
"""simple docstring"""




import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


sys.path.append(str(Path(__file__).parent.parent.parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402



class 			lowerCAmelCase_		(unittest.TestCase						):


				"""simple docstring"""



				def 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Optional[int]     =     0



				def 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Any     =     AutoImageProcessor.from_pretrained("""openai/clip-vit-base-patch32"""					)
											self.assertIsInstance(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)



				def 			__magic_name__					(self					)      ->	List[str]:



											"""simple docstring"""




											with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     Path(SCREAMING_SNAKE_CASE__					) / """preprocessor_config.json"""
																		SCREAMING_SNAKE_CASE__		: str     =     Path(SCREAMING_SNAKE_CASE__					) / """config.json"""
																		json.dump(
																		    {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}     , open(SCREAMING_SNAKE_CASE__     , """w"""					)     , )
																		json.dump({"""model_type""": """clip"""}     , open(SCREAMING_SNAKE_CASE__     , """w"""					)					)

																		SCREAMING_SNAKE_CASE__		: Optional[int]     =     AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__					)
																		self.assertIsInstance(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)



				def 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




											with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE__		: Optional[Any]     =     Path(SCREAMING_SNAKE_CASE__					) / """preprocessor_config.json"""
																		SCREAMING_SNAKE_CASE__		: Tuple     =     Path(SCREAMING_SNAKE_CASE__					) / """config.json"""
																		json.dump(
																		    {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}     , open(SCREAMING_SNAKE_CASE__     , """w"""					)     , )
																		json.dump({"""model_type""": """clip"""}     , open(SCREAMING_SNAKE_CASE__     , """w"""					)					)

																		SCREAMING_SNAKE_CASE__		: Optional[int]     =     AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__					)
																		self.assertIsInstance(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)



				def 			__magic_name__					(self					)      ->	Union[str, Any]:



											"""simple docstring"""




											with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE__		: Optional[Any]     =     CLIPConfig()

																		# Create a dummy config file with image_proceesor_type
																		SCREAMING_SNAKE_CASE__		: List[Any]     =     Path(SCREAMING_SNAKE_CASE__					) / """preprocessor_config.json"""
																		SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     Path(SCREAMING_SNAKE_CASE__					) / """config.json"""
																		json.dump(
																		    {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}     , open(SCREAMING_SNAKE_CASE__     , """w"""					)     , )
																		json.dump({"""model_type""": """clip"""}     , open(SCREAMING_SNAKE_CASE__     , """w"""					)					)

																		# remove image_processor_type to make sure config.json alone is enough to load image processor locally
																		SCREAMING_SNAKE_CASE__		: Dict     =     AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__					).to_dict()

																		config_dict.pop("""image_processor_type"""					)
																		SCREAMING_SNAKE_CASE__		: List[Any]     =     CLIPImageProcessor(**SCREAMING_SNAKE_CASE__					)

																		# save in new folder
																		model_config.save_pretrained(SCREAMING_SNAKE_CASE__					)
																		config.save_pretrained(SCREAMING_SNAKE_CASE__					)

																		SCREAMING_SNAKE_CASE__		: Tuple     =     AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__					)

																		# make sure private variable is not incorrectly saved
																		SCREAMING_SNAKE_CASE__		: str     =     json.loads(config.to_json_string()					)
																		self.assertTrue("""_processor_class""" not in dict_as_saved					)

											self.assertIsInstance(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)



				def 			__magic_name__					(self					)      ->	Tuple:



											"""simple docstring"""




											with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE__		: Tuple     =     Path(SCREAMING_SNAKE_CASE__					) / """preprocessor_config.json"""
																		json.dump(
																		    {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}     , open(SCREAMING_SNAKE_CASE__     , """w"""					)     , )

																		SCREAMING_SNAKE_CASE__		: Any     =     AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__					)
																		self.assertIsInstance(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)



				def 			__magic_name__					(self					)      ->	Union[str, Any]:



											"""simple docstring"""




											with self.assertRaisesRegex(
											    SCREAMING_SNAKE_CASE__     , """clip-base is not a local folder and is not a valid model identifier"""					):
																		SCREAMING_SNAKE_CASE__		: Any     =     AutoImageProcessor.from_pretrained("""clip-base"""					)



				def 			__magic_name__					(self					)      ->	Optional[Any]:



											"""simple docstring"""




											with self.assertRaisesRegex(
											    SCREAMING_SNAKE_CASE__     , r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""					):
																		SCREAMING_SNAKE_CASE__		: Dict     =     AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__     , revision="""aaaaaa"""					)



				def 			__magic_name__					(self					)      ->	Union[str, Any]:



											"""simple docstring"""




											with self.assertRaisesRegex(
											    SCREAMING_SNAKE_CASE__     , """hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."""     , ):
																		SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     AutoImageProcessor.from_pretrained("""hf-internal-testing/config-no-model"""					)



				def 			__magic_name__					(self					)      ->	List[Any]:



											"""simple docstring"""




											with self.assertRaises(SCREAMING_SNAKE_CASE__					):
																		SCREAMING_SNAKE_CASE__		: int     =     AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""					)
											# If remote code is disabled, we can't load this config.
											with self.assertRaises(SCREAMING_SNAKE_CASE__					):
																		SCREAMING_SNAKE_CASE__		: int     =     AutoImageProcessor.from_pretrained(
																		    """hf-internal-testing/test_dynamic_image_processor"""     , trust_remote_code=SCREAMING_SNAKE_CASE__					)

											SCREAMING_SNAKE_CASE__		: Tuple     =     AutoImageProcessor.from_pretrained(
											    """hf-internal-testing/test_dynamic_image_processor"""     , trust_remote_code=SCREAMING_SNAKE_CASE__					)
											self.assertEqual(image_processor.__class__.__name__     , """NewImageProcessor"""					)

