'''simple docstring'''







from __future__ import annotations

from decimal import Decimal

from numpy import array


def    lowerCamelCase       (			UpperCAmelCase__				:  list[list[float]]		)			->	list[list[float]]:


							'''simple docstring'''






							SCREAMING_SNAKE_CASE__     :Optional[Any]						    = Decimal

							# Check if the provided matrix has 2 rows and 2 columns
							# since this implementation only works for 2x2 matrices
							if len(UpperCAmelCase__		) == 2 and len(matrix[0]		) == 2 and len(matrix[1]		) == 2:
														# Calculate the determinant of the matrix
														SCREAMING_SNAKE_CASE__     :Union[str, Any]						    = float(
														    d(matrix[0][0]		) * d(matrix[1][1]		) - d(matrix[1][0]		) * d(matrix[0][1]		)		)
														if determinant == 0:
																					raise ValueError('This matrix has no inverse.'		)

														# Creates a copy of the matrix with swapped positions of the elements
														SCREAMING_SNAKE_CASE__     :Optional[Any]						    = [[0.0, 0.0], [0.0, 0.0]]
														SCREAMING_SNAKE_CASE__    ,      SCREAMING_SNAKE_CASE__     :Optional[int]						    = matrix[1][1], matrix[0][0]
														SCREAMING_SNAKE_CASE__    ,      SCREAMING_SNAKE_CASE__     :List[str]						    = -matrix[1][0], -matrix[0][1]

														# Calculate the inverse of the matrix
														return [
														    [(float(d(UpperCAmelCase__		)		) / determinant) or 0.0 for n in row] for row in swapped_matrix
														]
							elif (
							    len(UpperCAmelCase__		) == 3
							    and len(matrix[0]		) == 3
							    and len(matrix[1]		) == 3
							    and len(matrix[2]		) == 3
							):
														# Calculate the determinant of the matrix using Sarrus rule
														SCREAMING_SNAKE_CASE__     :List[Any]						    = float(
														    (
														        (d(matrix[0][0]		) * d(matrix[1][1]		) * d(matrix[2][2]		))
														        + (d(matrix[0][1]		) * d(matrix[1][2]		) * d(matrix[2][0]		))
														        + (d(matrix[0][2]		) * d(matrix[1][0]		) * d(matrix[2][1]		))
														    )
														    - (
														        (d(matrix[0][2]		) * d(matrix[1][1]		) * d(matrix[2][0]		))
														        + (d(matrix[0][1]		) * d(matrix[1][0]		) * d(matrix[2][2]		))
														        + (d(matrix[0][0]		) * d(matrix[1][2]		) * d(matrix[2][1]		))
														    )		)
														if determinant == 0:
																					raise ValueError('This matrix has no inverse.'		)

														# Creating cofactor matrix
														SCREAMING_SNAKE_CASE__     :List[str]						    = [
														    [d(0.0		), d(0.0		), d(0.0		)],
														    [d(0.0		), d(0.0		), d(0.0		)],
														    [d(0.0		), d(0.0		), d(0.0		)],
														]
														SCREAMING_SNAKE_CASE__     :List[Any]						    = (d(matrix[1][1]		) * d(matrix[2][2]		)) - (
														    d(matrix[1][2]		) * d(matrix[2][1]		)
														)
														SCREAMING_SNAKE_CASE__     :List[str]						    = -(
														    (d(matrix[1][0]		) * d(matrix[2][2]		)) - (d(matrix[1][2]		) * d(matrix[2][0]		))
														)
														SCREAMING_SNAKE_CASE__     :Union[str, Any]						    = (d(matrix[1][0]		) * d(matrix[2][1]		)) - (
														    d(matrix[1][1]		) * d(matrix[2][0]		)
														)
														SCREAMING_SNAKE_CASE__     :List[str]						    = -(
														    (d(matrix[0][1]		) * d(matrix[2][2]		)) - (d(matrix[0][2]		) * d(matrix[2][1]		))
														)
														SCREAMING_SNAKE_CASE__     :int						    = (d(matrix[0][0]		) * d(matrix[2][2]		)) - (
														    d(matrix[0][2]		) * d(matrix[2][0]		)
														)
														SCREAMING_SNAKE_CASE__     :Union[str, Any]						    = -(
														    (d(matrix[0][0]		) * d(matrix[2][1]		)) - (d(matrix[0][1]		) * d(matrix[2][0]		))
														)
														SCREAMING_SNAKE_CASE__     :List[Any]						    = (d(matrix[0][1]		) * d(matrix[1][2]		)) - (
														    d(matrix[0][2]		) * d(matrix[1][1]		)
														)
														SCREAMING_SNAKE_CASE__     :Optional[Any]						    = -(
														    (d(matrix[0][0]		) * d(matrix[1][2]		)) - (d(matrix[0][2]		) * d(matrix[1][0]		))
														)
														SCREAMING_SNAKE_CASE__     :Dict						    = (d(matrix[0][0]		) * d(matrix[1][1]		)) - (
														    d(matrix[0][1]		) * d(matrix[1][0]		)
														)

