



from __future__ import annotations

from PIL import Image

# Define the first generation of cells
# fmt: off
UpperCAmelCase__			:   int      			=    [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]


def 	_A	(   _UpperCamelCase			):
				return [int(lowerCAmelCase_			) for c in F'''{ruleset:08}'''[:8]]


def 	_A	(   _UpperCamelCase      ,					_UpperCamelCase      ,					_UpperCamelCase			):
				_UpperCAmelCase						:  Optional[Any]     					=	len(cells[0]			)  # 31
				_UpperCAmelCase						:  int     					=	[]
				for i in range(lowerCAmelCase_			):
								# Get the neighbors of each cell
								# Handle neighbours outside bounds by using 0 as their value
								_UpperCAmelCase						:  Union[str, Any]     					=	0 if i == 0 else cells[time][i - 1]
								_UpperCAmelCase						:  List[str]     					=	0 if i == population - 1 else cells[time][i + 1]
								# Define a new cell and add it to the new generation
								_UpperCAmelCase						:  List[Any]     					=	7 - int(F'''{left_neighbor}{cells[time][i]}{right_neighbor}'''      ,					2			)
								next_generation.append(rule[situation]			)
				return next_generation


def 	_A	(   _UpperCamelCase			):
				_UpperCAmelCase						:  Optional[Any]     					=	Image.new('''RGB'''      ,					(len(cells[0]			), len(lowerCAmelCase_			))			)
				_UpperCAmelCase						:  str     					=	img.load()
				# Generates image
				for w in range(img.width			):
								for h in range(img.height			):
												_UpperCAmelCase						:  Optional[Any]     					=	255 - int(255 * cells[h][w]			)
												_UpperCAmelCase						:  List[Any]     					=	(color, color, color)
				return img


if __name__ == "__main__":
					UpperCAmelCase__			:   str      			=    bin(int(input('Rule:\n').strip()))[2:]
					UpperCAmelCase__			:   List[str]      			=    format_ruleset(int(rule_num))
					for time in range(16):
										CELLS.append(new_generation(CELLS, rule, time))
					UpperCAmelCase__			:   Dict      			=    generate_image(CELLS)
					# Uncomment to save the image
					# img.save(f"rule_{rule_num}.png")
					img.show()




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 					snake_case__(				UpperCAmelCase__				):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__   :	Union[str, Any]       =				"""config.json"""




						@register_to_config
						def __init__(					self ,    __lowercase=2 ,    __lowercase=5 ,    __lowercase=(2, 5) ,    __lowercase="for diffusion" ,    __lowercase=[1, 3] ,    )       ->     int:
										pass







class 					snake_case__(				UpperCAmelCase__				):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__   :	int       =				"""config.json"""




						@register_to_config
						def __init__(					self ,    __lowercase=2 ,    __lowercase=5 ,    __lowercase=(2, 5) ,    __lowercase="for diffusion" ,    __lowercase=[1, 3] ,    )       ->     Optional[Any]:
										pass







class 					snake_case__(				UpperCAmelCase__				):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__   :	int       =				"""config.json"""




						@register_to_config
						def __init__(					self ,    __lowercase=2 ,    __lowercase=5 ,    __lowercase=(2, 5) ,    __lowercase="for diffusion" ,    __lowercase=[1, 3] ,    __lowercase=[1, 3] ,    )       ->     List[str]:
										pass







class 					snake_case__(				UpperCAmelCase__				):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__   :	Optional[Any]       =				"""config.json"""




						@register_to_config
						def __init__(					self ,    __lowercase=2 ,    __lowercase=5 ,    __lowercase=(2, 5) ,    __lowercase="for diffusion" ,    __lowercase=[1, 5] ,    __lowercase=[5, 4] ,    )       ->     List[str]:
										pass







class 					snake_case__(				unittest.TestCase				):







