

"""simple docstring"""






def 	lowercase_						(     _lowercase							:		list[int]				,   _lowercase							:		list[int]						):




					'''simple docstring'''






					if not len(UpperCamelCase__						) == len(UpperCamelCase__						) == 3:
										raise ValueError("Please enter a valid equation."						)
					if equationa[0] == equationa[1] == equationa[0] == equationa[1] == 0:
										raise ValueError("Both a & b of two equations can\'t be zero."						)

					# Extract the coefficients
					UpperCAmelCase      : Dict   =					equationa
					UpperCAmelCase      : List[str]   =					equationa

					# Calculate the determinants of the matrices
					UpperCAmelCase      : Tuple   =					aa * ba - aa * ba
					UpperCAmelCase      : List[str]   =					ca * ba - ca * ba
					UpperCAmelCase      : Optional[Any]   =					aa * ca - aa * ca

					# Check if the system of linear equations has a solution (using Cramer's rule)
					if determinant == 0:
										if determinant_x == determinant_y == 0:
															raise ValueError("Infinite solutions. (Consistent system)"						)
										else:
															raise ValueError("No solution. (Inconsistent system)"						)
					else:
										if determinant_x == determinant_y == 0:
															# Trivial solution (Inconsistent system)
															return (0.0, 0.0)
										else:
															UpperCAmelCase      : Optional[Any]   =					determinant_x / determinant
															UpperCAmelCase      : Optional[Any]   =					determinant_y / determinant
															# Non-Trivial Solution (Consistent system)
															return (x, y)









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 				a			(      unittest.TestCase			):






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Optional[int]           =   0






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				List[str]           =   AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''					)
										self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with tempfile.TemporaryDirectory() as tmpdirname:
																__SCREAMING_SNAKE_CASE:				Optional[Any]           =   Path(_lowerCAmelCase					) / '''preprocessor_config.json'''
																__SCREAMING_SNAKE_CASE:				List[str]           =   Path(_lowerCAmelCase					) / '''config.json'''
																json.dump(
																    {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}			, open(_lowerCAmelCase			, '''w'''					)			, )
																json.dump({'''model_type''': '''clip'''}			, open(_lowerCAmelCase			, '''w'''					)					)

																__SCREAMING_SNAKE_CASE:				Dict           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					)
																self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




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

																__SCREAMING_SNAKE_CASE:				str           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					)
																self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with tempfile.TemporaryDirectory() as tmpdirname:
																__SCREAMING_SNAKE_CASE:				int           =   CLIPConfig()

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

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

																config_dict.pop('''image_processor_type'''					)
																__SCREAMING_SNAKE_CASE:				List[str]           =   CLIPImageProcessor(**_lowerCAmelCase					)

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

																__SCREAMING_SNAKE_CASE:				Dict           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					)

																# make sure private variable is not incorrectly saved
																__SCREAMING_SNAKE_CASE:				int           =   json.loads(config.to_json_string()					)
																self.assertTrue('''_processor_class''' not in dict_as_saved					)

										self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




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

																__SCREAMING_SNAKE_CASE:				int           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					)
																self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with self.assertRaisesRegex(
										    _lowerCAmelCase			, '''clip-base is not a local folder and is not a valid model identifier'''					):
																__SCREAMING_SNAKE_CASE:				Tuple           =   AutoImageProcessor.from_pretrained('''clip-base'''					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with self.assertRaisesRegex(
										    _lowerCAmelCase			, R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''					):
																__SCREAMING_SNAKE_CASE:				Dict           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase			, revision='''aaaaaa'''					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




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






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with self.assertRaises(_lowerCAmelCase					):
																__SCREAMING_SNAKE_CASE:				Optional[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(_lowerCAmelCase					):
																__SCREAMING_SNAKE_CASE:				Any           =   AutoImageProcessor.from_pretrained(
																    '''hf-internal-testing/test_dynamic_image_processor'''			, trust_remote_code=_lowerCAmelCase					)

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

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






				def 			snake_case_    (  self					):

										"""simple docstring"""




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

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

																						__SCREAMING_SNAKE_CASE:				List[str]           =   CustomImageProcessor.from_pretrained(_lowerCAmelCase					)

																# 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(_lowerCAmelCase					)
																						__SCREAMING_SNAKE_CASE:				int           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					)
																						self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)

										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					):

										"""simple docstring"""




										class 				a			(      __lowercase			):
														SCREAMING_SNAKE_CASE__     :   Tuple		      =     True

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



