import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links





def 							UpperCAmelCase		(       lowercase				,     lowercase=7				):







				"""simple docstring"""



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

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

				__lowercase					     =				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}"

				__lowercase					     =				requests.get(__A				,     headers=__A				).json()

				return result["workflow_runs"]





def 							UpperCAmelCase		(       lowercase				):







				"""simple docstring"""



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

				return workflow_run_id





def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



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





def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



				get_last_daily_ci_artifacts(__A				,     __A				,     __A				)

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

				return results


from typing import TYPE_CHECKING

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


_lowerCamelCase      :					int					    =      {
    '''configuration_audio_spectrogram_transformer''': [
        '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ASTConfig''',
    ]
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase      :					Tuple					    =      [
       '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''ASTForAudioClassification''',
       '''ASTModel''',
       '''ASTPreTrainedModel''',
   ]

try:
   if not is_speech_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase      :					Optional[Any]					    =      ['''ASTFeatureExtractor''']

if TYPE_CHECKING:
   from .configuration_audio_spectrogram_transformer import (
       AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
       ASTConfig,
   )

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_audio_spectrogram_transformer import (
          AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          ASTForAudioClassification,
          ASTModel,
          ASTPreTrainedModel,
      )

   try:
      if not is_speech_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
   import sys

   _lowerCamelCase      :					Optional[int]					    =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