						'''simple docstring'''




						def     lowercase_			(					self				)       ->     str:
										with self.assertRaises(__lowercase				):
														ConfigMixin.load_config('''dummy_path'''				)




						def     lowercase_			(					self				)       ->     Optional[int]:
										lowerCAmelCase_			:   List[str]     					=					SampleObject()
										lowerCAmelCase_			:   Dict     					=					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_			:   List[str]     					=					SampleObject(_name_or_path='''lalala'''				)
										lowerCAmelCase_			:   Dict     					=					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_			:   List[Any]     					=					SampleObject(c=6				)
										lowerCAmelCase_			:   Optional[int]     					=					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_			:   Optional[Any]     					=					SampleObject(1 ,    c=6				)
										lowerCAmelCase_			:   Dict     					=					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     lowercase_			(					self				)       ->     int:
										lowerCAmelCase_			:   List[Any]     					=					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(__lowercase				)
														lowerCAmelCase_			:   int     					=					SampleObject.from_config(SampleObject.load_config(__lowercase				)				)
														lowerCAmelCase_			:   Optional[Any]     					=					new_obj.config

										# unfreeze configs
										lowerCAmelCase_			:   str     					=					dict(__lowercase				)
										lowerCAmelCase_			:   Any     					=					dict(__lowercase				)

										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     lowercase_			(					self				)       ->     List[str]:
										lowerCAmelCase_			:   Optional[Any]     					=					logging.get_logger('''diffusers.configuration_utils'''				)
										# 30 for warning
										logger.setLevel(3_0				)

										with CaptureLogger(__lowercase				) as cap_logger:
														lowerCAmelCase_			:   int     					=					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     lowercase_			(					self				)       ->     Optional[Any]:
										lowerCAmelCase_			:   List[Any]     					=					logging.get_logger('''diffusers.configuration_utils'''				)
										# 30 for warning
										logger.setLevel(3_0				)

										with CaptureLogger(__lowercase				) as cap_logger:
														lowerCAmelCase_			:   Any     					=					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     lowercase_			(					self				)       ->     Any:
										lowerCAmelCase_			:   Tuple     					=					logging.get_logger('''diffusers.configuration_utils'''				)
										# 30 for warning
										logger.setLevel(3_0				)

										with CaptureLogger(__lowercase				) as cap_logger:
														lowerCAmelCase_			:   Optional[int]     					=					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     lowercase_			(					self				)       ->     List[Any]:
										lowerCAmelCase_			:   Any     					=					logging.get_logger('''diffusers.configuration_utils'''				)
										# 30 for warning
										logger.setLevel(3_0				)

										with CaptureLogger(__lowercase				) as cap_logger:
														lowerCAmelCase_			:   Dict     					=					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     lowercase_			(					self				)       ->     Tuple:
										lowerCAmelCase_			:   Optional[int]     					=					logging.get_logger('''diffusers.configuration_utils'''				)
										# 30 for warning
										logger.setLevel(3_0				)

										with CaptureLogger(__lowercase				) as cap_logger:
														lowerCAmelCase_			:   int     					=					DDPMScheduler.from_pretrained(
														    '''hf-internal-testing/tiny-stable-diffusion-torch''' ,    subfolder='''scheduler''' ,    prediction_type='''sample''' ,    beta_end=8 ,    )

										with CaptureLogger(__lowercase				) 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     lowercase_			(					self				)       ->     int:
										lowerCAmelCase_			:   Tuple     					=					logging.get_logger('''diffusers.configuration_utils'''				)
										# 30 for warning
										logger.setLevel(3_0				)

										with CaptureLogger(__lowercase				) as cap_logger:
														lowerCAmelCase_			:   List[str]     					=					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     lowercase_			(					self				)       ->     Optional[Any]:
										# 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_			:   Dict     					=					SampleObject()

										lowerCAmelCase_			:   Optional[int]     					=					{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(__lowercase				)

														# now loading it with SampleObject2 should put f into `_use_default_values`
														lowerCAmelCase_			:   List[Any]     					=					SampleObjecta.from_config(__lowercase				)

														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[Any]     					=					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]