



import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


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

from test_module.custom_image_processing import CustomImageProcessor  # noqa E402


UpperCAmelCase_							:      Optional[Any]      =  get_tests_dir("fixtures")






class      UpperCamelCase    (						unittest.TestCase     ):



	def 			__A							(       self		):
							# A mock response for an HTTP head request to emulate server down
							A__							=       mock.Mock()
							A__							=       500
							A__							=       {}
							A__							=       HTTPError
							A__							=       {}

							# Download this model to make sure it's in the cache.
							A__							=       ViTImageProcessor.from_pretrained("hf-internal-testing/tiny-random-vit"		)
							# Under the mock environment we get a 500 error when trying to reach the model.
							with mock.patch("requests.Session.request"			,	return_value=_UpperCamelCase		) as mock_head:
													A__							=       ViTImageProcessor.from_pretrained("hf-internal-testing/tiny-random-vit"		)
													# This check we did call the fake head request
													mock_head.assert_called()



	def 			__A							(       self		):
							# This test is for deprecated behavior and can be removed in v5
							A__							=       ViTImageProcessor.from_pretrained(
							    "https://huggingface.co/hf-internal-testing/tiny-random-vit/resolve/main/preprocessor_config.json"		)



	def 			__A							(       self		):
							with self.assertRaises(_UpperCamelCase		):
													# config is in subfolder, the following should not work without specifying the subfolder
													A__							=       AutoImageProcessor.from_pretrained("hf-internal-testing/stable-diffusion-all-variants"		)

							A__							=       AutoImageProcessor.from_pretrained(
							    "hf-internal-testing/stable-diffusion-all-variants"			,	subfolder="feature_extractor"		)

							self.assertIsNotNone(_UpperCamelCase		)






@is_staging_test
class      UpperCamelCase    (						unittest.TestCase     ):



	@classmethod
	def 			__A							(       cls		):
							A__							=       TOKEN
							HfFolder.save_token(_UpperCamelCase		)



	@classmethod
	def 			__A							(       cls		):
							try:
													delete_repo(token=cls._token			,	repo_id="test-image-processor"		)
							except HTTPError:
													pass

							try:
													delete_repo(token=cls._token			,	repo_id="valid_org/test-image-processor-org"		)
							except HTTPError:
													pass

							try:
													delete_repo(token=cls._token			,	repo_id="test-dynamic-image-processor"		)
							except HTTPError:
													pass



	def 			__A							(       self		):
							A__							=       ViTImageProcessor.from_pretrained(_UpperCamelCase		)
							image_processor.push_to_hub("test-image-processor"			,	use_auth_token=self._token		)

							A__							=       ViTImageProcessor.from_pretrained(F"""{USER}/test-image-processor"""		)
							for k, v in image_processor.__dict__.items():
													self.assertEqual(_UpperCamelCase			,	getattr(_UpperCamelCase			,	_UpperCamelCase		)		)

							# Reset repo
							delete_repo(token=self._token			,	repo_id="test-image-processor"		)

							# Push to hub via save_pretrained
							with tempfile.TemporaryDirectory() as tmp_dir:
													image_processor.save_pretrained(
													    _UpperCamelCase			,	repo_id="test-image-processor"			,	push_to_hub=_UpperCamelCase			,	use_auth_token=self._token		)

							A__							=       ViTImageProcessor.from_pretrained(F"""{USER}/test-image-processor"""		)
							for k, v in image_processor.__dict__.items():
													self.assertEqual(_UpperCamelCase			,	getattr(_UpperCamelCase			,	_UpperCamelCase		)		)



	def 			__A							(       self		):
							A__							=       ViTImageProcessor.from_pretrained(_UpperCamelCase		)
							image_processor.push_to_hub("valid_org/test-image-processor"			,	use_auth_token=self._token		)

							A__							=       ViTImageProcessor.from_pretrained("valid_org/test-image-processor"		)
							for k, v in image_processor.__dict__.items():
													self.assertEqual(_UpperCamelCase			,	getattr(_UpperCamelCase			,	_UpperCamelCase		)		)

							# Reset repo
							delete_repo(token=self._token			,	repo_id="valid_org/test-image-processor"		)

							# Push to hub via save_pretrained
							with tempfile.TemporaryDirectory() as tmp_dir:
													image_processor.save_pretrained(
													    _UpperCamelCase			,	repo_id="valid_org/test-image-processor-org"			,	push_to_hub=_UpperCamelCase			,	use_auth_token=self._token		)

							A__							=       ViTImageProcessor.from_pretrained("valid_org/test-image-processor-org"		)
							for k, v in image_processor.__dict__.items():
													self.assertEqual(_UpperCamelCase			,	getattr(_UpperCamelCase			,	_UpperCamelCase		)		)



	def 			__A							(       self		):
							CustomImageProcessor.register_for_auto_class()
							A__							=       CustomImageProcessor.from_pretrained(_UpperCamelCase		)

							image_processor.push_to_hub("test-dynamic-image-processor"			,	use_auth_token=self._token		)

							# This has added the proper auto_map field to the config
							self.assertDictEqual(
							    image_processor.auto_map			,	{"AutoImageProcessor": "custom_image_processing.CustomImageProcessor"}			,	)

							A__							=       AutoImageProcessor.from_pretrained(
							    F"""{USER}/test-dynamic-image-processor"""			,	trust_remote_code=_UpperCamelCase		)
							# Can't make an isinstance check because the new_image_processor is from the CustomImageProcessor class of a dynamic module
							self.assertEqual(new_image_processor.__class__.__name__			,	"CustomImageProcessor"		)










def  UpperCamelCase						(       _A			:				str			,							_A			:				str    )->       str:





						"""simple docstring"""





						A__							=       len(_A    )
						A__							=       len(_A    )
						A__							=       (
						    first_str_length if first_str_length > second_str_length else second_str_length
						)
						A__							=       []
						for char_count in range(_A    ):
												if char_count < first_str_length:
																		output_list.append(first_str[char_count]    )
												if char_count < second_str_length:
																		output_list.append(second_str[char_count]    )
						return "".join(_A    )


if __name__ == "__main__":
						print(alternative_string_arrange("AB", "XYZ"), end=" ")





