
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 						__magic_name__				(  snake_case      ):
		_lowerCAmelCase						=		"config.json"





		@register_to_config
		def __init__(							self      :		int  ,					lowerCamelCase__      :		Optional[Any]=2  ,					lowerCamelCase__      :		int=5  ,					lowerCamelCase__      :		Any=(2, 5)  ,					lowerCamelCase__      :		int="for diffusion"  ,					lowerCamelCase__      :		Dict=[1, 3]  ,					):
							pass



class 						__magic_name__				(  snake_case      ):
		_lowerCAmelCase						=		"config.json"





		@register_to_config
		def __init__(							self      :		List[str]  ,					lowerCamelCase__      :		Optional[int]=2  ,					lowerCamelCase__      :		Tuple=5  ,					lowerCamelCase__      :		str=(2, 5)  ,					lowerCamelCase__      :		int="for diffusion"  ,					lowerCamelCase__      :		List[Any]=[1, 3]  ,					):
							pass



class 						__magic_name__				(  snake_case      ):
		_lowerCAmelCase						=		"config.json"





		@register_to_config
		def __init__(							self      :		Any  ,					lowerCamelCase__      :		Union[str, Any]=2  ,					lowerCamelCase__      :		Tuple=5  ,					lowerCamelCase__      :		Optional[Any]=(2, 5)  ,					lowerCamelCase__      :		Optional[Any]="for diffusion"  ,					lowerCamelCase__      :		Optional[int]=[1, 3]  ,					lowerCamelCase__      :		List[Any]=[1, 3]  ,					):
							pass



class 						__magic_name__				(  snake_case      ):
		_lowerCAmelCase						=		"config.json"





		@register_to_config
		def __init__(							self      :		Union[str, Any]  ,					lowerCamelCase__      :		Union[str, Any]=2  ,					lowerCamelCase__      :		Any=5  ,					lowerCamelCase__      :		Dict=(2, 5)  ,					lowerCamelCase__      :		Union[str, Any]="for diffusion"  ,					lowerCamelCase__      :		str=[1, 5]  ,					lowerCamelCase__      :		Any=[5, 4]  ,					):
							pass



class 						__magic_name__				(  unittest.TestCase      ):





		def  _A							(							self      :		List[str]			):
							with self.assertRaises(lowerCamelCase__			):
												ConfigMixin.load_config('''dummy_path'''			)





		def  _A							(							self      :		int			):
							lowerCAmelCase						:   Optional[Any]							=       SampleObject()
							lowerCAmelCase						:   Optional[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]

							# init ignore private arguments
							lowerCAmelCase						:   Tuple							=       SampleObject(_name_or_path='''lalala'''			)
							lowerCAmelCase						:   List[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]

							# can override default
							lowerCAmelCase						:   Optional[Any]							=       SampleObject(c=6			)
							lowerCAmelCase						:   Dict							=       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						:   Union[str, Any]							=       SampleObject(1  ,					c=6			)
							lowerCAmelCase						:   List[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[Any]			):
							lowerCAmelCase						:   str							=       SampleObject()
							lowerCAmelCase						:   Union[str, 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]

							with tempfile.TemporaryDirectory() as tmpdirname:
												obj.save_config(lowerCamelCase__			)
												lowerCAmelCase						:   Union[str, Any]							=       SampleObject.from_config(SampleObject.load_config(lowerCamelCase__			)			)
												lowerCAmelCase						:   Optional[Any]							=       new_obj.config

							# unfreeze configs
							lowerCAmelCase						:   Tuple							=       dict(lowerCamelCase__			)
							lowerCAmelCase						:   Any							=       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      :		List[str]			):
							lowerCAmelCase						:   Optional[int]							=       logging.get_logger('''diffusers.configuration_utils'''			)
							# 30 for warning
							logger.setLevel(3_0			)

							with CaptureLogger(lowerCamelCase__			) as cap_logger:
												lowerCAmelCase						:   List[Any]							=       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      :		Union[str, Any]			):
							lowerCAmelCase						:   str							=       logging.get_logger('''diffusers.configuration_utils'''			)
							# 30 for warning
							logger.setLevel(3_0			)

							with CaptureLogger(lowerCamelCase__			) as cap_logger:
												lowerCAmelCase						:   Optional[int]							=       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      :		Optional[Any]			):
							lowerCAmelCase						:   List[Any]							=       logging.get_logger('''diffusers.configuration_utils'''			)
							# 30 for warning
							logger.setLevel(3_0			)

							with CaptureLogger(lowerCamelCase__			) as cap_logger:
												lowerCAmelCase						:   Tuple							=       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      :		Optional[Any]			):
							lowerCAmelCase						:   Optional[int]							=       logging.get_logger('''diffusers.configuration_utils'''			)
							# 30 for warning
							logger.setLevel(3_0			)

							with CaptureLogger(lowerCamelCase__			) as cap_logger:
												lowerCAmelCase						:   Optional[int]							=       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      :		Tuple			):
							lowerCAmelCase						:   List[Any]							=       logging.get_logger('''diffusers.configuration_utils'''			)
							# 30 for warning
							logger.setLevel(3_0			)

							with CaptureLogger(lowerCamelCase__			) as cap_logger:
												lowerCAmelCase						:   Tuple							=       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=8_8			)

							assert ddpm.__class__ == DDPMScheduler
							assert ddpm.config.prediction_type == "sample"
							assert ddpm.config.beta_end == 8
							assert ddpm_a.config.beta_start == 8_8

							# no warning should be thrown
							assert cap_logger.out == ""
							assert cap_logger_a.out == ""





		def  _A							(							self      :		Union[str, Any]			):
							lowerCAmelCase						:   int							=       logging.get_logger('''diffusers.configuration_utils'''			)
							# 30 for warning
							logger.setLevel(3_0			)

							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      :		int			):
							# 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						:   List[str]							=       SampleObject()

							lowerCAmelCase						:   List[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						:   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						:   List[str]							=       SampleObjecta.from_config(config.config			)
							assert new_config.f == [5, 4]

							config.config._use_default_values.pop()
							lowerCAmelCase						:   int							=       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]


def       UpperCAmelCase__							(    __magic_name__  :       Union[str, Any]							,					__magic_name__  :       int					):


					'''simple docstring'''

					sequence.append(__magic_name__					)

					lowerCAmelCase						:   Tuple							=       0
					while sequence[index] != target:
										index += 1

					sequence.pop()

					if index == len(__magic_name__					):
										return None

					return index


if __name__ == "__main__":
		__SCREAMING_SNAKE_CASE     :				Dict             =       input('Enter numbers separated by comma:\n').strip()
		__SCREAMING_SNAKE_CASE     :				int             =       [int(item) for item in user_input.split(',')]

		__SCREAMING_SNAKE_CASE     :				str             =       input('Enter a single number to be found in the list:\n')
		__SCREAMING_SNAKE_CASE     :				Tuple             =       int(target_input)
		__SCREAMING_SNAKE_CASE     :				Union[str, Any]             =       sentinel_linear_search(sequence, target)
		if result is not None:
				print(f"""{target} found at positions: {result}""")
		else:
				print('Not found')
