
"""simple docstring"""


SCREAMING_SNAKE_CASE      =     [
    (1_000, """M"""),
    (900, """CM"""),
    (500, """D"""),
    (400, """CD"""),
    (100, """C"""),
    (90, """XC"""),
    (50, """L"""),
    (40, """XL"""),
    (10, """X"""),
    (9, """IX"""),
    (5, """V"""),
    (4, """IV"""),
    (1, """I"""),
]



def 	lowerCamelCase__			(							UpperCAmelCase_				)->							int:







       """simple docstring"""
       UpperCamelCase					 =		{"I": 1, "V": 5, "X": 10, "L": 50, "C": 1_00, "D": 5_00, "M": 10_00}
       UpperCamelCase					 =		0
       UpperCamelCase					 =		0
       while place < len(UpperCAmelCase_				):
              if (place + 1 < len(UpperCAmelCase_				)) and (vals[roman[place]] < vals[roman[place + 1]]):
                     total += vals[roman[place + 1]] - vals[roman[place]]
                     place += 2
              else:
                     total += vals[roman[place]]
                     place += 1
       return total



def 	lowerCamelCase__			(							UpperCAmelCase_				)->							str:







       """simple docstring"""
       UpperCamelCase					 =		[]
       for arabic, roman in ROMAN:
              ((UpperCamelCase) ,       (UpperCamelCase))					 =		divmod(UpperCAmelCase_		,      UpperCAmelCase_				)
              result.append(roman * factor				)
              if number == 0:
                     break
       return "".join(UpperCAmelCase_				)


if __name__ == "__main__":
      import doctest

      doctest.testmod()







"""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   __a  (      _lowerCAmelCase	):
       UpperCamelCase_		:					Union[List[PIL.Image.Image], np.ndarray]
       UpperCamelCase_		:					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   __a  (      _lowerCAmelCase	):
             UpperCamelCase_		:					np.ndarray
             UpperCamelCase_		:					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





