code: 
  
  
  
  
  
  import tempfile
  import unittest
  
  from diffusers import (
      DDIMScheduler,
      DDPMScheduler,
      DPMSolverMultistepScheduler,
      EulerAncestralDiscreteScheduler,
      EulerDiscreteScheduler,
      PNDMScheduler,
      logging,
  )
  from diffusers.configuration_utils import ConfigMixin, register_to_config
  from diffusers.utils.testing_utils import CaptureLogger
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	str							=				'config.json'
  
  
  
  					@register_to_config
  					def __init__(		self    :    Dict					,			lowerCamelCase    :    Optional[Any]=2					,			lowerCamelCase    :    Tuple=5					,			lowerCamelCase    :    Union[str, Any]=(2, 5)					,			lowerCamelCase    :    int="for diffusion"					,			lowerCamelCase    :    str=[1, 3]					,			):
  							pass
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	Union[str, Any]							=				'config.json'
  
  
  
  					@register_to_config
  					def __init__(		self    :    Any					,			lowerCamelCase    :    Dict=2					,			lowerCamelCase    :    Optional[int]=5					,			lowerCamelCase    :    Optional[int]=(2, 5)					,			lowerCamelCase    :    Dict="for diffusion"					,			lowerCamelCase    :    str=[1, 3]					,			):
  							pass
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	Optional[Any]							=				'config.json'
  
  
  
  					@register_to_config
  					def __init__(		self    :    int					,			lowerCamelCase    :    Optional[Any]=2					,			lowerCamelCase    :    Union[str, Any]=5					,			lowerCamelCase    :    Optional[Any]=(2, 5)					,			lowerCamelCase    :    Union[str, Any]="for diffusion"					,			lowerCamelCase    :    List[Any]=[1, 3]					,			lowerCamelCase    :    List[Any]=[1, 3]					,			):
  							pass
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	Tuple							=				'config.json'
  
  
  
  					@register_to_config
  					def __init__(		self    :    Optional[int]					,			lowerCamelCase    :    Optional[int]=2					,			lowerCamelCase    :    Optional[int]=5					,			lowerCamelCase    :    str=(2, 5)					,			lowerCamelCase    :    str="for diffusion"					,			lowerCamelCase    :    Union[str, Any]=[1, 5]					,			lowerCamelCase    :    Dict=[5, 4]					,			):
  							pass
  
  
  
  
  
  
  class 	UpperCamelCase_     (     unittest.TestCase       ):
  
  
  
  					def      __a    (		self    :    Tuple	):
  							with self.assertRaises(lowerCamelCase	):
  									ConfigMixin.load_config('dummy_path'	)
  
  
  
  					def      __a    (		self    :    Any	):
  							lowerCamelCase_  :    List[Any]   	=			SampleObject()
  							lowerCamelCase_  :    Any   	=			obj.config
  							assert config["a"] == 2
  							assert config["b"] == 5
  							assert config["c"] == (2, 5)
  							assert config["d"] == "for diffusion"
  							assert config["e"] == [1, 3]
  
  							# init ignore private arguments
  							lowerCamelCase_  :    Any   	=			SampleObject(_name_or_path='lalala'	)
  							lowerCamelCase_  :    int   	=			obj.config
  							assert config["a"] == 2
  							assert config["b"] == 5
  							assert config["c"] == (2, 5)
  							assert config["d"] == "for diffusion"
  							assert config["e"] == [1, 3]
  
  							# can override default
  							lowerCamelCase_  :    Union[str, Any]   	=			SampleObject(c=6	)
  							lowerCamelCase_  :    List[Any]   	=			obj.config
  							assert config["a"] == 2
  							assert config["b"] == 5
  							assert config["c"] == 6
  							assert config["d"] == "for diffusion"
  							assert config["e"] == [1, 3]
  
  							# can use positional arguments.
  							lowerCamelCase_  :    Tuple   	=			SampleObject(1					,			c=6	)
  							lowerCamelCase_  :    Union[str, Any]   	=			obj.config
  							assert config["a"] == 1
  							assert config["b"] == 5
  							assert config["c"] == 6
  							assert config["d"] == "for diffusion"
  							assert config["e"] == [1, 3]
  
