


"""simple docstring"""






import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig






class     A(     lowerCamelCase__		):

		"""simple docstring"""





		A         =       CustomConfig
		def __init__(   self				,							SCREAMING_SNAKE_CASE__      )			->  Tuple:

					"""simple docstring"""



					super().__init__(SCREAMING_SNAKE_CASE__      )
					_UpperCamelCase				:int				    =  torch.nn.Linear(config.hidden_size				,							config.hidden_size      )
		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__      )			->  Tuple:

					"""simple docstring"""



					return self.linear(SCREAMING_SNAKE_CASE__      )





		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__      )			->  Any:

					"""simple docstring"""



					pass






class     A(     lowerCamelCase__		):

		"""simple docstring"""





		A         =       NoSuperInitConfig
		def __init__(   self				,							SCREAMING_SNAKE_CASE__      )			->  Optional[Any]:

					"""simple docstring"""



					super().__init__(SCREAMING_SNAKE_CASE__      )
					_UpperCamelCase				:Any				    =  torch.nn.Linear(config.attribute				,							config.attribute      )
		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__      )			->  Optional[Any]:

					"""simple docstring"""



					return self.linear(SCREAMING_SNAKE_CASE__      )





		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__      )			->  Optional[int]:

					"""simple docstring"""



					pass





"""simple docstring"""






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

import numpy as np
import PIL

from ...utils import BaseOutput, is_invisible_watermark_available, is_torch_available, is_transformers_available






@dataclass
class     A(     lowerCamelCase__		):

		"""simple docstring"""





		A         =       42


if is_transformers_available() and is_torch_available() and is_invisible_watermark_available():
					from .pipeline_stable_diffusion_xl import StableDiffusionXLPipeline
					from .pipeline_stable_diffusion_xl_imgaimg import StableDiffusionXLImgaImgPipeline

