
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      SCREAMING_SNAKE_CASE__  (			UpperCAmelCase      ):





 '''simple docstring'''



 _UpperCAmelCase :	int					     =      "config.json"



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


    '''simple docstring'''


    pass




class      SCREAMING_SNAKE_CASE__  (			UpperCAmelCase      ):





 '''simple docstring'''



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



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


    '''simple docstring'''


    pass




class      SCREAMING_SNAKE_CASE__  (			UpperCAmelCase      ):





 '''simple docstring'''



 _UpperCAmelCase :	str					     =      "config.json"



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


    '''simple docstring'''


    pass




class      SCREAMING_SNAKE_CASE__  (			UpperCAmelCase      ):





 '''simple docstring'''



 _UpperCAmelCase :	Dict					     =      "config.json"



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


    '''simple docstring'''


    pass




class      SCREAMING_SNAKE_CASE__  (			unittest.TestCase      ):





 '''simple docstring'''



 def 				A							(						self			:					Optional[int]			):


    '''simple docstring'''


    with self.assertRaises(lowercase			):
       ConfigMixin.load_config('dummy_path'			)



 def 				A							(						self			:					Optional[Any]			):


    '''simple docstring'''


    _snake_case						=    SampleObject()
    _snake_case						=    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
    _snake_case						=    SampleObject(_name_or_path='lalala'			)
    _snake_case						=    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
    _snake_case						=    SampleObject(c=6			)
    _snake_case						=    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.
    _snake_case						=    SampleObject(1    ,						c=6			)
    _snake_case						=    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			:					Union[str, Any]			):


    '''simple docstring'''


    _snake_case						=    SampleObject()
    _snake_case						=    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			)
       _snake_case						=    SampleObject.from_config(SampleObject.load_config(lowercase			)			)
       _snake_case						=    new_obj.config

    # unfreeze configs
    _snake_case						=    dict(lowercase			)
    _snake_case						=    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 				A							(						self			:					List[Any]			):


    '''simple docstring'''


    _snake_case						=    logging.get_logger('diffusers.configuration_utils'			)
    # 30 for warning
    logger.setLevel(30			)

    with CaptureLogger(lowercase			) as cap_logger:
       _snake_case						=    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			:					Any			):


    '''simple docstring'''


    _snake_case						=    logging.get_logger('diffusers.configuration_utils'			)
    # 30 for warning
    logger.setLevel(30			)

    with CaptureLogger(lowercase			) as cap_logger:
       _snake_case						=    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			:					Dict			):


    '''simple docstring'''


    _snake_case						=    logging.get_logger('diffusers.configuration_utils'			)
    # 30 for warning
    logger.setLevel(30			)

    with CaptureLogger(lowercase			) as cap_logger:
       _snake_case						=    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[int]			):


    '''simple docstring'''


    _snake_case						=    logging.get_logger('diffusers.configuration_utils'			)
    # 30 for warning
    logger.setLevel(30			)

    with CaptureLogger(lowercase			) as cap_logger:
       _snake_case						=    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[Any]			):


    '''simple docstring'''


    _snake_case						=    logging.get_logger('diffusers.configuration_utils'			)
    # 30 for warning
    logger.setLevel(30			)

    with CaptureLogger(lowercase			) as cap_logger:
       _snake_case						=    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:
       _snake_case						=    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			:					str			):


    '''simple docstring'''


    _snake_case						=    logging.get_logger('diffusers.configuration_utils'			)
    # 30 for warning
    logger.setLevel(30			)

    with CaptureLogger(lowercase			) as cap_logger:
       _snake_case						=    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			:					Any			):


    '''simple docstring'''


    _snake_case						=    SampleObject()

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

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

_lowerCamelCase :       Union[str, Any]     					=    {
    0: '''underwear''',
    1: '''pants''',
    2: '''belt''',
    3: '''suit''',
    4: '''shoe''',
    5: '''socks''',
    6: '''shirt''',
    7: '''tie''',
    8: '''watch''',
}

_lowerCamelCase :       Optional[Any]     					=    [[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

_lowerCamelCase :       Dict     					=    [0 for x in range(len(graph))]
_lowerCamelCase :       Dict     					=    []






def  a_	( __lowercase     :			Optional[int] ,      __lowercase     :			Dict				)				->						Optional[int]:
			_snake_case						=    1
			while stack:
						_snake_case						=    stack.pop()
						print(__lowercase ,      clothes[current_clothing]				)
						order += 1






def  a_	( __lowercase     :			Union[str, Any] ,      __lowercase     :			Dict ,      __lowercase     :			Union[str, Any]				)				->						List[Any]:
			_snake_case						=    1
			for v in graph[u]:
						if not visited[v]:
									depth_first_search(__lowercase ,      __lowercase ,      __lowercase				)

			stack.append(__lowercase				)






def  a_	( __lowercase     :			Dict ,      __lowercase     :			int				)				->						List[str]:
			for v in range(len(__lowercase				)				):
						if not visited[v]:
									depth_first_search(__lowercase ,      __lowercase ,      __lowercase				)


if __name__ == "__main__":
			topological_sort(graph, visited)
			print(stack)
			print_stack(stack, clothes)