






"""simple docstring"""





import warnings

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCamelCase							=  logging.get_logger(__name__)

__lowerCamelCase							=  {
    'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/config.json',
    'xlnet-large-cased': 'https://huggingface.co/xlnet-large-cased/resolve/main/config.json',
}



class       __A		(   SCREAMING_SNAKE_CASE_			):
					UpperCAmelCase__								=				"xlnet"
					UpperCAmelCase__								=				["mems"]
					UpperCAmelCase__								=				{
					    "n_token": "vocab_size",  # Backward compatibility
					    "hidden_size": "d_model",
					    "num_attention_heads": "n_head",
					    "num_hidden_layers": "n_layer",
					}

					def __init__(			self  :      Optional[Any]     ,		__snake_case  :      int=3_2_0_0_0     ,		__snake_case  :      Tuple=1_0_2_4     ,		__snake_case  :      List[str]=2_4     ,		__snake_case  :      Dict=1_6     ,		__snake_case  :      Tuple=4_0_9_6     ,		__snake_case  :      str="gelu"     ,		__snake_case  :      Dict=True     ,		__snake_case  :      Optional[Any]="bi"     ,		__snake_case  :      Any=0.02     ,		__snake_case  :      Tuple=1E-12     ,		__snake_case  :      List[str]=0.1     ,		__snake_case  :      Any=5_1_2     ,		__snake_case  :      Optional[int]=None     ,		__snake_case  :      Any=True     ,		__snake_case  :      List[str]=False     ,		__snake_case  :      Dict=False     ,		__snake_case  :      List[Any]=-1     ,		__snake_case  :      List[Any]=False     ,		__snake_case  :      Tuple="last"     ,		__snake_case  :      Optional[Any]=True     ,		__snake_case  :      List[str]="tanh"     ,		__snake_case  :      Any=0.1     ,		__snake_case  :      str=5     ,		__snake_case  :      Optional[Any]=5     ,		__snake_case  :      List[str]=5     ,		__snake_case  :      str=1     ,		__snake_case  :      Dict=2     ,		**__snake_case  :      Dict     ,		)			->							Optional[int]:
											__magic_name__:	Dict							=       vocab_size
											__magic_name__:	List[Any]							=       d_model
											__magic_name__:	int							=       n_layer
											__magic_name__:	List[Any]							=       n_head
											if d_model % n_head != 0:
																	raise ValueError(F'\'d_model % n_head\' ({d_model % n_head}) should be equal to 0'					)
											if "d_head" in kwargs:
																	if kwargs["d_head"] != d_model // n_head:
																							raise ValueError(
																							    F'`d_head` ({kwargs["d_head"]}) should be equal to `d_model // n_head` ({d_model // n_head})'					)
											__magic_name__:	str							=       d_model // n_head
											__magic_name__:	Optional[Any]							=       ff_activation
											__magic_name__:	Tuple							=       d_inner
											__magic_name__:	int							=       untie_r
											__magic_name__:	Optional[Any]							=       attn_type

											__magic_name__:	str							=       initializer_range
											__magic_name__:	List[Any]							=       layer_norm_eps

											__magic_name__:	Union[str, Any]							=       dropout
											__magic_name__:	List[Any]							=       mem_len
											__magic_name__:	str							=       reuse_len
											__magic_name__:	int							=       bi_data
											__magic_name__:	Optional[int]							=       clamp_len
											__magic_name__:	str							=       same_length

											__magic_name__:	Tuple							=       summary_type
											__magic_name__:	List[Any]							=       summary_use_proj
											__magic_name__:	Union[str, Any]							=       summary_activation
											__magic_name__:	Tuple							=       summary_last_dropout
											__magic_name__:	Union[str, Any]							=       start_n_top
											__magic_name__:	Optional[int]							=       end_n_top

											__magic_name__:	Tuple							=       bos_token_id
											__magic_name__:	int							=       pad_token_id
											__magic_name__:	List[Any]							=       eos_token_id

											if "use_cache" in kwargs:
																	warnings.warn(
																	    """The `use_cache` argument is deprecated and will be removed in a future version, use `use_mems_eval`"""
																	    """ instead."""     ,		__snake_case     ,		)
																	__magic_name__:	int							=       kwargs["""use_cache"""]

											__magic_name__:	str							=       use_mems_eval
											__magic_name__:	List[str]							=       use_mems_train
											super().__init__(pad_token_id=__snake_case     ,		bos_token_id=__snake_case     ,		eos_token_id=__snake_case     ,		**__snake_case					)

					@property
					def   lowerCamelCase__   (			self  :      Dict					)			->							Any:
											logger.info(F'The model {self.model_type} is one of the few models that has no sequence length limit.'					)
											return -1






					@max_position_embeddings.setter
					def   lowerCamelCase__   (			self  :      Tuple     ,		__snake_case  :      Optional[Any]					)			->							str:
											# Message copied from Transformer-XL documentation
											raise NotImplementedError(
											    F'The model {self.model_type} is one of the few models that has no sequence length limit.'					)








'''simple docstring'''





def 			a_	(				_lowerCAmelCase			,_lowerCAmelCase			) -> tuple[float, float]:

  # Check if the input is valid
  if not len(_lowerCAmelCase			) == len(_lowerCAmelCase			) == 3:
    raise ValueError('Please enter a valid equation.'			)
  if equationa[0] == equationa[1] == equationa[0] == equationa[1] == 0:
    raise ValueError('Both a & b of two equations can\'t be zero.'			)

  # Extract the coefficients
  __lowerCamelCase			,__lowerCamelCase			,__lowerCamelCase			:			Union[str, Any]       			=					equationa
  __lowerCamelCase			,__lowerCamelCase			,__lowerCamelCase			:			Any       			=					equationa

  # Calculate the determinants of the matrices
  __lowerCamelCase			:			Union[str, Any]       			=					aa * ba - aa * ba
  __lowerCamelCase			:			Dict       			=					ca * ba - ca * ba
  __lowerCamelCase			:			List[str]       			=					aa * ca - aa * ca

  # Check if the system of linear equations has a solution (using Cramer's rule)
  if determinant == 0:
    if determinant_x == determinant_y == 0:
      raise ValueError('Infinite solutions. (Consistent system)'			)
    else:
      raise ValueError('No solution. (Inconsistent system)'			)
  else:
    if determinant_x == determinant_y == 0:
      # Trivial solution (Inconsistent system)
      return (0.0, 0.0)
    else:
      __lowerCamelCase			:			Tuple       			=					determinant_x / determinant
      __lowerCamelCase			:			Union[str, Any]       			=					determinant_y / determinant
      # Non-Trivial Solution (Consistent system)
      return (x, y)






