

"""simple docstring"""




from __future__ import annotations

from decimal import Decimal

from numpy import array





def       lowercase__						(       snake_case_   :list[list[float]]    ):
	__UpperCAmelCase      		= Decimal

	# Check if the provided matrix has 2 rows and 2 columns
	# since this implementation only works for 2x2 matrices
	if len(snake_case_    ) == 2 and len(matrix[0]    ) == 2 and len(matrix[1]    ) == 2:
		# Calculate the determinant of the matrix
		__UpperCAmelCase      		= 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
		__UpperCAmelCase      		= [[0.0, 0.0], [0.0, 0.0]]
		__UpperCAmelCase		,							__UpperCAmelCase      		= matrix[1][1], matrix[0][0]
		__UpperCAmelCase		,							__UpperCAmelCase      		= -matrix[1][0], -matrix[0][1]

		# Calculate the inverse of the matrix
		return [
		    [(float(d(snake_case_    )    ) / determinant) or 0.0 for n in row] for row in swapped_matrix
		]
	elif (
	    len(snake_case_    ) == 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
		__UpperCAmelCase      		= 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
		__UpperCAmelCase      		= [
		    [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    )],
		]
		__UpperCAmelCase      		= (d(matrix[1][1]    ) * d(matrix[2][2]    )) - (
		    d(matrix[1][2]    ) * d(matrix[2][1]    )
		)
		__UpperCAmelCase      		= -(
		    (d(matrix[1][0]    ) * d(matrix[2][2]    )) - (d(matrix[1][2]    ) * d(matrix[2][0]    ))
		)
		__UpperCAmelCase      		= (d(matrix[1][0]    ) * d(matrix[2][1]    )) - (
		    d(matrix[1][1]    ) * d(matrix[2][0]    )
		)
		__UpperCAmelCase      		= -(
		    (d(matrix[0][1]    ) * d(matrix[2][2]    )) - (d(matrix[0][2]    ) * d(matrix[2][1]    ))
		)
		__UpperCAmelCase      		= (d(matrix[0][0]    ) * d(matrix[2][2]    )) - (
		    d(matrix[0][2]    ) * d(matrix[2][0]    )
		)
		__UpperCAmelCase      		= -(
		    (d(matrix[0][0]    ) * d(matrix[2][1]    )) - (d(matrix[0][1]    ) * d(matrix[2][0]    ))
		)
		__UpperCAmelCase      		= (d(matrix[0][1]    ) * d(matrix[1][2]    )) - (
		    d(matrix[0][2]    ) * d(matrix[1][1]    )
		)
		__UpperCAmelCase      		= -(
		    (d(matrix[0][0]    ) * d(matrix[1][2]    )) - (d(matrix[0][2]    ) * d(matrix[1][0]    ))
		)
		__UpperCAmelCase      		= (d(matrix[0][0]    ) * d(matrix[1][1]    )) - (
		    d(matrix[0][1]    ) * d(matrix[1][0]    )
		)

		# Transpose the cofactor matrix (Adjoint matrix)
		__UpperCAmelCase      		= array(snake_case_    )
		for i in range(3    ):
			for j in range(3    ):
				__UpperCAmelCase      		= cofactor_matrix[j][i]

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

        # Calculate the inverse of the matrix
		return [[float(d(snake_case_    )    ) 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'''



import copy
import random

from transformers import CLIPTokenizer
class 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):




      def __init__(	self			, *lowerCamelCase			, **lowerCamelCase   )				->Union[str, Any]:



         '''simple docstring'''
         super().__init__(*lowerCamelCase			, **lowerCamelCase   )
         __a					  =     {}




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )				->Dict:



         '''simple docstring'''
         __a					  =     super().add_tokens(lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )
         if num_added_tokens == 0:
            raise ValueError(
                F"""The tokenizer already contains the token {placeholder_token}. Please pass a different"""
                ' `placeholder_token` that is not already in the tokenizer.'   )




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, *lowerCamelCase			, lowerCamelCase=1			, **lowerCamelCase   )				->List[str]:



         '''simple docstring'''
         __a					  =     []
         if num_vec_per_token == 1:
            self.try_adding_tokens(lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )
            output.append(lowerCamelCase   )
         else:
            __a					  =     []
            for i in range(lowerCamelCase   ):
               __a					  =     placeholder_token + F"""_{i}"""
               self.try_adding_tokens(lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )
               output.append(lowerCamelCase   )
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
         for token in self.token_map:
            if token in placeholder_token:
               raise ValueError(
                   F"""The tokenizer already has placeholder token {token} that can get confused with"""
                   F""" {placeholder_token}keep placeholder tokens independent"""   )
         __a					  =     output




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase=False			, lowerCamelCase=1.0   )				->int:



         '''simple docstring'''
         if isinstance(lowerCamelCase			, lowerCamelCase   ):
            __a					  =     []
            for i in range(len(lowerCamelCase   )   ):
               output.append(self.replace_placeholder_tokens_in_text(text[i]			, vector_shuffle=lowerCamelCase   )   )
            return output
         for placeholder_token in self.token_map:
            if placeholder_token in text:
               __a					  =     self.token_map[placeholder_token]
               __a					  =     tokens[: 1 + int(len(lowerCamelCase   ) * prop_tokens_to_load   )]
               if vector_shuffle:
                  __a					  =     copy.copy(lowerCamelCase   )
                  random.shuffle(lowerCamelCase   )
               __a					  =     text.replace(lowerCamelCase			, ' '.join(lowerCamelCase   )   )
         return text




      def __call__(	self			, lowerCamelCase			, *lowerCamelCase			, lowerCamelCase=False			, lowerCamelCase=1.0			, **lowerCamelCase   )				->Optional[int]:



         '''simple docstring'''
         return super().__call__(
             self.replace_placeholder_tokens_in_text(
                 lowerCamelCase			, vector_shuffle=lowerCamelCase			, prop_tokens_to_load=lowerCamelCase   )			, *lowerCamelCase			, **lowerCamelCase			, )






      def 			__UpperCamelCase				(	self			, lowerCamelCase			, *lowerCamelCase			, lowerCamelCase=False			, lowerCamelCase=1.0			, **lowerCamelCase   )				->List[Any]:



         '''simple docstring'''
         return super().encode(
             self.replace_placeholder_tokens_in_text(
                 lowerCamelCase			, vector_shuffle=lowerCamelCase			, prop_tokens_to_load=lowerCamelCase   )			, *lowerCamelCase			, **lowerCamelCase			, )