



'''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 	lowerCAmelCase_(    _A					):
		'''simple docstring'''




		__lowercase							:				Optional[int]           =				4_2
		__lowercase							:				List[str]           =				4_2


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 	lowerCAmelCase_(    _A					):
			'''simple docstring'''




			__lowercase							:				Union[str, Any]           =				4_2
			__lowercase							:				Tuple           =				4_2







	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







'''simple docstring'''





_lowerCAmelCase										=     '''Input must be a string of 8 numbers plus letter'''
_lowerCAmelCase										=     '''TRWAGMYFPDXBNJZSQVHLCKE'''
def        _SCREAMING_SNAKE_CASE  (	UpperCamelCase      ):



    """simple docstring"""





    if not isinstance(UpperCamelCase							,   UpperCamelCase      ):
        lowerCAmelCase__			:  List[Any]											= f"""Expected string as input, found {type(UpperCamelCase      ).__name__}"""
        raise TypeError(UpperCamelCase      )

    lowerCAmelCase__			:  Union[str, Any]											= spanish_id.replace("""-"""							,   """"""      ).upper()
    if len(UpperCamelCase      ) != 9:
        raise ValueError(UpperCamelCase      )

    try:
        lowerCAmelCase__			:  Optional[int]											= int(spanish_id_clean[0:8]      )
        lowerCAmelCase__			:  int											= spanish_id_clean[8]
    except ValueError as ex:
        raise ValueError(UpperCamelCase      ) from ex

    if letter.isdigit():
        raise ValueError(UpperCamelCase      )

    return letter == LOOKUP_LETTERS[number % 23]


if __name__ == "__main__":
 import doctest

 doctest.testmod()