  
  
  					def      __a    (		self    :    List[str]	):
  							lowerCamelCase_  :    int   	=			SampleObject()
  							lowerCamelCase_  :    str   	=			obj.config
  
  							assert config["a"] == 2
  							assert config["b"] == 5
  							assert config["c"] == (2, 5)
  							assert config["d"] == "for diffusion"
  							assert config["e"] == [1, 3]
  
  							with tempfile.TemporaryDirectory() as tmpdirname:
  									obj.save_config(lowerCamelCase	)
  									lowerCamelCase_  :    str   	=			SampleObject.from_config(SampleObject.load_config(lowerCamelCase	)	)
  									lowerCamelCase_  :    Optional[Any]   	=			new_obj.config
  
  							# unfreeze configs
  							lowerCamelCase_  :    int   	=			dict(lowerCamelCase	)
  							lowerCamelCase_  :    str   	=			dict(lowerCamelCase	)
  
  							assert config.pop('c'	) == (2, 5)  # instantiated as tuple
  							assert new_config.pop('c'	) == [2, 5]  # saved & loaded as list because of json
  							config.pop('_use_default_values'	)
  							assert config == new_config
  
  
  
  					def      __a    (		self    :    Optional[int]	):
  							lowerCamelCase_  :    List[str]   	=			logging.get_logger('diffusers.configuration_utils'	)
  							# 30 for warning
  							logger.setLevel(30	)
  
  							with CaptureLogger(lowerCamelCase	) as cap_logger:
  									lowerCamelCase_  :    List[str]   	=			DDIMScheduler.from_pretrained(
  									    'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)
  
  							assert ddim.__class__ == DDIMScheduler
  							# no warning should be thrown
  							assert cap_logger.out == ""
  
  
  
  					def      __a    (		self    :    List[str]	):
  							lowerCamelCase_  :    Optional[Any]   	=			logging.get_logger('diffusers.configuration_utils'	)
  							# 30 for warning
  							logger.setLevel(30	)
  
  							with CaptureLogger(lowerCamelCase	) as cap_logger:
  									lowerCamelCase_  :    List[str]   	=			EulerDiscreteScheduler.from_pretrained(
  									    'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)
  
  							assert euler.__class__ == EulerDiscreteScheduler
  							# no warning should be thrown
  							assert cap_logger.out == ""
  
  
  
  					def      __a    (		self    :    int	):
  							lowerCamelCase_  :    str   	=			logging.get_logger('diffusers.configuration_utils'	)
  							# 30 for warning
  							logger.setLevel(30	)
  
  							with CaptureLogger(lowerCamelCase	) as cap_logger:
  									lowerCamelCase_  :    List[Any]   	=			EulerAncestralDiscreteScheduler.from_pretrained(
  									    'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)
  
  							assert euler.__class__ == EulerAncestralDiscreteScheduler
  							# no warning should be thrown
  							assert cap_logger.out == ""
  
  
  
  					def      __a    (		self    :    List[str]	):
  							lowerCamelCase_  :    Optional[int]   	=			logging.get_logger('diffusers.configuration_utils'	)
  							# 30 for warning
  							logger.setLevel(30	)
  
  							with CaptureLogger(lowerCamelCase	) as cap_logger:
  									lowerCamelCase_  :    List[Any]   	=			PNDMScheduler.from_pretrained(
  									    'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)
  
  							assert pndm.__class__ == PNDMScheduler
  							# no warning should be thrown
  							assert cap_logger.out == ""
  
