

"""simple docstring"""




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 (   _A						):
		SCREAMING_SNAKE_CASE								=    "config.json"


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





class 			__UpperCamelCase (   _A						):
		SCREAMING_SNAKE_CASE								=    "config.json"


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





class 			__UpperCamelCase (   _A						):
		SCREAMING_SNAKE_CASE								=    "config.json"


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





class 			__UpperCamelCase (   _A						):
		SCREAMING_SNAKE_CASE								=    "config.json"


		@register_to_config
		def __init__(self :		Any     ,     __SCREAMING_SNAKE_CASE :		Union[str, Any]=2     ,     __SCREAMING_SNAKE_CASE :		List[Any]=5     ,     __SCREAMING_SNAKE_CASE :		Optional[Any]=(2, 5)     ,     __SCREAMING_SNAKE_CASE :		str="for diffusion"     ,     __SCREAMING_SNAKE_CASE :		int=[1, 5]     ,     __SCREAMING_SNAKE_CASE :		Optional[int]=[5, 4]     ,     ):
							pass





class 			__UpperCamelCase (   unittest.TestCase						):


		def 					SCREAMING_SNAKE_CASE__   (self :		Optional[int]):


							with self.assertRaises(A_):
												ConfigMixin.load_config("dummy_path")


		def 					SCREAMING_SNAKE_CASE__   (self :		Tuple):
							A			=					SampleObject()
							A			=					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
							A			=					SampleObject(_name_or_path="lalala")
							A			=					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
							A			=					SampleObject(c=6)
							A			=					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.
							A			=					SampleObject(1     ,     c=6)
							A			=					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 					SCREAMING_SNAKE_CASE__   (self :		Union[str, Any]):
							A			=					SampleObject()
							A			=					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(A_)
												A			=					SampleObject.from_config(SampleObject.load_config(A_))
												A			=					new_obj.config

							# unfreeze configs
							A			=					dict(A_)
							A			=					dict(A_)

							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 					SCREAMING_SNAKE_CASE__   (self :		List[str]):
							A			=					logging.get_logger("diffusers.configuration_utils")
							# 30 for warning
							logger.setLevel(3_0)

							with CaptureLogger(A_) as cap_logger:
												A			=					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 					SCREAMING_SNAKE_CASE__   (self :		List[Any]):
							A			=					logging.get_logger("diffusers.configuration_utils")
							# 30 for warning
							logger.setLevel(3_0)

							with CaptureLogger(A_) as cap_logger:
												A			=					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 					SCREAMING_SNAKE_CASE__   (self :		List[str]):
							A			=					logging.get_logger("diffusers.configuration_utils")
							# 30 for warning
							logger.setLevel(3_0)

							with CaptureLogger(A_) as cap_logger:
												A			=					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 					SCREAMING_SNAKE_CASE__   (self :		Any):
							A			=					logging.get_logger("diffusers.configuration_utils")
							# 30 for warning
							logger.setLevel(3_0)

							with CaptureLogger(A_) as cap_logger:
												A			=					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 					SCREAMING_SNAKE_CASE__   (self :		Any):
							A			=					logging.get_logger("diffusers.configuration_utils")
							# 30 for warning
							logger.setLevel(3_0)

							with CaptureLogger(A_) as cap_logger:
												A			=					DDPMScheduler.from_pretrained(
												    "hf-internal-testing/tiny-stable-diffusion-torch"     ,     subfolder="scheduler"     ,     prediction_type="sample"     ,     beta_end=8     ,     )

							with CaptureLogger(A_) as cap_logger_a:
												A			=					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 					SCREAMING_SNAKE_CASE__   (self :		List[str]):
							A			=					logging.get_logger("diffusers.configuration_utils")
							# 30 for warning
							logger.setLevel(3_0)

							with CaptureLogger(A_) as cap_logger:
												A			=					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 					SCREAMING_SNAKE_CASE__   (self :		int):
							A			=					SampleObject()

							A			=					{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(A_)

												# now loading it with SampleObject2 should put f into `_use_default_values`
												A			=					SampleObjecta.from_config(A_)

												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`
							A			=					SampleObjecta.from_config(config.config)
							assert new_config.f == [5, 4]

							config.config._use_default_values.pop()
							A			=					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]








import math

def 							__SCREAMING_SNAKE_CASE							( lowerCAmelCase:     int       )      ->				list:
				if n <= 0:
								raise ValueError("Only positive integers have prime factors"       )
				_UpperCAmelCase				:						Union[str, Any]       						=			[]
				while n % 2 == 0:
								pf.append(2       )
								_UpperCAmelCase				:						Tuple       						=			int(n / 2       )
				for i in range(3     ,					int(math.sqrt(lowerCAmelCase       )       ) + 1     ,					2       ):
								while n % i == 0:
												pf.append(lowerCAmelCase       )
												_UpperCAmelCase				:						Optional[int]       						=			int(n / i       )
				if n > 2:
								pf.append(lowerCAmelCase       )
				return pf

def 							__SCREAMING_SNAKE_CASE							( lowerCAmelCase:     int       )      ->				int:
				if n <= 0:
								raise ValueError("Only positive numbers are accepted"       )
				_UpperCAmelCase				:						Dict       						=			1
				_UpperCAmelCase				:						str       						=			1
				while n % 2 == 0:
								temp += 1
								_UpperCAmelCase				:						List[str]       						=			int(n / 2       )
				div *= temp
				for i in range(3     ,					int(math.sqrt(lowerCAmelCase       )       ) + 1     ,					2       ):
								_UpperCAmelCase				:						Any       						=			1
								while n % i == 0:
												temp += 1
												_UpperCAmelCase				:						Any       						=			int(n / i       )
								div *= temp
				if n > 1:
								div *= 2
				return div

def 							__SCREAMING_SNAKE_CASE							( lowerCAmelCase:     int       )      ->				int:
				if n <= 0:
								raise ValueError("Only positive numbers are accepted"       )
				_UpperCAmelCase				:						Optional[Any]       						=			1
				_UpperCAmelCase				:						Union[str, Any]       						=			1
				while n % 2 == 0:
								temp += 1
								_UpperCAmelCase				:						Optional[Any]       						=			int(n / 2       )
				if temp > 1:
								s *= (2**temp - 1) / (2 - 1)
				for i in range(3     ,					int(math.sqrt(lowerCAmelCase       )       ) + 1     ,					2       ):
								_UpperCAmelCase				:						List[str]       						=			1
								while n % i == 0:
												temp += 1
												_UpperCAmelCase				:						List[Any]       						=			int(n / i       )
								if temp > 1:
												s *= (i**temp - 1) / (i - 1)
				return int(lowerCAmelCase       )

def 							__SCREAMING_SNAKE_CASE							( lowerCAmelCase:     int       )      ->				int:
				_UpperCAmelCase				:						Any       						=			n
				for x in set(prime_factors(lowerCAmelCase       )       ):
								s *= (x - 1) / x
				return int(lowerCAmelCase       )


if __name__ == "__main__":
					import doctest

					doctest.testmod()


