





"""simple docstring"""


from ...processing_utils import ProcessorMixin



class      __SCREAMING_SNAKE_CASE    (						_UpperCamelCase   ):







		'''simple docstring'''


		SCREAMING_SNAKE_CASE__							:Union[str, Any]	     =					["image_processor", "feature_extractor"]
		SCREAMING_SNAKE_CASE__							:List[str]	     =					"TvltImageProcessor"
		SCREAMING_SNAKE_CASE__							:List[Any]	     =					"TvltFeatureExtractor"

		def __init__(		self   :       List[str]					,   __a   :       List[Any]					,   __a   :       List[str]	)		->				List[str]:
								super().__init__(image_processor=__A					,   feature_extractor=__A	)

								_UpperCamelCase      :	Optional[Any]						=       image_processor
								_UpperCamelCase      :	Any						=       feature_extractor

		def __call__(		self   :       List[str]					,   __a   :       Any=None					,   __a   :       Any=None					,   __a   :       Optional[int]=None					,   __a   :       str=None					,   __a   :       List[Any]=False					,   __a   :       Tuple=False					,   *__a   :       List[str]					,   **__a   :       Optional[Any]					,   )		->				Optional[Any]:

								if images is None and audio is None:
														raise ValueError("You need to specify either an `images` or `audio` input to process."	)

								_UpperCamelCase      :	int						=       None
								if images is not None:
														_UpperCamelCase      :	Optional[int]						=       self.image_processor(__A					,   mask_pixel=__A					,   *__A					,   **__A	)
								if images_mixed is not None:
														_UpperCamelCase      :	Optional[Any]						=       self.image_processor(__A					,   is_mixed=__A					,   *__A					,   **__A	)
								if audio is not None:
														_UpperCamelCase      :	Dict						=       self.feature_extractor(
														    __A					,   *__A					,   sampling_rate=__A					,   mask_audio=__A					,   **__A	)

								_UpperCamelCase      :	Optional[int]						=       {}
								if audio is not None:
														output_dict.update(__A	)
								if images is not None:
														output_dict.update(__A	)
								if images_mixed_dict is not None:
														output_dict.update(__A	)
								return output_dict


		@property
		def    __SCREAMING_SNAKE_CASE				(		self   :       Optional[Any]	)		->				int:
								_UpperCamelCase      :	Any						=       self.image_processor.model_input_names
								_UpperCamelCase      :	Tuple						=       self.feature_extractor.model_input_names
								return list(dict.fromkeys(image_processor_input_names + feature_extractor_input_names	)	)







"""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
