'''simple docstring'''




from ..utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_invisible_watermark_available,
    is_k_diffusion_available,
    is_librosa_available,
    is_note_seq_available,
    is_onnx_available,
    is_torch_available,
    is_transformers_available,
)


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_pt_objects import *  # noqa F403
else:
  from .consistency_models import ConsistencyModelPipeline
  from .dance_diffusion import DanceDiffusionPipeline
  from .ddim import DDIMPipeline
  from .ddpm import DDPMPipeline
  from .dit import DiTPipeline
  from .latent_diffusion import LDMSuperResolutionPipeline
  from .latent_diffusion_uncond import LDMPipeline
  from .pipeline_utils import AudioPipelineOutput, DiffusionPipeline, ImagePipelineOutput
  from .pndm import PNDMPipeline
  from .repaint import RePaintPipeline
  from .score_sde_ve import ScoreSdeVePipeline
  from .stochastic_karras_ve import KarrasVePipeline

try:
  if not (is_torch_available() and is_librosa_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_torch_and_librosa_objects import *  # noqa F403
else:
  from .audio_diffusion import AudioDiffusionPipeline, Mel

try:
  if not (is_torch_available() and is_transformers_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
  from .alt_diffusion import AltDiffusionImgaImgPipeline, AltDiffusionPipeline
  from .audioldm import AudioLDMPipeline
  from .controlnet import (
      StableDiffusionControlNetImgaImgPipeline,
      StableDiffusionControlNetInpaintPipeline,
      StableDiffusionControlNetPipeline,
  )
  from .deepfloyd_if import (
      IFImgaImgPipeline,
      IFImgaImgSuperResolutionPipeline,
      IFInpaintingPipeline,
      IFInpaintingSuperResolutionPipeline,
      IFPipeline,
      IFSuperResolutionPipeline,
  )
  from .kandinsky import (
      KandinskyImgaImgPipeline,
      KandinskyInpaintPipeline,
      KandinskyPipeline,
      KandinskyPriorPipeline,
  )
  from .kandinskya_a import (
      KandinskyVaaControlnetImgaImgPipeline,
      KandinskyVaaControlnetPipeline,
      KandinskyVaaImgaImgPipeline,
      KandinskyVaaInpaintPipeline,
      KandinskyVaaPipeline,
      KandinskyVaaPriorEmbaEmbPipeline,
      KandinskyVaaPriorPipeline,
  )
  from .latent_diffusion import LDMTextToImagePipeline
  from .paint_by_example import PaintByExamplePipeline
  from .semantic_stable_diffusion import SemanticStableDiffusionPipeline
  from .shap_e import ShapEImgaImgPipeline, ShapEPipeline
  from .stable_diffusion import (
      CycleDiffusionPipeline,
      StableDiffusionAttendAndExcitePipeline,
      StableDiffusionDepthaImgPipeline,
      StableDiffusionDiffEditPipeline,
      StableDiffusionImageVariationPipeline,
      StableDiffusionImgaImgPipeline,
      StableDiffusionInpaintPipeline,
      StableDiffusionInpaintPipelineLegacy,
      StableDiffusionInstructPixaPixPipeline,
      StableDiffusionLatentUpscalePipeline,
      StableDiffusionLDMaDPipeline,
      StableDiffusionModelEditingPipeline,
      StableDiffusionPanoramaPipeline,
      StableDiffusionParadigmsPipeline,
      StableDiffusionPipeline,
      StableDiffusionPixaPixZeroPipeline,
      StableDiffusionSAGPipeline,
      StableDiffusionUpscalePipeline,
      StableUnCLIPImgaImgPipeline,
      StableUnCLIPPipeline,
  )
  from .stable_diffusion_safe import StableDiffusionPipelineSafe
  from .text_to_video_synthesis import TextToVideoSDPipeline, TextToVideoZeroPipeline, VideoToVideoSDPipeline
  from .unclip import UnCLIPImageVariationPipeline, UnCLIPPipeline
  from .unidiffuser import ImageTextPipelineOutput, UniDiffuserModel, UniDiffuserPipeline, UniDiffuserTextDecoder
  from .versatile_diffusion import (
      VersatileDiffusionDualGuidedPipeline,
      VersatileDiffusionImageVariationPipeline,
      VersatileDiffusionPipeline,
      VersatileDiffusionTextToImagePipeline,
  )
  from .vq_diffusion import VQDiffusionPipeline


