

from typing import TYPE_CHECKING

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


UpperCamelCase__  :      Optional[Any]			=    {"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLNetConfig"]}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      List[Any]			=    ["XLNetTokenizer"]

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      Any			=    ["XLNetTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      Optional[int]			=    [
           "XLNET_PRETRAINED_MODEL_ARCHIVE_LIST",
           "XLNetForMultipleChoice",
           "XLNetForQuestionAnswering",
           "XLNetForQuestionAnsweringSimple",
           "XLNetForSequenceClassification",
           "XLNetForTokenClassification",
           "XLNetLMHeadModel",
           "XLNetModel",
           "XLNetPreTrainedModel",
           "load_tf_weights_in_xlnet",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      Dict			=    [
           "TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFXLNetForMultipleChoice",
           "TFXLNetForQuestionAnsweringSimple",
           "TFXLNetForSequenceClassification",
           "TFXLNetForTokenClassification",
           "TFXLNetLMHeadModel",
           "TFXLNetMainLayer",
           "TFXLNetModel",
           "TFXLNetPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig

       try:
              if not is_sentencepiece_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_xlnet import XLNetTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_xlnet_fast import XLNetTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_xlnet import (
                  XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  XLNetForMultipleChoice,
                  XLNetForQuestionAnswering,
                  XLNetForQuestionAnsweringSimple,
                  XLNetForSequenceClassification,
                  XLNetForTokenClassification,
                  XLNetLMHeadModel,
                  XLNetModel,
                  XLNetPreTrainedModel,
                  load_tf_weights_in_xlnet,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_xlnet import (
                  TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFXLNetForMultipleChoice,
                  TFXLNetForQuestionAnsweringSimple,
                  TFXLNetForSequenceClassification,
                  TFXLNetForTokenClassification,
                  TFXLNetLMHeadModel,
                  TFXLNetMainLayer,
                  TFXLNetModel,
                  TFXLNetPreTrainedModel,
              )

else:
       import sys

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




import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		List[Any] ,   _SCREAMING_SNAKE_CASE					:		int=7       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						None
    if token is not None:
        SCREAMING_SNAKE_CASE_									=						{'Accept': 'application/vnd.github+json', 'Authorization': f"""Bearer {token}"""}

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

    SCREAMING_SNAKE_CASE_									=						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}"""

    SCREAMING_SNAKE_CASE_									=						requests.get(_SCREAMING_SNAKE_CASE ,   headers=_SCREAMING_SNAKE_CASE       ).json()

    return result["workflow_runs"]


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		str       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						get_daily_ci_runs(_SCREAMING_SNAKE_CASE       )
    SCREAMING_SNAKE_CASE_									=						None
    for workflow_run in workflow_runs:
        if workflow_run["status"] == "completed":
            SCREAMING_SNAKE_CASE_									=						workflow_run['id']
            break

    return workflow_run_id


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		int ,   _SCREAMING_SNAKE_CASE					:		str ,   _SCREAMING_SNAKE_CASE					:		Optional[int]       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						get_last_daily_ci_runs(_SCREAMING_SNAKE_CASE       )
    if workflow_run_id is not None:
        SCREAMING_SNAKE_CASE_									=						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:
                SCREAMING_SNAKE_CASE_									=						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					:		List[Any] ,   _SCREAMING_SNAKE_CASE					:		str ,   _SCREAMING_SNAKE_CASE					:		List[Any]       ):





    """simple docstring"""


    get_last_daily_ci_artifacts(_SCREAMING_SNAKE_CASE ,   _SCREAMING_SNAKE_CASE ,   _SCREAMING_SNAKE_CASE       )

    SCREAMING_SNAKE_CASE_									=						{}
    for artifact_name in artifact_names:
        SCREAMING_SNAKE_CASE_									=						os.path.join(_SCREAMING_SNAKE_CASE ,   f"""{artifact_name}.zip"""       )
        if os.path.isfile(_SCREAMING_SNAKE_CASE       ):
            SCREAMING_SNAKE_CASE_									=						{}
            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:
                            SCREAMING_SNAKE_CASE_									=						f.read().decode('UTF-8'       )

    return results


