





from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available



@dataclass
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class 							_UpperCamelCase    (		lowerCAmelCase_   ):
       _UpperCamelCase :    Tuple   			=      4_2
       _UpperCamelCase :    List[str]   			=      4_2


if is_transformers_available() and is_torch_available():
     from .modeling_roberta_series import RobertaSeriesModelWithTransformation
     from .pipeline_alt_diffusion import AltDiffusionPipeline
     from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline







def 					snake_case					(							A			)							->							int:




	'''simple docstring'''


	if not isinstance(A						,   A			):
		raise ValueError('double_factorial() only accepts integral values'			)
	if n < 0:
		raise ValueError('double_factorial() not defined for negative values'			)
	return 1 if n <= 1 else n * double_factorial(n - 2			)


if __name__ == "__main__":
							import doctest

							doctest.testmod()
