

from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import (
    BaseOutput,
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_k_diffusion_available,
    is_k_diffusion_version,
    is_onnx_available,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)




@dataclass
class      UpperCamelCase (     a__   ):
    __UpperCamelCase         =42
    __UpperCamelCase         =42


try:
      if not (is_transformers_available() and is_torch_available()):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
      from .pipeline_cycle_diffusion import CycleDiffusionPipeline
      from .pipeline_stable_diffusion import StableDiffusionPipeline
      from .pipeline_stable_diffusion_attend_and_excite import StableDiffusionAttendAndExcitePipeline
      from .pipeline_stable_diffusion_imgaimg import StableDiffusionImgaImgPipeline
      from .pipeline_stable_diffusion_inpaint import StableDiffusionInpaintPipeline
      from .pipeline_stable_diffusion_inpaint_legacy import StableDiffusionInpaintPipelineLegacy
      from .pipeline_stable_diffusion_instruct_pixapix import StableDiffusionInstructPixaPixPipeline
      from .pipeline_stable_diffusion_latent_upscale import StableDiffusionLatentUpscalePipeline
      from .pipeline_stable_diffusion_ldmad import StableDiffusionLDMaDPipeline
      from .pipeline_stable_diffusion_model_editing import StableDiffusionModelEditingPipeline
      from .pipeline_stable_diffusion_panorama import StableDiffusionPanoramaPipeline
      from .pipeline_stable_diffusion_paradigms import StableDiffusionParadigmsPipeline
      from .pipeline_stable_diffusion_sag import StableDiffusionSAGPipeline
      from .pipeline_stable_diffusion_upscale import StableDiffusionUpscalePipeline
      from .pipeline_stable_unclip import StableUnCLIPPipeline
      from .pipeline_stable_unclip_imgaimg import StableUnCLIPImgaImgPipeline
      from .safety_checker import StableDiffusionSafetyChecker
      from .stable_unclip_image_normalizer import StableUnCLIPImageNormalizer

try:
      if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_torch_and_transformers_objects import StableDiffusionImageVariationPipeline
else:
      from .pipeline_stable_diffusion_image_variation import StableDiffusionImageVariationPipeline


try:
      if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.26.0")):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_torch_and_transformers_objects import (
          StableDiffusionDepthaImgPipeline,
          StableDiffusionDiffEditPipeline,
          StableDiffusionPixaPixZeroPipeline,
      )
else:
      from .pipeline_stable_diffusion_depthaimg import StableDiffusionDepthaImgPipeline
      from .pipeline_stable_diffusion_diffedit import StableDiffusionDiffEditPipeline
      from .pipeline_stable_diffusion_pixapix_zero import StableDiffusionPixaPixZeroPipeline


try:
      if not (
          is_torch_available()
          and is_transformers_available()
          and is_k_diffusion_available()
          and is_k_diffusion_version(">=", "0.0.12")
      ):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_torch_and_transformers_and_k_diffusion_objects import *  # noqa F403
else:
      from .pipeline_stable_diffusion_k_diffusion import StableDiffusionKDiffusionPipeline

try:
      if not (is_transformers_available() and is_onnx_available()):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_onnx_objects import *  # noqa F403
else:
      from .pipeline_onnx_stable_diffusion import OnnxStableDiffusionPipeline, StableDiffusionOnnxPipeline
      from .pipeline_onnx_stable_diffusion_imgaimg import OnnxStableDiffusionImgaImgPipeline
      from .pipeline_onnx_stable_diffusion_inpaint import OnnxStableDiffusionInpaintPipeline
      from .pipeline_onnx_stable_diffusion_inpaint_legacy import OnnxStableDiffusionInpaintPipelineLegacy
      from .pipeline_onnx_stable_diffusion_upscale import OnnxStableDiffusionUpscalePipeline

if is_transformers_available() and is_flax_available():
      import flax




      @flax.struct.dataclass
      class      UpperCamelCase (     a__   ):
          __UpperCamelCase         =42
          __UpperCamelCase         =42


      from ...schedulers.scheduling_pndm_flax import PNDMSchedulerState
      from .pipeline_flax_stable_diffusion import FlaxStableDiffusionPipeline
      from .pipeline_flax_stable_diffusion_imgaimg import FlaxStableDiffusionImgaImgPipeline
      from .pipeline_flax_stable_diffusion_inpaint import FlaxStableDiffusionInpaintPipeline
      from .safety_checker_flax import FlaxStableDiffusionSafetyChecker


def        __lowerCAmelCase    (       _UpperCamelCase		:  int	)		->							int:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE								=			abs(_UpperCamelCase	)
 SCREAMING_SNAKE_CASE								=			0
 while n > 0:
  res += n % 10
  n //= 10
 return res


def        __lowerCAmelCase    (       _UpperCamelCase		:  int	)		->							int:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE								=			abs(_UpperCamelCase	)
 return n if n < 10 else n % 10 + sum_of_digits(n // 10	)


def        __lowerCAmelCase    (       _UpperCamelCase		:  int	)		->							int:
 '''simple docstring'''


 return sum(int(_UpperCamelCase	) for c in str(abs(_UpperCamelCase	)	)	)


def        __lowerCAmelCase    (       )		->							None:
 '''simple docstring'''


 from collections.abc import Callable
 from timeit import timeit

 def benchmark_a_function(_UpperCamelCase		:  Callable		,							_UpperCamelCase		:  int	) -> None:
  SCREAMING_SNAKE_CASE								=			f"""{func.__name__}({value})"""
  SCREAMING_SNAKE_CASE								=			timeit(f"""__main__.{call}"""		,							setup='import __main__'	)
  print(f"""{call:56} = {func(_UpperCamelCase	)} -- {timing:.4f} seconds"""	)

 for value in (26_21_44, 11_25_89_99_06_84_26_24, 1_26_76_50_60_02_28_22_94_01_49_67_03_20_53_76):
  for func in (sum_of_digits, sum_of_digits_recursion, sum_of_digits_compact):
   benchmark_a_function(_UpperCamelCase		,							_UpperCamelCase	)
  print()


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      benchmark()

