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 					lowercase__						(   unittest.TestCase):


						def        __A       (       self	:				List[Any]						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    Dict							=							0


						def        __A       (       self	:				Dict						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    str							=							AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''						)
												self.assertIsInstance(UpperCamelCase__    ,		UpperCamelCase__						)


						def        __A       (       self	:				Dict						):





												'''simple docstring'''





												with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE							:    str							=							Path(UpperCamelCase__						) / '''preprocessor_config.json'''
																		SCREAMING_SNAKE_CASE							:    Dict							=							Path(UpperCamelCase__						) / '''config.json'''
																		json.dump(
																		    {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}    ,		open(UpperCamelCase__    ,		'''w'''						)    ,		)
																		json.dump({'''model_type''': '''clip'''}    ,		open(UpperCamelCase__    ,		'''w'''						)						)

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


						def        __A       (       self	:				int						):





												'''simple docstring'''





												with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE							:    Tuple							=							Path(UpperCamelCase__						) / '''preprocessor_config.json'''
																		SCREAMING_SNAKE_CASE							:    Dict							=							Path(UpperCamelCase__						) / '''config.json'''
																		json.dump(
																		    {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}    ,		open(UpperCamelCase__    ,		'''w'''						)    ,		)
																		json.dump({'''model_type''': '''clip'''}    ,		open(UpperCamelCase__    ,		'''w'''						)						)

																		SCREAMING_SNAKE_CASE							:    Optional[Any]							=							AutoImageProcessor.from_pretrained(UpperCamelCase__						)
																		self.assertIsInstance(UpperCamelCase__    ,		UpperCamelCase__						)


						def        __A       (       self	:				List[str]						):





												'''simple docstring'''





												with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE							:    Dict							=							CLIPConfig()

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

																		# remove image_processor_type to make sure config.json alone is enough to load image processor locally
																		SCREAMING_SNAKE_CASE							:    List[Any]							=							AutoImageProcessor.from_pretrained(UpperCamelCase__						).to_dict()

																		config_dict.pop('''image_processor_type'''						)
																		SCREAMING_SNAKE_CASE							:    str							=							CLIPImageProcessor(**UpperCamelCase__						)

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

																		SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							AutoImageProcessor.from_pretrained(UpperCamelCase__						)

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

												self.assertIsInstance(UpperCamelCase__    ,		UpperCamelCase__						)


						def        __A       (       self	:				Tuple						):





												'''simple docstring'''





												with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE							:    Optional[int]							=							Path(UpperCamelCase__						) / '''preprocessor_config.json'''
																		json.dump(
																		    {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}    ,		open(UpperCamelCase__    ,		'''w'''						)    ,		)

																		SCREAMING_SNAKE_CASE							:    Dict							=							AutoImageProcessor.from_pretrained(UpperCamelCase__						)
																		self.assertIsInstance(UpperCamelCase__    ,		UpperCamelCase__						)


						def        __A       (       self	:				int						):





												'''simple docstring'''





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


						def        __A       (       self	:				List[str]						):





												'''simple docstring'''





												with self.assertRaisesRegex(
												    UpperCamelCase__    ,		r'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''						):
																		SCREAMING_SNAKE_CASE							:    Tuple							=							AutoImageProcessor.from_pretrained(UpperCamelCase__    ,		revision='''aaaaaa'''						)


						def        __A       (       self	:				Dict						):





												'''simple docstring'''





												with self.assertRaisesRegex(
												    UpperCamelCase__    ,		'''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''    ,		):
																		SCREAMING_SNAKE_CASE							:    Dict							=							AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''						)


						def        __A       (       self	:				List[Any]						):





												'''simple docstring'''





												with self.assertRaises(UpperCamelCase__						):
																		SCREAMING_SNAKE_CASE							:    str							=							AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''						)
												# If remote code is disabled, we can't load this config.
												with self.assertRaises(UpperCamelCase__						):
																		SCREAMING_SNAKE_CASE							:    List[Any]							=							AutoImageProcessor.from_pretrained(
																		    '''hf-internal-testing/test_dynamic_image_processor'''    ,		trust_remote_code=UpperCamelCase__						)

												SCREAMING_SNAKE_CASE							:    List[Any]							=							AutoImageProcessor.from_pretrained(
												    '''hf-internal-testing/test_dynamic_image_processor'''    ,		trust_remote_code=UpperCamelCase__						)
												self.assertEqual(image_processor.__class__.__name__    ,		'''NewImageProcessor'''						)

												# Test image processor can be reloaded.
												with tempfile.TemporaryDirectory() as tmp_dir:
																		image_processor.save_pretrained(UpperCamelCase__						)
																		SCREAMING_SNAKE_CASE							:    Optional[int]							=							AutoImageProcessor.from_pretrained(UpperCamelCase__    ,		trust_remote_code=UpperCamelCase__						)
												self.assertEqual(reloaded_image_processor.__class__.__name__    ,		'''NewImageProcessor'''						)


						def        __A       (       self	:				Optional[Any]						):





												'''simple docstring'''





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

																		with tempfile.TemporaryDirectory() as tmpdirname:
																								SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							Path(UpperCamelCase__						) / '''preprocessor_config.json'''
																								SCREAMING_SNAKE_CASE							:    Any							=							Path(UpperCamelCase__						) / '''config.json'''
																								json.dump(
																								    {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}    ,		open(UpperCamelCase__    ,		'''w'''						)    ,		)
																								json.dump({'''model_type''': '''clip'''}    ,		open(UpperCamelCase__    ,		'''w'''						)						)

																								SCREAMING_SNAKE_CASE							:    Tuple							=							CustomImageProcessor.from_pretrained(UpperCamelCase__						)

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

												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	:				Any						):





												'''simple docstring'''





												class 					lowercase__						(   UpperCamelCase_):
																		UpperCamelCase_     =		True

												try:
																		AutoConfig.register('''custom'''    ,		UpperCamelCase__						)
																		AutoImageProcessor.register(UpperCamelCase__    ,		UpperCamelCase__						)
																		# 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							:    Union[str, Any]							=							AutoImageProcessor.from_pretrained(
																		    '''hf-internal-testing/test_dynamic_image_processor'''    ,		trust_remote_code=UpperCamelCase__						)
																		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							:    Optional[Any]							=							AutoImageProcessor.from_pretrained(
																		    '''hf-internal-testing/test_dynamic_image_processor'''    ,		trust_remote_code=UpperCamelCase__						)
																		self.assertEqual(image_processor.__class__.__name__    ,		'''NewImageProcessor'''						)
																		self.assertTrue(not hasattr(UpperCamelCase__    ,		'''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]






import math
def       A	(    _lowercase						):
						return math.sqrt(_lowercase						) * math.sqrt(_lowercase						) == num
def       A	(    _lowercase						):
						SCREAMING_SNAKE_CASE							:    Dict							=							0
						SCREAMING_SNAKE_CASE							:    Tuple							=							n
						while left <= right:
												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							(left + right) // 2
												if mid**2 == n:
																		return True
												elif mid**2 > n:
																		SCREAMING_SNAKE_CASE							:    Optional[Any]							=							mid - 1
												else:
																		SCREAMING_SNAKE_CASE							:    Optional[int]							=							mid + 1
						return False


if __name__ == "__main__":
					import doctest

					doctest.testmod()