														# Transpose the cofactor matrix (Adjoint matrix)
														SCREAMING_SNAKE_CASE__     :str						    = array(UpperCAmelCase__		)
														for i in range(3		):
																					for j in range(3		):
																												SCREAMING_SNAKE_CASE__     :int						    = cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
														SCREAMING_SNAKE_CASE__     :List[str]						    = array(UpperCAmelCase__		)
														for i in range(3		):
																					for j in range(3		):
																												inverse_matrix[i][j] /= d(UpperCAmelCase__		)

        # Calculate the inverse of the matrix
														return [[float(d(UpperCAmelCase__		)		) or 0.0 for n in row] for row in inverse_matrix]
							raise ValueError('Please provide a matrix of size 2x2 or 3x3.'		)







'''simple docstring'''







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


UpperCamelCase_      	=	logging.get_logger(__name__)

UpperCamelCase_      	=	{
    '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json''',
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}




class _SCREAMING_SNAKE_CASE(							_SCREAMING_SNAKE_CASE					):
						A_			:							Union[str, Any]     		= 'gpt_neox'




						def __init__(    self :       List[str]							,							UpperCamelCase_ :       int=5_04_32							,							UpperCamelCase_ :       Dict=61_44							,							UpperCamelCase_ :       int=44							,							UpperCamelCase_ :       Any=64							,							UpperCamelCase_ :       Optional[int]=2_45_76							,							UpperCamelCase_ :       str="gelu"							,							UpperCamelCase_ :       Tuple=0.25							,							UpperCamelCase_ :       Tuple=1_00_00							,							UpperCamelCase_ :       Tuple=0.0							,							UpperCamelCase_ :       Optional[int]=0.0							,							UpperCamelCase_ :       str=0.1							,							UpperCamelCase_ :       List[Any]=20_48							,							UpperCamelCase_ :       List[str]=0.02							,							UpperCamelCase_ :       Optional[int]=1e-5							,							UpperCamelCase_ :       List[str]=True							,							UpperCamelCase_ :       Optional[Any]=0							,							UpperCamelCase_ :       str=2							,							UpperCamelCase_ :       str=False							,							UpperCamelCase_ :       Union[str, Any]=True							,							UpperCamelCase_ :       Tuple=None							,							**UpperCamelCase_ :       Any							,							)     ->				int:
													super().__init__(bos_token_id=UpperCamelCase_							,							eos_token_id=UpperCamelCase_							,							**UpperCamelCase_      )
													SCREAMING_SNAKE_CASE__     :int						    = vocab_size
													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = max_position_embeddings
													SCREAMING_SNAKE_CASE__     :List[Any]						    = hidden_size
													SCREAMING_SNAKE_CASE__     :Optional[int]						    = num_hidden_layers
													SCREAMING_SNAKE_CASE__     :Dict						    = num_attention_heads
													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = intermediate_size
													SCREAMING_SNAKE_CASE__     :Dict						    = hidden_act
													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = rotary_pct
													SCREAMING_SNAKE_CASE__     :Any						    = rotary_emb_base
													SCREAMING_SNAKE_CASE__     :Dict						    = attention_dropout
													SCREAMING_SNAKE_CASE__     :Tuple						    = hidden_dropout
													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = classifier_dropout
													SCREAMING_SNAKE_CASE__     :Dict						    = initializer_range
													SCREAMING_SNAKE_CASE__     :List[str]						    = layer_norm_eps
													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = use_cache
													SCREAMING_SNAKE_CASE__     :Any						    = tie_word_embeddings
													SCREAMING_SNAKE_CASE__     :List[str]						    = use_parallel_residual
													SCREAMING_SNAKE_CASE__     :int						    = rope_scaling
													self._rope_scaling_validation()

													if self.hidden_size % self.num_attention_heads != 0:
																				raise ValueError(
																				    'The hidden size is not divisble by the number of attention heads! Make sure to update them!'      )




						def      __lowerCamelCase       (    self :       Optional[Any]      )     ->				Union[str, Any]:
													if self.rope_scaling is None:
																				return

													if not isinstance(self.rope_scaling							,							UpperCamelCase_      ) or len(self.rope_scaling      ) != 2:
																				raise ValueError(
																				    '`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, '
																				    f'''got {self.rope_scaling}'''      )
													SCREAMING_SNAKE_CASE__     :Optional[int]						    = self.rope_scaling.get('type'							,							UpperCamelCase_      )
													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = self.rope_scaling.get('factor'							,							UpperCamelCase_      )
													if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
																				raise ValueError(
																				    f'''`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'''      )
													if rope_scaling_factor is None or not isinstance(UpperCamelCase_							,							UpperCamelCase_      ) or rope_scaling_factor <= 1.0:
																				raise ValueError(f'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''      )