try:
  if not (is_torch_available() and is_transformers_available() and is_invisible_watermark_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_torch_and_transformers_and_invisible_watermark_objects import *  # noqa F403
else:
  from .stable_diffusion_xl import StableDiffusionXLImgaImgPipeline, StableDiffusionXLPipeline

try:
  if not is_onnx_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_onnx_objects import *  # noqa F403
else:
  from .onnx_utils import OnnxRuntimeModel

try:
  if not (is_torch_available() and is_transformers_available() and is_onnx_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_torch_and_transformers_and_onnx_objects import *  # noqa F403
else:
  from .stable_diffusion import (
      OnnxStableDiffusionImgaImgPipeline,
      OnnxStableDiffusionInpaintPipeline,
      OnnxStableDiffusionInpaintPipelineLegacy,
      OnnxStableDiffusionPipeline,
      OnnxStableDiffusionUpscalePipeline,
      StableDiffusionOnnxPipeline,
  )

try:
  if not (is_torch_available() and is_transformers_available() and is_k_diffusion_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_torch_and_transformers_and_k_diffusion_objects import *  # noqa F403
else:
  from .stable_diffusion import StableDiffusionKDiffusionPipeline

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_flax_objects import *  # noqa F403
else:
  from .pipeline_flax_utils import FlaxDiffusionPipeline


try:
  if not (is_flax_available() and is_transformers_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_flax_and_transformers_objects import *  # noqa F403
else:
  from .controlnet import FlaxStableDiffusionControlNetPipeline
  from .stable_diffusion import (
      FlaxStableDiffusionImgaImgPipeline,
      FlaxStableDiffusionInpaintPipeline,
      FlaxStableDiffusionPipeline,
  )
try:
  if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
  from .spectrogram_diffusion import MidiProcessor, SpectrogramDiffusionPipeline







'''simple docstring'''




__snake_case   :      List[Any]						    =  [chr(i) for i in range(32, 126)]
__snake_case   :      Dict						    =  list(range(len(alphabets)))
__snake_case   :      Dict						    =  list(range(len(alphabets)))
__snake_case   :      Dict						    =  list(range(len(alphabets)))
__snake_case   :      List[Any]						    =  list(reversed(range(len(alphabets))))
__snake_case   :      Optional[int]						    =  []
__snake_case   :      List[Any]						    =  0





def      _UpperCAmelCase    (							)	->      Any:
    global gear_one_pos
    global gear_two_pos
    global gear_three_pos
    A_     =   gear_one[0]
    gear_one.append(_UpperCamelCase   )
    del gear_one[0]
    gear_one_pos += 1
    if gear_one_pos % int(len(_UpperCamelCase   )   ) == 0:
        A_     =   gear_two[0]
        gear_two.append(_UpperCamelCase   )
        del gear_two[0]
        gear_two_pos += 1
        if gear_two_pos % int(len(_UpperCamelCase   )   ) == 0:
            A_     =   gear_three[0]
            gear_three.append(_UpperCamelCase   )
            del gear_three[0]
            gear_three_pos += 1





def      _UpperCAmelCase    (							_UpperCamelCase    :	Tuple   )	->      Any:
    A_     =   alphabets.index(_UpperCamelCase   )
    A_     =   gear_one[target]
    A_     =   gear_two[target]
    A_     =   gear_three[target]
    A_     =   reflector[target]
    A_     =   gear_three.index(_UpperCamelCase   )
    A_     =   gear_two.index(_UpperCamelCase   )
    A_     =   gear_one.index(_UpperCamelCase   )
    code.append(alphabets[target]   )
    rotator()


if __name__ == "__main__":
  __snake_case   :      List[str]						    =  list(input('Type your message:\n'))
  while True:
    try:
      __snake_case   :      Any						    =  int(input('Please set token:(must be only digits)\n'))
      break
    except Exception as error:
      print(error)
  for _ in range(token):
    rotator()
  for j in decode:
    engine(j)
  print('\n' + ''.join(code))
  print(
      F"""\nYour Token is {token} please write it down.\nIf you want to decode """
      'this message again you should input same digits as token!'
  )






