"""simple docstring"""





import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						"M-CLIP"





				def __init__(      self							:							Optional[Any]      ,    _A							:							List[str]=1_0_2_4      ,    _A							:							Union[str, Any]=7_6_8      ,    **_A							:							Optional[Any]):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Tuple			  =    transformerDimSize
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    imageDimSize
											super().__init__(**_A)




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						MCLIPConfig





				def __init__(      self							:							Dict      ,    _A							:							Optional[Any]      ,    *_A							:							Any      ,    **_A							:							Dict):



											"""simple docstring"""







											super().__init__(_A      ,    *_A      ,    **_A)
											_SCREAMING_SNAKE_CASE		:						Tuple			  =    XLMRobertaModel(_A)
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    torch.nn.Linear(
											    in_features=config.transformerDimensions      ,    out_features=config.numDims)





				def 		_lowerCAmelCase		(      self							:							Union[str, Any]      ,    _A							:							str      ,    _A							:							int):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						str			  =    self.transformer(input_ids=_A      ,    attention_mask=_A)[0]
											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    (embs * attention_mask.unsqueeze(2)).sum(dim=1) / attention_mask.sum(dim=1)[:, None]
											return self.LinearTransformation(_A), embs



"""simple docstring"""





from __future__ import annotations



def      lowerCamelCase_(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	)->    tuple:
							if (electron_conc, hole_conc, intrinsic_conc).count(0  ) != 1:
														raise ValueError("""You cannot supply more or less than 2 values"""  )
							elif electron_conc < 0:
														raise ValueError("""Electron concentration cannot be negative in a semiconductor"""  )
							elif hole_conc < 0:
														raise ValueError("""Hole concentration cannot be negative in a semiconductor"""  )
							elif intrinsic_conc < 0:
														raise ValueError(
														    """Intrinsic concentration cannot be negative in a semiconductor"""  )
							elif electron_conc == 0:
														return (
														    "electron_conc",
														    intrinsic_conc**2 / hole_conc,
														)
							elif hole_conc == 0:
														return (
														    "hole_conc",
														    intrinsic_conc**2 / electron_conc,
														)
							elif intrinsic_conc == 0:
														return (
														    "intrinsic_conc",
														    (electron_conc * hole_conc) ** 0.5,
														)
							else:
														return (-1, -1)


if __name__ == "__main__":
			import doctest

			doctest.testmod()


