


"""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 		snake_case_(							a__      ):
     __UpperCamelCase	=       '''config.json'''






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



class 		snake_case_(							a__      ):
     __UpperCamelCase	=       '''config.json'''






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



class 		snake_case_(							a__      ):
     __UpperCamelCase	=       '''config.json'''






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



class 		snake_case_(							a__      ):
     __UpperCamelCase	=       '''config.json'''






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



class 		snake_case_(							unittest.TestCase      ):






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






     def   lowerCamelCase__  (						self	:       Dict					):
           lowerCAmelCase       :						Union[str, Any]							= SampleObject()
           lowerCAmelCase       :						Tuple							= 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       :						Any							= SampleObject(_name_or_path='''lalala'''					)
           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]

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

           with tempfile.TemporaryDirectory() as tmpdirname:
                 obj.save_config(UpperCamelCase_					)
                 lowerCAmelCase       :						Optional[int]							= SampleObject.from_config(SampleObject.load_config(UpperCamelCase_					)					)
                 lowerCAmelCase       :						List[Any]							= new_obj.config

           # unfreeze configs
           lowerCAmelCase       :						List[Any]							= dict(UpperCamelCase_					)
           lowerCAmelCase       :						Tuple							= dict(UpperCamelCase_					)

           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   lowerCamelCase__  (						self	:       List[str]					):
           lowerCAmelCase       :						int							= logging.get_logger('''diffusers.configuration_utils'''					)
           # 30 for warning
           logger.setLevel(3_0					)

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

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

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

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

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

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

           with CaptureLogger(UpperCamelCase_					) 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   lowerCamelCase__  (						self	:       List[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       :						str							= SampleObject()

           lowerCAmelCase       :						List[Any]							= {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(UpperCamelCase_					)

                 # now loading it with SampleObject2 should put f into `_use_default_values`
                 lowerCAmelCase       :						Union[str, Any]							= SampleObjecta.from_config(UpperCamelCase_					)

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

           config.config._use_default_values.pop()
           lowerCAmelCase       :						Optional[Any]							= 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"""





import math as m


def   _snake_case    (    _snake_case					:      List[Any]			, _snake_case					:      Tuple			, _snake_case					:      Tuple=0.001      ):
      return (f(a + h      ) - f(a - h      )) / (2 * h)


def   _snake_case    (    _snake_case					:      int			, _snake_case					:      List[Any]=0			, _snake_case					:      Any=100			, _snake_case					:      Any=0.0001			, _snake_case					:      Optional[Any]=1E-6			, _snake_case					:      Any=False      ):
      lowerCAmelCase       :						Optional[Any]							= xa  # set the initial guess
      lowerCAmelCase       :						str							= [a]
      lowerCAmelCase       :						List[str]							= abs(f(_snake_case      )      )
      lowerCAmelCase       :						Dict							= lambda _snake_case      : calc_derivative(_snake_case			, _snake_case			, h=_snake_case      )  # noqa: E731  Derivative of f(x)
      for _ in range(_snake_case      ):
            if fa(_snake_case      ) == 0:
                  raise ValueError('''No converging solution found'''      )
            lowerCAmelCase       :						Tuple							= a - f(_snake_case      ) / fa(_snake_case      )  # Calculate the next estimate
            if logsteps:
                  steps.append(_snake_case      )
            if error < maxerror:
                  break
      else:
            raise ValueError('''Iteration limit reached, no converging solution found'''      )
      if logsteps:
            # If logstep is true, then log intermediate steps
            return a, error, steps
      return a, error


if __name__ == "__main__":
 from matplotlib import pyplot as plt

 snake_case__		:  Any     					=					lambda x: m.tanh(x) ** 2 - m.exp(3 * x)  # noqa: E731
 snake_case__					,  snake_case__					,  snake_case__		:  List[str]     					=					newton_raphson(
     f, xa=10, maxiter=1_000, step=1e-6, logsteps=True
 )
 plt.plot([abs(f(x)) for x in steps])
 plt.xlabel('''step''')
 plt.ylabel('''error''')
 plt.show()
 print(f"""solution = {{{solution:f}}}, error = {{{error:f}}}""")


