeatureEncoder,
  )

else:
 import sys

 _lowerCAmelCase    : Optional[Any]							=							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





"""simple docstring"""




import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links

def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						Tuple						,  SCREAMING_SNAKE_CASE__     :						List[str]=7    )  ->       Tuple:





     '''simple docstring'''

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

     # The id of a workflow (not of a workflow run)
     _UpperCAmelCase      :     Any        =   "636036"

     _UpperCAmelCase      :     Dict        =   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}'

     _UpperCAmelCase      :     Tuple        =   requests.get(SCREAMING_SNAKE_CASE__						,  headers=SCREAMING_SNAKE_CASE__    ).json()

     return result["workflow_runs"]

def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						Union[str, Any]    )  ->       Optional[int]:





     '''simple docstring'''

     _UpperCAmelCase      :     int        =   get_daily_ci_runs(SCREAMING_SNAKE_CASE__    )
     _UpperCAmelCase      :     Optional[int]        =   None
     for workflow_run in workflow_runs:
          if workflow_run["status"] == "completed":
               _UpperCAmelCase      :     str        =   workflow_run["id"]
               break

     return workflow_run_id

def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						Dict						,  SCREAMING_SNAKE_CASE__     :						str						,  SCREAMING_SNAKE_CASE__     :						Union[str, Any]    )  ->       List[str]:





     '''simple docstring'''

     _UpperCAmelCase      :     List[str]        =   get_last_daily_ci_runs(SCREAMING_SNAKE_CASE__    )
     if workflow_run_id is not None:
          _UpperCAmelCase      :     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:
                    _UpperCAmelCase      :     List[str]        =   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 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						Tuple						,  SCREAMING_SNAKE_CASE__     :						Dict						,  SCREAMING_SNAKE_CASE__     :						Union[str, Any]    )  ->       Union[str, Any]:





     '''simple docstring'''

     get_last_daily_ci_artifacts(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__    )

     _UpperCAmelCase      :     Any        =   {}
     for artifact_name in artifact_names:
          _UpperCAmelCase      :     Dict        =   os.path.join(SCREAMING_SNAKE_CASE__						,  f'{artifact_name}.zip'    )
          if os.path.isfile(SCREAMING_SNAKE_CASE__    ):
               _UpperCAmelCase      :     str        =   {}
               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:
                                   _UpperCAmelCase      :     List[str]        =   f.read().decode("UTF-8"    )

     return results
