

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 			A						(							_UpperCAmelCase			):







				"""simple docstring"""





				lowerCamelCase		     =							42
				lowerCamelCase		     =							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 			A						(							_UpperCAmelCase			):







									"""simple docstring"""





									lowerCamelCase		     =							42
									lowerCamelCase		     =							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




import random
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     list   ,      SCREAMING_SNAKE_CASE__      :     str				)							->				tuple:





    '''simple docstring'''






    A__				,						A__				,						A__   				=       [], [], []
    for element in data:
        if element < pivot:
            less.append(SCREAMING_SNAKE_CASE__				)
        elif element > pivot:
            greater.append(SCREAMING_SNAKE_CASE__				)
        else:
            equal.append(SCREAMING_SNAKE_CASE__				)
    return less, equal, greater

def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     list   ,      SCREAMING_SNAKE_CASE__      :     int				)							->				str:





    '''simple docstring'''






    if index >= len(SCREAMING_SNAKE_CASE__				) or index < 0:
        return None

    A__   				=       items[random.randint(0   ,      len(SCREAMING_SNAKE_CASE__				) - 1				)]
    A__   				=       0
    A__				,						A__				,						A__   				=       _partition(SCREAMING_SNAKE_CASE__   ,      SCREAMING_SNAKE_CASE__				)
    A__   				=       len(SCREAMING_SNAKE_CASE__				)
    A__   				=       len(SCREAMING_SNAKE_CASE__				)

    # index is the pivot
    if m <= index < m + count:
        return pivot
    # must be in smaller
    elif m > index:
        return quick_select(SCREAMING_SNAKE_CASE__   ,      SCREAMING_SNAKE_CASE__				)
    # must be in larger
    else:
        return quick_select(SCREAMING_SNAKE_CASE__   ,      index - (m + count)				)

