

import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__=7				):







							'''simple docstring'''






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

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

							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}'''

							snake_case_          =   requests.get(UpperCamelCase__       ,							headers=UpperCamelCase__				).json()

							return result["workflow_runs"]





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






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

							return workflow_run_id





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






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





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							get_last_daily_ci_artifacts(UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				)

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

							return results







from typing import TYPE_CHECKING

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


_UpperCAmelCase		:       Dict						    =	{
    """configuration_blip""": [
        """BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BlipConfig""",
        """BlipTextConfig""",
        """BlipVisionConfig""",
    ],
    """processing_blip""": ["""BlipProcessor"""],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:       Optional[int]						    =	["""BlipImageProcessor"""]


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:       Any						    =	[
					    """BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """BlipModel""",
					    """BlipPreTrainedModel""",
					    """BlipForConditionalGeneration""",
					    """BlipForQuestionAnswering""",
					    """BlipVisionModel""",
					    """BlipTextModel""",
					    """BlipForImageTextRetrieval""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:       Any						    =	[
					    """TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFBlipModel""",
					    """TFBlipPreTrainedModel""",
					    """TFBlipForConditionalGeneration""",
					    """TFBlipForQuestionAnswering""",
					    """TFBlipVisionModel""",
					    """TFBlipTextModel""",
					    """TFBlipForImageTextRetrieval""",
					]

if TYPE_CHECKING:
					from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
					from .processing_blip import BlipProcessor

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_blip import BlipImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_blip import (
										    BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BlipForConditionalGeneration,
										    BlipForImageTextRetrieval,
										    BlipForQuestionAnswering,
										    BlipModel,
										    BlipPreTrainedModel,
										    BlipTextModel,
										    BlipVisionModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_blip import (
										    TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFBlipForConditionalGeneration,
										    TFBlipForImageTextRetrieval,
										    TFBlipForQuestionAnswering,
										    TFBlipModel,
										    TFBlipPreTrainedModel,
										    TFBlipTextModel,
										    TFBlipVisionModel,
										)

else:
					import sys

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




