




"""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 					A_    (  self  ):
							_lowerCamelCase     :			int    =    0
			def 					A_    (  self  ):
							_lowerCamelCase     :			Dict    =    AutoImageProcessor.from_pretrained('openai/clip-vit-base-patch32'  )
							self.assertIsInstance(__a  ,      __a  )
			def 					A_    (  self  ):
							with tempfile.TemporaryDirectory() as tmpdirname:
											_lowerCamelCase     :			Dict    =    Path(__a  ) / 'preprocessor_config.json'
											_lowerCamelCase     :			int    =    Path(__a  ) / 'config.json'
											json.dump(
											    {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}  ,      open(__a  ,      'w'  )  ,      )
											json.dump({'model_type': 'clip'}  ,      open(__a  ,      'w'  )  )

											_lowerCamelCase     :			List[str]    =    AutoImageProcessor.from_pretrained(__a  )
											self.assertIsInstance(__a  ,      __a  )
			def 					A_    (  self  ):
							# Ensure we can load the image processor from the feature extractor config
							with tempfile.TemporaryDirectory() as tmpdirname:
											_lowerCamelCase     :			Tuple    =    Path(__a  ) / 'preprocessor_config.json'
											_lowerCamelCase     :			List[Any]    =    Path(__a  ) / 'config.json'
											json.dump(
											    {'feature_extractor_type': 'CLIPFeatureExtractor', 'processor_class': 'CLIPProcessor'}  ,      open(__a  ,      'w'  )  ,      )
											json.dump({'model_type': 'clip'}  ,      open(__a  ,      'w'  )  )

											_lowerCamelCase     :			int    =    AutoImageProcessor.from_pretrained(__a  )
											self.assertIsInstance(__a  ,      __a  )
			def 					A_    (  self  ):
							with tempfile.TemporaryDirectory() as tmpdirname:
											_lowerCamelCase     :			Optional[Any]    =    CLIPConfig()

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

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

											config_dict.pop('image_processor_type'  )
											_lowerCamelCase     :			Union[str, Any]    =    CLIPImageProcessor(**__a  )

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

											_lowerCamelCase     :			Any    =    AutoImageProcessor.from_pretrained(__a  )

											# make sure private variable is not incorrectly saved
											_lowerCamelCase     :			Optional[Any]    =    json.loads(config.to_json_string()  )
											self.assertTrue('_processor_class' not in dict_as_saved  )

							self.assertIsInstance(__a  ,      __a  )
			def 					A_    (  self  ):
							with tempfile.TemporaryDirectory() as tmpdirname:
											_lowerCamelCase     :			List[Any]    =    Path(__a  ) / 'preprocessor_config.json'
											json.dump(
											    {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}  ,      open(__a  ,      'w'  )  ,      )

											_lowerCamelCase     :			Optional[Any]    =    AutoImageProcessor.from_pretrained(__a  )
											self.assertIsInstance(__a  ,      __a  )
			def 					A_    (  self  ):
							with self.assertRaisesRegex(
							    __a  ,      'clip-base is not a local folder and is not a valid model identifier'  ):
											_lowerCamelCase     :			Union[str, Any]    =    AutoImageProcessor.from_pretrained('clip-base'  )
			def 					A_    (  self  ):
							with self.assertRaisesRegex(
							    __a  ,      r'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'  ):
											_lowerCamelCase     :			str    =    AutoImageProcessor.from_pretrained(__a  ,      revision='aaaaaa'  )
			def 					A_    (  self  ):
							with self.assertRaisesRegex(
							    __a  ,      'hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'  ,      ):
											_lowerCamelCase     :			Optional[Any]    =    AutoImageProcessor.from_pretrained('hf-internal-testing/config-no-model'  )
			def 					A_    (  self  ):
							# If remote code is not set, we will time out when asking whether to load the model.
							with self.assertRaises(__a  ):
											_lowerCamelCase     :			Optional[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(__a  ):
											_lowerCamelCase     :			Optional[Any]    =    AutoImageProcessor.from_pretrained(
											    'hf-internal-testing/test_dynamic_image_processor'  ,      trust_remote_code=__a  )

							_lowerCamelCase     :			Dict    =    AutoImageProcessor.from_pretrained(
							    'hf-internal-testing/test_dynamic_image_processor'  ,      trust_remote_code=__a  )
							self.assertEqual(image_processor.__class__.__name__  ,      'NewImageProcessor'  )

