code: 
  
  
  
  
  
  
  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
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  import random
  
  
  
  
  
  
  
  class 							UpperCAmelCase_     :
  
  
  
  
       def __init__(							self  ,	_lowerCAmelCase  ,	_lowerCAmelCase		):
            UpperCAmelCase__			:     Union[str, Any]										= x
            UpperCAmelCase__			:     Union[str, Any]										= y
  
  
  
  
       def      __UpperCAmelCase     (							self		):
            return (self.x**2 + self.y**2) <= 1
  
  
  
  
       @classmethod
       def      __UpperCAmelCase     (							cls		):
            return cls(x=random.random()  ,	y=random.random()		)
  
  
  
  
  
  def    _lowerCamelCase	(	__lowerCamelCase					)   -> float:
  
       '''simple docstring'''
       if number_of_simulations < 1:
            raise ValueError("""At least one simulation is necessary to estimate PI."""					)
  
       UpperCAmelCase__			:     Dict										= 0
       for _ in range(__lowerCamelCase					):
            UpperCAmelCase__			:     Union[str, Any]										= Point.random_unit_square()
  
            if random_point.is_in_unit_circle():
                 number_in_unit_circle += 1
  
       return 4 * number_in_unit_circle / number_of_simulations
  
  
  if __name__ == "__main__":
        # import doctest
  
        # doctest.testmod()
        from math import pi
  
        SCREAMING_SNAKE_CASE__		:       List[str]   							=							"""Please enter the desired number of Monte Carlo simulations: """
        SCREAMING_SNAKE_CASE__		:       int   							=							estimate_pi(int(input(prompt).strip()))
        print(f'''An estimate of PI is {my_pi} with an error of {abs(my_pi - pi)}''')
  
  
  
  
  
  
  