





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 SCREAMING_SNAKE_CASE_ (					lowercase_   ):





					"""simple docstring"""


					A__				 =    42
					A__				 =    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 SCREAMING_SNAKE_CASE_ (					lowercase_   ):





											"""simple docstring"""


											A__				 =    42
											A__				 =    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    __UpperCamelCase      (    a) ->str:

					if isinstance(a,     a):
										raise TypeError("'float' object cannot be interpreted as an integer")
					if isinstance(a,     a):
										raise TypeError("'str' object cannot be interpreted as an integer")

					if num == 0:
										return "0b0"

					lowerCamelCase__       =       False

					if num < 0:
										lowerCamelCase__       =       True
										lowerCamelCase__       =       -num

					lowerCamelCase__       =       []
					while num > 0:
										binary.insert(0,     num % 2)
										num >>= 1

					if negative:
										return "-0b" + "".join(str(a) for e in binary)

					return "0b" + "".join(str(a) for e in binary)


if __name__ == "__main__":
						import doctest

						doctest.testmod()