							# Test image processor can be reloaded.
							with tempfile.TemporaryDirectory() as tmp_dir:
											image_processor.save_pretrained(__a  )
											_lowerCamelCase     :			List[str]    =    AutoImageProcessor.from_pretrained(__a  ,      trust_remote_code=__a  )
							self.assertEqual(reloaded_image_processor.__class__.__name__  ,      'NewImageProcessor'  )
			def 					A_    (  self  ):
							try:
											AutoConfig.register('custom'  ,      __a  )
											AutoImageProcessor.register(__a  ,      __a  )
											# Trying to register something existing in the Transformers library will raise an error
											with self.assertRaises(__a  ):
															AutoImageProcessor.register(__a  ,      __a  )

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

															_lowerCamelCase     :			List[Any]    =    CustomImageProcessor.from_pretrained(__a  )

											# 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(__a  )
															_lowerCamelCase     :			Union[str, Any]    =    AutoImageProcessor.from_pretrained(__a  )
															self.assertIsInstance(__a  ,      __a  )

							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 					A_    (  self  ):






							class lowerCAmelCase__	(     lowerCAmelCase__						):






										'''simple docstring'''



										lowerCamelCase__      =			True

							try:
											AutoConfig.register('custom'  ,      __a  )
											AutoImageProcessor.register(__a  ,      __a  )
											# If remote code is not set, the default is to use local
											_lowerCamelCase     :			Optional[Any]    =    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.
											_lowerCamelCase     :			str    =    AutoImageProcessor.from_pretrained(
											    'hf-internal-testing/test_dynamic_image_processor'  ,      trust_remote_code=__a  )
											self.assertEqual(image_processor.__class__.__name__  ,      'NewImageProcessor'  )
											self.assertTrue(image_processor.is_local  )

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


class   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							pass
class   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							pass
class   _UpperCamelCase  :
							'''simple docstring'''







							def __init__(     self	):
										__lowerCAmelCase				    =			[
										    [],
										    [],
										    [],
										]

							def 			snake_case				(     self    ,   __a    ,   __a	):
										try:
													if len(self.queues[priority]	) >= 1_00:
																raise OverflowError("Maximum queue size is 100"	)
													self.queues[priority].append(__a	)
										except IndexError:
													raise ValueError("Valid priorities are 0, 1, and 2"	)

							def 			snake_case				(     self	):
										for queue in self.queues:
													if queue:
																return queue.pop(0	)
										raise UnderFlowError("All queues are empty"	)



							def __str__(     self	):
										return "\n".join(f"Priority {i}: {q}" for i, q in enumerate(self.queues	)	)
class   _UpperCamelCase  :
							'''simple docstring'''







							def __init__(     self	):
										__lowerCAmelCase				    =			[]

							def 			snake_case				(     self    ,   __a	):
										if len(self.queue	) == 1_00:
													raise OverFlowError("Maximum queue size is 100"	)
										self.queue.append(__a	)

							def 			snake_case				(     self	):
										if not self.queue:
													raise UnderFlowError("The queue is empty"	)
										else:
													__lowerCAmelCase				    =			min(self.queue	)
													self.queue.remove(__a	)
													return data



							def __str__(     self	):
										return str(self.queue	)


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			FixedPriorityQueue()
			fpq.enqueue(0    , 10      )
			fpq.enqueue(1    , 70      )
			fpq.enqueue(0    , 100      )
			fpq.enqueue(2    , 1      )
			fpq.enqueue(2    , 5      )
			fpq.enqueue(1    , 7      )
			fpq.enqueue(2    , 4      )
			fpq.enqueue(1    , 64      )
			fpq.enqueue(0    , 128      )
			print(_UpperCamelCase      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(_UpperCamelCase      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			ElementPriorityQueue()
			epq.enqueue(10      )
			epq.enqueue(70      )
			epq.enqueue(100      )
			epq.enqueue(1      )
			epq.enqueue(5      )
			epq.enqueue(7      )
			epq.enqueue(4      )
			epq.enqueue(64      )
			epq.enqueue(128      )
			print(_UpperCamelCase      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(_UpperCamelCase      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )


if __name__ == "__main__":
	fixed_priority_queue()
	element_priority_queue()




