


"""simple docstring"""






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 			lowerCamelCase_		(			lowercase   ):





				"""simple docstring"""







				_lowerCAmelCase      :      Union[List[PIL.Image.Image], np.ndarray]
				_lowerCAmelCase      :      Optional[List[bool]]


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 			lowerCamelCase_		(			lowercase   ):





					"""simple docstring"""







					_lowerCAmelCase      :      np.ndarray
					_lowerCAmelCase      :      List[bool]


	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




"""simple docstring"""






def __lowercase     (      lowerCamelCase_  :      List[Any]  ):
				SCREAMING_SNAKE_CASE__     							=				[]
				SCREAMING_SNAKE_CASE__     							=				set({"(", "[", "{"}  )
				SCREAMING_SNAKE_CASE__     							=				set({")", "]", "}"}  )
				SCREAMING_SNAKE_CASE__     							=				{"{": "}", "[": "]", "(": ")"}

				for i in range(len(lowerCamelCase_  )  ):
								if s[i] in open_brackets:
												stack.append(s[i]  )

								elif s[i] in closed_brackets and (
								    len(lowerCamelCase_  ) == 0 or (len(lowerCamelCase_  ) > 0 and open_to_closed[stack.pop()] != s[i])
								):
												return False

				return len(lowerCamelCase_  ) == 0


def __lowercase     (      ):
				SCREAMING_SNAKE_CASE__     							=				input("Enter sequence of brackets: "  )
				if is_balanced(lowerCamelCase_  ):
								print(lowerCamelCase_						,					"is balanced"  )
				else:
								print(lowerCamelCase_						,					"is not balanced"  )


if __name__ == "__main__":
	main()
