



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 		_lowercase		(							UpperCAmelCase__						):
   _UpperCAmelCase  						=      '''config.json'''

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


    """simple docstring"""






    pass



class 		_lowercase		(							UpperCAmelCase__						):
   _UpperCAmelCase  						=      '''config.json'''

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


    """simple docstring"""






    pass



class 		_lowercase		(							UpperCAmelCase__						):
   _UpperCAmelCase  						=      '''config.json'''

   @register_to_config
   def __init__(   self      :							Dict				, __lowerCAmelCase      :							str=2				, __lowerCAmelCase      :							Tuple=5				, __lowerCAmelCase      :							str=(2, 5)				, __lowerCAmelCase      :							Optional[int]="for diffusion"				, __lowerCAmelCase      :							List[str]=[1, 3]				, __lowerCAmelCase      :							str=[1, 3]				, )							->					Optional[int]:


    """simple docstring"""






    pass



class 		_lowercase		(							UpperCAmelCase__						):
   _UpperCAmelCase  						=      '''config.json'''

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


    """simple docstring"""






    pass



class 		_lowercase		(							unittest.TestCase						):

   def 		A				(   self      :							List[str]				)							->					Optional[int]:


    """simple docstring"""






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

   def 		A				(   self      :							Optional[int]				)							->					Union[str, Any]:


    """simple docstring"""






    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 		A				(   self      :							List[str]				)							->					Optional[int]:


    """simple docstring"""






    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(__lowerCAmelCase				)
     a							=		SampleObject.from_config(SampleObject.load_config(__lowerCAmelCase				)				)
     a							=		new_obj.config

    # unfreeze configs
    a							=		dict(__lowerCAmelCase				)
    a							=		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      :							Any				)							->					Union[str, Any]:


    """simple docstring"""






    a							=		logging.get_logger("diffusers.configuration_utils"				)
    # 30 for warning
    logger.setLevel(30				)

    with CaptureLogger(__lowerCAmelCase				) 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 		A				(   self      :							List[str]				)							->					str:


    """simple docstring"""






    a							=		logging.get_logger("diffusers.configuration_utils"				)
    # 30 for warning
    logger.setLevel(30				)

    with CaptureLogger(__lowerCAmelCase				) 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 		A				(   self      :							Optional[Any]				)							->					Optional[Any]:


    """simple docstring"""






    a							=		logging.get_logger("diffusers.configuration_utils"				)
    # 30 for warning
    logger.setLevel(30				)

    with CaptureLogger(__lowerCAmelCase				) 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 		A				(   self      :							Optional[int]				)							->					Tuple:


    """simple docstring"""






    a							=		logging.get_logger("diffusers.configuration_utils"				)
    # 30 for warning
    logger.setLevel(30				)

    with CaptureLogger(__lowerCAmelCase				) 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 		A				(   self      :							str				)							->					int:


    """simple docstring"""






    a							=		logging.get_logger("diffusers.configuration_utils"				)
    # 30 for warning
    logger.setLevel(30				)

    with CaptureLogger(__lowerCAmelCase				) as cap_logger:
     a							=		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:
     a							=		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      :							Any				)							->					Union[str, Any]:


    """simple docstring"""






    a							=		logging.get_logger("diffusers.configuration_utils"				)
    # 30 for warning
    logger.setLevel(30				)

    with CaptureLogger(__lowerCAmelCase				) 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 		A				(   self      :							List[str]				)							->					Dict:


    """simple docstring"""






    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(__lowerCAmelCase				)

     # now loading it with SampleObject2 should put f into `_use_default_values`
     a							=		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`
    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]






'''simple docstring'''






def        snake_case_   (	lowerCAmelCase_			,  lowerCAmelCase_						)->						float:





       '''simple docstring'''


       return a + b


if __name__ == "__main__":
   A_				:					Tuple							=      5
   A_				:					Tuple							=      6
   print(f"""The sum of {a} + {b} is {add(a, b)}""")



