


'''simple docstring'''







A__:    List[Any]					    =       '''0.18.2'''

from .configuration_utils import ConfigMixin
from .utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_inflect_available,
    is_invisible_watermark_available,
    is_k_diffusion_available,
    is_k_diffusion_version,
    is_librosa_available,
    is_note_seq_available,
    is_onnx_available,
    is_scipy_available,
    is_torch_available,
    is_torchsde_available,
    is_transformers_available,
    is_transformers_version,
    is_unidecode_available,
    logging,
)


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

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from .utils.dummy_pt_objects import *  # noqa F403
else:
   from .models import (
       AutoencoderKL,
       ControlNetModel,
       ModelMixin,
       PriorTransformer,
       TaFilmDecoder,
       TransformeraDModel,
       UNetaDModel,
       UNetaDConditionModel,
       UNetaDModel,
       UNetaDConditionModel,
       VQModel,
   )
   from .optimization import (
       get_constant_schedule,
       get_constant_schedule_with_warmup,
       get_cosine_schedule_with_warmup,
       get_cosine_with_hard_restarts_schedule_with_warmup,
       get_linear_schedule_with_warmup,
       get_polynomial_decay_schedule_with_warmup,
       get_scheduler,
   )
   from .pipelines import (
       AudioPipelineOutput,
       ConsistencyModelPipeline,
       DanceDiffusionPipeline,
       DDIMPipeline,
       DDPMPipeline,
       DiffusionPipeline,
       DiTPipeline,
       ImagePipelineOutput,
       KarrasVePipeline,
       LDMPipeline,
       LDMSuperResolutionPipeline,
       PNDMPipeline,
       RePaintPipeline,
       ScoreSdeVePipeline,
   )
   from .schedulers import (
       CMStochasticIterativeScheduler,
       DDIMInverseScheduler,
       DDIMParallelScheduler,
       DDIMScheduler,
       DDPMParallelScheduler,
       DDPMScheduler,
       DEISMultistepScheduler,
       DPMSolverMultistepInverseScheduler,
       DPMSolverMultistepScheduler,
       DPMSolverSinglestepScheduler,
       EulerAncestralDiscreteScheduler,
       EulerDiscreteScheduler,
       HeunDiscreteScheduler,
       IPNDMScheduler,
       KarrasVeScheduler,
       KDPMaAncestralDiscreteScheduler,
       KDPMaDiscreteScheduler,
       PNDMScheduler,
       RePaintScheduler,
       SchedulerMixin,
       ScoreSdeVeScheduler,
       UnCLIPScheduler,
       UniPCMultistepScheduler,
       VQDiffusionScheduler,
   )
   from .training_utils import EMAModel

try:
   if not (is_torch_available() and is_scipy_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from .utils.dummy_torch_and_scipy_objects import *  # noqa F403
else:
   from .schedulers import LMSDiscreteScheduler

try:
   if not (is_torch_available() and is_torchsde_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from .utils.dummy_torch_and_torchsde_objects import *  # noqa F403
else:
   from .schedulers import DPMSolverSDEScheduler

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 .pipelines import (
       AltDiffusionImgaImgPipeline,
       AltDiffusionPipeline,
       AudioLDMPipeline,
       CycleDiffusionPipeline,
       IFImgaImgPipeline,
       IFImgaImgSuperResolutionPipeline,
       IFInpaintingPipeline,
       IFInpaintingSuperResolutionPipeline,
       IFPipeline,
       IFSuperResolutionPipeline,
       ImageTextPipelineOutput,
       KandinskyImgaImgPipeline,
       KandinskyInpaintPipeline,
       KandinskyPipeline,
       KandinskyPriorPipeline,
       KandinskyVaaControlnetImgaImgPipeline,
       KandinskyVaaControlnetPipeline,
       KandinskyVaaImgaImgPipeline,
       KandinskyVaaInpaintPipeline,
       KandinskyVaaPipeline,
       KandinskyVaaPriorEmbaEmbPipeline,
       KandinskyVaaPriorPipeline,
       LDMTextToImagePipeline,
       PaintByExamplePipeline,
       SemanticStableDiffusionPipeline,
       ShapEImgaImgPipeline,
       ShapEPipeline,
       StableDiffusionAttendAndExcitePipeline,
       StableDiffusionControlNetImgaImgPipeline,
       StableDiffusionControlNetInpaintPipeline,
       StableDiffusionControlNetPipeline,
       StableDiffusionDepthaImgPipeline,
       StableDiffusionDiffEditPipeline,
       StableDiffusionImageVariationPipeline,
       StableDiffusionImgaImgPipeline,
       StableDiffusionInpaintPipeline,
       StableDiffusionInpaintPipelineLegacy,
       StableDiffusionInstructPixaPixPipeline,
       StableDiffusionLatentUpscalePipeline,
       StableDiffusionLDMaDPipeline,
       StableDiffusionModelEditingPipeline,
       StableDiffusionPanoramaPipeline,
       StableDiffusionParadigmsPipeline,
       StableDiffusionPipeline,
       StableDiffusionPipelineSafe,
       StableDiffusionPixaPixZeroPipeline,
       StableDiffusionSAGPipeline,
       StableDiffusionUpscalePipeline,
       StableUnCLIPImgaImgPipeline,
       StableUnCLIPPipeline,
       TextToVideoSDPipeline,
       TextToVideoZeroPipeline,
       UnCLIPImageVariationPipeline,
       UnCLIPPipeline,
       UniDiffuserModel,
       UniDiffuserPipeline,
       UniDiffuserTextDecoder,
       VersatileDiffusionDualGuidedPipeline,
       VersatileDiffusionImageVariationPipeline,
       VersatileDiffusionPipeline,
       VersatileDiffusionTextToImagePipeline,
       VideoToVideoSDPipeline,
       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 .pipelines import StableDiffusionXLImgaImgPipeline, StableDiffusionXLPipeline