											# Test image processor can be reloaded.
											with tempfile.TemporaryDirectory() as tmp_dir:
																		image_processor.save_pretrained(SCREAMING_SNAKE_CASE__					)
																		SCREAMING_SNAKE_CASE__		: str     =     AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__     , trust_remote_code=SCREAMING_SNAKE_CASE__					)
											self.assertEqual(reloaded_image_processor.__class__.__name__     , """NewImageProcessor"""					)



				def 			__magic_name__					(self					)      ->	Optional[int]:



											"""simple docstring"""




											try:
																		AutoConfig.register("""custom"""     , SCREAMING_SNAKE_CASE__					)
																		AutoImageProcessor.register(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)
																		# Trying to register something existing in the Transformers library will raise an error
																		with self.assertRaises(SCREAMING_SNAKE_CASE__					):
																									AutoImageProcessor.register(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)

																		with tempfile.TemporaryDirectory() as tmpdirname:
																									SCREAMING_SNAKE_CASE__		: List[str]     =     Path(SCREAMING_SNAKE_CASE__					) / """preprocessor_config.json"""
																									SCREAMING_SNAKE_CASE__		: str     =     Path(SCREAMING_SNAKE_CASE__					) / """config.json"""
																									json.dump(
																									    {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}     , open(SCREAMING_SNAKE_CASE__     , """w"""					)     , )
																									json.dump({"""model_type""": """clip"""}     , open(SCREAMING_SNAKE_CASE__     , """w"""					)					)

																									SCREAMING_SNAKE_CASE__		: Dict     =     CustomImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__					)

																		# Now that the config is registered, it can be used as any other config with the auto-API
																		with tempfile.TemporaryDirectory() as tmp_dir:
																									image_processor.save_pretrained(SCREAMING_SNAKE_CASE__					)
																									SCREAMING_SNAKE_CASE__		: Tuple     =     AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__					)
																									self.assertIsInstance(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)

											finally:
																		if "custom" in CONFIG_MAPPING._extra_content:
																									del CONFIG_MAPPING._extra_content["custom"]
																		if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
																									del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]



				def 			__magic_name__					(self					)      ->	Optional[int]:



											"""simple docstring"""




											class 			lowerCAmelCase_		(a__						):


															"""simple docstring"""



															__UpperCamelCase   :		Union[str, Any]       =     True

											try:
																		AutoConfig.register("""custom"""     , SCREAMING_SNAKE_CASE__					)
																		AutoImageProcessor.register(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)
																		# If remote code is not set, the default is to use local
																		SCREAMING_SNAKE_CASE__		: str     =     AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""					)
																		self.assertEqual(image_processor.__class__.__name__     , """NewImageProcessor"""					)
																		self.assertTrue(image_processor.is_local					)

																		# If remote code is disabled, we load the local one.
																		SCREAMING_SNAKE_CASE__		: Dict     =     AutoImageProcessor.from_pretrained(
																		    """hf-internal-testing/test_dynamic_image_processor"""     , trust_remote_code=SCREAMING_SNAKE_CASE__					)
																		self.assertEqual(image_processor.__class__.__name__     , """NewImageProcessor"""					)
																		self.assertTrue(image_processor.is_local					)

																		# If remote is enabled, we load from the Hub
																		SCREAMING_SNAKE_CASE__		: Dict     =     AutoImageProcessor.from_pretrained(
																		    """hf-internal-testing/test_dynamic_image_processor"""     , trust_remote_code=SCREAMING_SNAKE_CASE__					)
																		self.assertEqual(image_processor.__class__.__name__     , """NewImageProcessor"""					)
																		self.assertTrue(not hasattr(SCREAMING_SNAKE_CASE__     , """is_local"""					)					)

											finally:
																		if "custom" in CONFIG_MAPPING._extra_content:
																									del CONFIG_MAPPING._extra_content["custom"]
																		if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
																									del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]






"""simple docstring"""




import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links

def lowercase_						(     _snake_case     ,_snake_case=7		):
							SCREAMING_SNAKE_CASE__		: Dict     =     None
							if token is not None:
														SCREAMING_SNAKE_CASE__		: str     =     {"""Accept""": """application/vnd.github+json""", """Authorization""": f'''Bearer {token}'''}

							# The id of a workflow (not of a workflow run)
							SCREAMING_SNAKE_CASE__		: List[str]     =     """636036"""

							SCREAMING_SNAKE_CASE__		: Any     =     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__		: str     =     requests.get(_snake_case     ,headers=_snake_case		).json()

							return result["workflow_runs"]

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

							return workflow_run_id

def lowercase_						(     _snake_case     ,_snake_case     ,_snake_case		):
							SCREAMING_SNAKE_CASE__		: Dict     =     get_last_daily_ci_runs(_snake_case		)
							if workflow_run_id is not None:
														SCREAMING_SNAKE_CASE__		: Tuple     =     get_artifacts_links(worflow_run_id=_snake_case     ,token=_snake_case		)
														for artifact_name in artifact_names:
																					if artifact_name in artifacts_links:
																												SCREAMING_SNAKE_CASE__		: Tuple     =     artifacts_links[artifact_name]
																												download_artifact(
																												    artifact_name=_snake_case     ,artifact_url=_snake_case     ,output_dir=_snake_case     ,token=_snake_case		)

def lowercase_						(     _snake_case     ,_snake_case     ,_snake_case		):
							get_last_daily_ci_artifacts(_snake_case     ,_snake_case     ,_snake_case		)

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

							return results




