



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 				snake_case__(unittest.TestCase      ):

					"""simple docstring"""






					def 			snake_case					(							self :     List[Any]					):
									lowercase__					:   Optional[Any]													=					0







					def 			snake_case					(							self :     Any					):
									lowercase__					:   List[Any]													=					AutoImageProcessor.from_pretrained("openai/clip-vit-base-patch32"					)
									self.assertIsInstance(SCREAMING_SNAKE_CASE				,       SCREAMING_SNAKE_CASE					)







					def 			snake_case					(							self :     Optional[int]					):
									with tempfile.TemporaryDirectory() as tmpdirname:
													lowercase__					:   str													=					Path(SCREAMING_SNAKE_CASE					) / "preprocessor_config.json"
													lowercase__					:   int													=					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"					)					)

													lowercase__					:   Any													=					AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE					)
													self.assertIsInstance(SCREAMING_SNAKE_CASE				,       SCREAMING_SNAKE_CASE					)







					def 			snake_case					(							self :     List[Any]					):
									# Ensure we can load the image processor from the feature extractor config
									with tempfile.TemporaryDirectory() as tmpdirname:
													lowercase__					:   Optional[Any]													=					Path(SCREAMING_SNAKE_CASE					) / "preprocessor_config.json"
													lowercase__					:   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"					)					)

													lowercase__					:   Any													=					AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE					)
													self.assertIsInstance(SCREAMING_SNAKE_CASE				,       SCREAMING_SNAKE_CASE					)







					def 			snake_case					(							self :     List[str]					):
									with tempfile.TemporaryDirectory() as tmpdirname:
													lowercase__					:   Optional[Any]													=					CLIPConfig()

													# Create a dummy config file with image_proceesor_type
													lowercase__					:   int													=					Path(SCREAMING_SNAKE_CASE					) / "preprocessor_config.json"
													lowercase__					:   List[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
													lowercase__					:   List[str]													=					AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE					).to_dict()

													config_dict.pop("image_processor_type"					)
													lowercase__					:   str													=					CLIPImageProcessor(**SCREAMING_SNAKE_CASE					)

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

													lowercase__					:   Any													=					AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE					)

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

									self.assertIsInstance(SCREAMING_SNAKE_CASE				,       SCREAMING_SNAKE_CASE					)







					def 			snake_case					(							self :     Dict					):
									with tempfile.TemporaryDirectory() as tmpdirname:
													lowercase__					:   Optional[Any]													=					Path(SCREAMING_SNAKE_CASE					) / "preprocessor_config.json"
													json.dump(
													    {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}				,       open(SCREAMING_SNAKE_CASE				,       "w"					)				,       )

													lowercase__					:   List[str]													=					AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE					)
													self.assertIsInstance(SCREAMING_SNAKE_CASE				,       SCREAMING_SNAKE_CASE					)







					def 			snake_case					(							self :     List[Any]					):
									with self.assertRaisesRegex(
									    SCREAMING_SNAKE_CASE				,       "clip-base is not a local folder and is not a valid model identifier"					):
													lowercase__					:   List[str]													=					AutoImageProcessor.from_pretrained("clip-base"					)







					def 			snake_case					(							self :     Any					):
									with self.assertRaisesRegex(
									    SCREAMING_SNAKE_CASE				,       r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"					):
													lowercase__					:   Optional[int]													=					AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE				,       revision="aaaaaa"					)







					def 			snake_case					(							self :     Any					):
									with self.assertRaisesRegex(
									    SCREAMING_SNAKE_CASE				,       "hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."				,       ):
													lowercase__					:   Any													=					AutoImageProcessor.from_pretrained("hf-internal-testing/config-no-model"					)







					def 			snake_case					(							self :     List[Any]					):
									# If remote code is not set, we will time out when asking whether to load the model.
									with self.assertRaises(SCREAMING_SNAKE_CASE					):
													lowercase__					:   Union[str, Any]													=					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					):
													lowercase__					:   List[str]													=					AutoImageProcessor.from_pretrained(
													    "hf-internal-testing/test_dynamic_image_processor"				,       trust_remote_code=SCREAMING_SNAKE_CASE					)

									lowercase__					:   str													=					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					)
													lowercase__					:   List[str]													=					AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE				,       trust_remote_code=SCREAMING_SNAKE_CASE					)
									self.assertEqual(reloaded_image_processor.__class__.__name__				,       "NewImageProcessor"					)







					def 			snake_case					(							self :     int					):
									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:
																	lowercase__					:   int													=					Path(SCREAMING_SNAKE_CASE					) / "preprocessor_config.json"
																	lowercase__					:   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"					)					)

																	lowercase__					:   List[Any]													=					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					)
																	lowercase__					:   Any													=					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 			snake_case					(							self :     List[Any]					):

									class 				snake_case__(_UpperCamelCase      ):

														"""simple docstring"""






														lowercase_								=		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
													lowercase__					:   Tuple													=					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.
													lowercase__					:   int													=					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
													lowercase__					:   Union[str, Any]													=					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]









def  __lowerCamelCase (       lowerCamelCase__ = 1_000						):

				"""simple docstring"""


				lowercase__							,							lowercase__					:   int													=					1, 1
				lowercase__					:   List[Any]													=					[]
				for i in range(1					,			n + 1						):
								lowercase__					:   Dict													=					prev_numerator + 2 * prev_denominator
								lowercase__					:   Tuple													=					prev_numerator + prev_denominator
								if len(str(lowerCamelCase__						)						) > len(str(lowerCamelCase__						)						):
												result.append(lowerCamelCase__						)
								lowercase__					:   int													=					numerator
								lowercase__					:   int													=					denominator

				return len(lowerCamelCase__						)


if __name__ == "__main__":
				print(f'''{solution() = }''')