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 .pipelines import StableDiffusionKDiffusionPipeline

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 .pipelines import (
       OnnxStableDiffusionImgaImgPipeline,
       OnnxStableDiffusionInpaintPipeline,
       OnnxStableDiffusionInpaintPipelineLegacy,
       OnnxStableDiffusionPipeline,
       OnnxStableDiffusionUpscalePipeline,
       StableDiffusionOnnxPipeline,
   )

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 .pipelines import AudioDiffusionPipeline, Mel

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 .pipelines import SpectrogramDiffusionPipeline

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from .utils.dummy_flax_objects import *  # noqa F403
else:
   from .models.controlnet_flax import FlaxControlNetModel
   from .models.modeling_flax_utils import FlaxModelMixin
   from .models.unet_ad_condition_flax import FlaxUNetaDConditionModel
   from .models.vae_flax import FlaxAutoencoderKL
   from .pipelines import FlaxDiffusionPipeline
   from .schedulers import (
       FlaxDDIMScheduler,
       FlaxDDPMScheduler,
       FlaxDPMSolverMultistepScheduler,
       FlaxKarrasVeScheduler,
       FlaxLMSDiscreteScheduler,
       FlaxPNDMScheduler,
       FlaxSchedulerMixin,
       FlaxScoreSdeVeScheduler,
   )


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 .pipelines import (
       FlaxStableDiffusionControlNetPipeline,
       FlaxStableDiffusionImgaImgPipeline,
       FlaxStableDiffusionInpaintPipeline,
       FlaxStableDiffusionPipeline,
   )

try:
   if not (is_note_seq_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from .utils.dummy_note_seq_objects import *  # noqa F403
else:
   from .pipelines import MidiProcessor






'''simple docstring'''







from __future__ import annotations







class A__       :






      def __init__( self			:Union[str, Any]     ,						SCREAMING_SNAKE_CASE			:str     ,						SCREAMING_SNAKE_CASE			:str	)       ->					Optional[int]:




             '''simple docstring'''
             _a					,    _a    : List[str]     					=text, pattern
             _a					,    _a    : Union[str, Any]     					=len(SCREAMING_SNAKE_CASE	), len(SCREAMING_SNAKE_CASE	)






      def __UpperCAmelCase       ( self			:Optional[int]     ,						SCREAMING_SNAKE_CASE			:str	)       ->					int:




             '''simple docstring'''

             for i in range(self.patLen - 1     ,						-1     ,						-1	):
                    if char == self.pattern[i]:
                           return i
             return -1






      def __UpperCAmelCase       ( self			:Union[str, Any]     ,						SCREAMING_SNAKE_CASE			:int	)       ->					int:




             '''simple docstring'''

             for i in range(self.patLen - 1     ,						-1     ,						-1	):
                    if self.pattern[i] != self.text[current_pos + i]:
                           return current_pos + i
             return -1






      def __UpperCAmelCase       ( self			:Union[str, Any]	)       ->					list[int]:




             '''simple docstring'''
             # searches pattern in text and returns index positions
             _a    : Union[str, Any]     					=[]
             for i in range(self.textLen - self.patLen + 1	):
                    _a    : Any     					=self.mismatch_in_text(SCREAMING_SNAKE_CASE	)
                    if mismatch_index == -1:
                           positions.append(SCREAMING_SNAKE_CASE	)
                    else:
                           _a    : int     					=self.match_in_pattern(self.text[mismatch_index]	)
                           _a    : List[str]     					=(
                               mismatch_index - match_index
                           )  # shifting index lgtm [py/multiple-definition]
             return positions

A__:    Any					    =       '''ABAABA'''
A__:    int					    =       '''AB'''
A__:    Optional[int]					    =       BoyerMooreSearch(text, pattern)
A__:    Optional[Any]					    =       bms.bad_character_heuristic()

if len(positions) == 0:
   print('''No match found''')
else:
   print('''Pattern found in following positions: ''')
   print(positions)