  
  
  					def      __a    (		self    :    List[str]	):
  							lowerCamelCase_  :    Tuple   	=			logging.get_logger('diffusers.configuration_utils'	)
  							# 30 for warning
  							logger.setLevel(30	)
  
  							with CaptureLogger(lowerCamelCase	) as cap_logger:
  									lowerCamelCase_  :    Optional[Any]   	=			DDPMScheduler.from_pretrained(
  									    'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'					,			prediction_type='sample'					,			beta_end=8					,			)
  
  							with CaptureLogger(lowerCamelCase	) as cap_logger_a:
  									lowerCamelCase_  :    Tuple   	=			DDPMScheduler.from_pretrained('google/ddpm-celebahq-256'					,			beta_start=88	)
  
  							assert ddpm.__class__ == DDPMScheduler
  							assert ddpm.config.prediction_type == "sample"
  							assert ddpm.config.beta_end == 8
  							assert ddpm_a.config.beta_start == 88
  
  							# no warning should be thrown
  							assert cap_logger.out == ""
  							assert cap_logger_a.out == ""
  
  
  
  					def      __a    (		self    :    int	):
  							lowerCamelCase_  :    Optional[Any]   	=			logging.get_logger('diffusers.configuration_utils'	)
  							# 30 for warning
  							logger.setLevel(30	)
  
  							with CaptureLogger(lowerCamelCase	) as cap_logger:
  									lowerCamelCase_  :    Optional[Any]   	=			DPMSolverMultistepScheduler.from_pretrained(
  									    'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)
  
  							assert dpm.__class__ == DPMSolverMultistepScheduler
  							# no warning should be thrown
  							assert cap_logger.out == ""
  
  
  
  
  
  					def      __a    (		self    :    Dict	):
  							# let's first save a config that should be in the form
  							#    a=2,
  							#    b=5,
  							#    c=(2, 5),
  							#    d="for diffusion",
  							#    e=[1, 3],
  
  							lowerCamelCase_  :    Optional[Any]   	=			SampleObject()
  
  							lowerCamelCase_  :    str   	=			{k: v for k, v in config.config.items() if not k.startswith('_'	)}
  
  							# make sure that default config has all keys in `_use_default_values`
  							assert set(config_dict.keys()	) == set(config.config._use_default_values	)
  
  							with tempfile.TemporaryDirectory() as tmpdirname:
  									config.save_config(lowerCamelCase	)
  
  									# now loading it with SampleObject2 should put f into `_use_default_values`
  									lowerCamelCase_  :    Optional[Any]   	=			SampleObjecta.from_config(lowerCamelCase	)
  
  									assert "f" in config._use_default_values
  									assert config.f == [1, 3]
  
  							# now loading the config, should **NOT** use [1, 3] for `f`, but the default [1, 4] value
  							# **BECAUSE** it is part of `config._use_default_values`
  							lowerCamelCase_  :    Union[str, Any]   	=			SampleObjecta.from_config(config.config	)
  							assert new_config.f == [5, 4]
  
  							config.config._use_default_values.pop()
  							lowerCamelCase_  :    Optional[Any]   	=			SampleObjecta.from_config(config.config	)
  							assert new_config_a.f == [1, 3]
  
  							# Nevertheless "e" should still be correctly loaded to [1, 3] from SampleObject2 instead of defaulting to [1, 5]
  							assert new_config_a.e == [1, 3]
  
style_context: 
  
  
  
  
  
  from __future__ import annotations
  
  
  def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
  		lowerCamelCase_  :    int
  		lowerCamelCase_  :    list[str]   	=			list(lowerCAmelCase__	)
  		lowerCamelCase_	,			lowerCamelCase_  :    List[str]   	=			_vector[:-1], int(_vector[-1]	)
  		lowerCamelCase_  :    list[int]   	=			[int(lowerCAmelCase__	) for digit in __vector]
  
  		vector.reverse()
  		for i, digit in enumerate(lowerCAmelCase__	):
  				if i & 1 == 0:
  						lowerCamelCase_  :    int   	=			digit * 2
  						if doubled > 9:
  								doubled -= 9
  						check_digit += doubled
  				else:
  						check_digit += digit
  
  		return check_digit % 10 == 0
  
  
  if __name__ == "__main__":
  		import doctest
  
  		doctest.testmod()
  		assert is_luhn("""79927398713""")
  		assert not is_luhn("""79927398714""")
  