





"""simple docstring"""


from typing import TYPE_CHECKING

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


lowerCamelCase__				  =   {
    "configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
    "tokenization_xlm": ["XLMTokenizer"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase__				  =   [
      "XLM_PRETRAINED_MODEL_ARCHIVE_LIST",
      "XLMForMultipleChoice",
      "XLMForQuestionAnswering",
      "XLMForQuestionAnsweringSimple",
      "XLMForSequenceClassification",
      "XLMForTokenClassification",
      "XLMModel",
      "XLMPreTrainedModel",
      "XLMWithLMHeadModel",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase__				  =   [
      "TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST",
      "TFXLMForMultipleChoice",
      "TFXLMForQuestionAnsweringSimple",
      "TFXLMForSequenceClassification",
      "TFXLMForTokenClassification",
      "TFXLMMainLayer",
      "TFXLMModel",
      "TFXLMPreTrainedModel",
      "TFXLMWithLMHeadModel",
  ]


if TYPE_CHECKING:
  from .configuration_xlm import XLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMConfig, XLMOnnxConfig
  from .tokenization_xlm import XLMTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_xlm import (
        XLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        XLMForMultipleChoice,
        XLMForQuestionAnswering,
        XLMForQuestionAnsweringSimple,
        XLMForSequenceClassification,
        XLMForTokenClassification,
        XLMModel,
        XLMPreTrainedModel,
        XLMWithLMHeadModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_xlm import (
        TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFXLMForMultipleChoice,
        TFXLMForQuestionAnsweringSimple,
        TFXLMForSequenceClassification,
        TFXLMForTokenClassification,
        TFXLMMainLayer,
        TFXLMModel,
        TFXLMPreTrainedModel,
        TFXLMWithLMHeadModel,
    )

else:
  import sys

  lowerCamelCase__				  =   _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 					lowercase__    (					lowercase_		,lowercase_=7			)					->		Tuple:




      """simple docstring"""

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

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

      _UpperCamelCase      :	Tuple						=       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      :	Dict						=       requests.get(lowercase_		,headers=lowercase_			).json()

      return result["workflow_runs"]




def 					lowercase__    (					lowercase_			)					->		List[str]:




      """simple docstring"""

      _UpperCamelCase      :	List[Any]						=       get_daily_ci_runs(lowercase_			)
      _UpperCamelCase      :	Tuple						=       None
      for workflow_run in workflow_runs:
            if workflow_run["status"] == "completed":
                  _UpperCamelCase      :	Union[str, Any]						=       workflow_run["id"]
                  break

      return workflow_run_id




def 					lowercase__    (					lowercase_		,lowercase_		,lowercase_			)					->		Optional[int]:




      """simple docstring"""

      _UpperCamelCase      :	str						=       get_last_daily_ci_runs(lowercase_			)
      if workflow_run_id is not None:
            _UpperCamelCase      :	int						=       get_artifacts_links(worflow_run_id=lowercase_		,token=lowercase_			)
            for artifact_name in artifact_names:
                  if artifact_name in artifacts_links:
                        _UpperCamelCase      :	Dict						=       artifacts_links[artifact_name]
                        download_artifact(
                            artifact_name=lowercase_		,artifact_url=lowercase_		,output_dir=lowercase_		,token=lowercase_			)




def 					lowercase__    (					lowercase_		,lowercase_		,lowercase_			)					->		int:




      """simple docstring"""

      get_last_daily_ci_artifacts(lowercase_		,lowercase_		,lowercase_			)

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

      return results
