



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        snake_case__    (A__		):







						"""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        snake_case__    (A__		):







								"""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









from string import ascii_uppercase

_lowercase		:				str      		={char: i for i, char in enumerate(ascii_uppercase)}
_lowercase		:				Dict      		=dict(enumerate(ascii_uppercase))

def      lowerCAmelCase_					(  _lowercase    :       str						,       _lowercase    :       str)							->	str:







			"""simple docstring"""
			a__       :						Any							=  len(_lowercase)
			a__       :						Optional[int]							=  0
			while True:
						if x == i:
									a__       :						Optional[Any]							=  0
						if len(_lowercase) == len(_lowercase):
									break
						key += key[i]
						i += 1
			return key

def      lowerCAmelCase_					(  _lowercase    :       str						,       _lowercase    :       str)							->	str:







			"""simple docstring"""
			a__       :						Tuple							=  """"""
			a__       :						str							=  0
			for letter in message:
						if letter == " ":
									cipher_text += " "
						else:
									a__       :						List[str]							=  (dicta[letter] - dicta[key_new[i]]) % 26
									i += 1
									cipher_text += dicta[x]
			return cipher_text

def      lowerCAmelCase_					(  _lowercase    :       str						,       _lowercase    :       str)							->	str:







			"""simple docstring"""
			a__       :						int							=  """"""
			a__       :						int							=  0
			for letter in cipher_text:
						if letter == " ":
									or_txt += " "
						else:
									a__       :						Dict							=  (dicta[letter] + dicta[key_new[i]] + 26) % 26
									i += 1
									or_txt += dicta[x]
			return or_txt

def      lowerCAmelCase_					(  )							->	None:







			"""simple docstring"""
			a__       :						List[Any]							=  """THE GERMAN ATTACK"""
			a__       :						List[Any]							=  """SECRET"""
			a__       :						Tuple							=  generate_key(_lowercase						,       _lowercase)
			a__       :						str							=  cipher_text(_lowercase						,       _lowercase)
			print(F'''Encrypted Text = {s}''')
			print(F'''Original Text = {original_text(_lowercase						,       _lowercase)}''')


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()




