






from __future__ import annotations
class  _UpperCAmelCase   :

				"""simple docstring"""




				def __init__(	self		:       List[str],    lowerCamelCase		:       list[list[int]]    ):

								'''simple docstring'''
								lowercase__  					=     TypeError(
								    '''Matrices must be formed from a list of zero or more lists containing at '''
								    '''least one and the same number of values, each of which must be of type '''
								    '''int or float.'''    )
								if len(lowerCamelCase    ) != 0:
												lowercase__  					=     len(rows[0]    )
												if cols == 0:
																raise error
												for row in rows:
																if len(lowerCamelCase    ) != cols:
																				raise error
																for value in row:
																				if not isinstance(lowerCamelCase,    (int, float)    ):
																								raise error
												lowercase__  					=     rows
								else:
												lowercase__  					=     []




				def 							lowercase__  (	self		:       Optional[int]    ):

								'''simple docstring'''
								return [[row[i] for row in self.rows] for i in range(len(self.rows[0]    )    )]




				@property
				def 							lowercase__  (	self		:       Union[str, Any]    ):

								'''simple docstring'''
								return len(self.rows    )




				@property
				def 							lowercase__  (	self		:       Union[str, Any]    ):

								'''simple docstring'''
								return len(self.rows[0]    )




				@property
				def 							lowercase__  (	self		:       List[str]    ):

								'''simple docstring'''
								return (self.num_rows, self.num_columns)




				@property
				def 							lowercase__  (	self		:       int    ):

								'''simple docstring'''
								return self.order[0] == self.order[1]




				def 							lowercase__  (	self		:       List[Any]    ):

								'''simple docstring'''
								lowercase__  					=     [
								    [0 if column_num != row_num else 1 for column_num in range(self.num_rows    )]
								    for row_num in range(self.num_rows    )
								]
								return Matrix(lowerCamelCase    )




				def 							lowercase__  (	self		:       Union[str, Any]    ):

								'''simple docstring'''
								if not self.is_square:
												return 0
								if self.order == (0, 0):
												return 1
								if self.order == (1, 1):
												return int(self.rows[0][0]    )
								if self.order == (2, 2):
												return int(
												    (self.rows[0][0] * self.rows[1][1])
												    - (self.rows[0][1] * self.rows[1][0])    )
								else:
												return sum(
												    self.rows[0][column] * self.cofactors().rows[0][column]
												    for column in range(self.num_columns    )    )




				def 							lowercase__  (	self		:       List[Any]    ):

								'''simple docstring'''
								return bool(self.determinant()    )




				def 							lowercase__  (	self		:       List[Any],    lowerCamelCase		:       int,    lowerCamelCase		:       int    ):

								'''simple docstring'''
								lowercase__  					=     [
								    [
								        self.rows[other_row][other_column]
								        for other_column in range(self.num_columns    )
								        if other_column != column
								    ]
								    for other_row in range(self.num_rows    )
								    if other_row != row
								]
								return Matrix(lowerCamelCase    ).determinant()




				def 							lowercase__  (	self		:       str,    lowerCamelCase		:       int,    lowerCamelCase		:       int    ):

								'''simple docstring'''
								if (row + column) % 2 == 0:
												return self.get_minor(lowerCamelCase,    lowerCamelCase    )
								return -1 * self.get_minor(lowerCamelCase,    lowerCamelCase    )




				def 							lowercase__  (	self		:       List[Any]    ):

								'''simple docstring'''
								return Matrix(
								    [
								        [self.get_minor(lowerCamelCase,    lowerCamelCase    ) for column in range(self.num_columns    )]
								        for row in range(self.num_rows    )
								    ]    )




				def 							lowercase__  (	self		:       Dict    ):

								'''simple docstring'''
								return Matrix(
								    [
								        [
								            self.minors().rows[row][column]
								            if (row + column) % 2 == 0
								            else self.minors().rows[row][column] * -1
								            for column in range(self.minors().num_columns    )
								        ]
								        for row in range(self.minors().num_rows    )
								    ]    )




				def 							lowercase__  (	self		:       Any    ):

								'''simple docstring'''
								lowercase__  					=     [
								    [self.cofactors().rows[column][row] for column in range(self.num_columns    )]
								    for row in range(self.num_rows    )
								]
								return Matrix(lowerCamelCase    )




				def 							lowercase__  (	self		:       Any    ):

								'''simple docstring'''
								lowercase__  					=     self.determinant()
								if not determinant:
												raise TypeError('''Only matrices with a non-zero determinant have an inverse'''    )
								return self.adjugate() * (1 / determinant)




				def __repr__(	self		:       Tuple    ):

								'''simple docstring'''
								return str(self.rows    )




				def __str__(	self		:       str    ):

								'''simple docstring'''
								if self.num_rows == 0:
												return "[]"
								if self.num_rows == 1:
												return "[[" + ". ".join(str(self.rows[0]    )    ) + "]]"
								return (
								    "["
								    + "\n ".join(
								        [
								            '''[''' + '''. '''.join([str(lowerCamelCase    ) for value in row]    ) + '''.]'''
								            for row in self.rows
								        ]    )
								    + "]"
								)




				def 							lowercase__  (	self		:       List[Any],    lowerCamelCase		:       list[int],    lowerCamelCase		:       int | None = None    ):

								'''simple docstring'''
								lowercase__  					=     TypeError('''Row must be a list containing all ints and/or floats'''    )
								if not isinstance(lowerCamelCase,    lowerCamelCase    ):
												raise type_error
								for value in row:
												if not isinstance(lowerCamelCase,    (int, float)    ):
																raise type_error
								if len(lowerCamelCase    ) != self.num_columns:
												raise ValueError(
												    '''Row must be equal in length to the other rows in the matrix'''    )
								if position is None:
												self.rows.append(lowerCamelCase    )
								else:
												lowercase__  					=     self.rows[0:position] + [row] + self.rows[position:]




				def 							lowercase__  (	self		:       List[str],    lowerCamelCase		:       list[int],    lowerCamelCase		:       int | None = None    ):

								'''simple docstring'''
								lowercase__  					=     TypeError(
								    '''Column must be a list containing all ints and/or floats'''    )
								if not isinstance(lowerCamelCase,    lowerCamelCase    ):
												raise type_error
								for value in column:
												if not isinstance(lowerCamelCase,    (int, float)    ):
																raise type_error
								if len(lowerCamelCase    ) != self.num_rows:
												raise ValueError(
												    '''Column must be equal in length to the other columns in the matrix'''    )
								if position is None:
												lowercase__  					=     [self.rows[i] + [column[i]] for i in range(self.num_rows    )]
								else:
												lowercase__  					=     [
												    self.rows[i][0:position] + [column[i]] + self.rows[i][position:]
												    for i in range(self.num_rows    )
												]




				def __eq__(	self		:       Union[str, Any],    lowerCamelCase		:       object    ):

								'''simple docstring'''
								if not isinstance(lowerCamelCase,    lowerCamelCase    ):
												return NotImplemented
								return self.rows == other.rows




				def __ne__(	self		:       int,    lowerCamelCase		:       object    ):

								'''simple docstring'''
								return not self == other




				def __neg__(	self		:       Tuple    ):

								'''simple docstring'''
								return self * -1




				def __add__(	self		:       List[str],    lowerCamelCase		:       Matrix    ):

								'''simple docstring'''
								if self.order != other.order:
												raise ValueError('''Addition requires matrices of the same order'''    )
								return Matrix(
								    [
								        [self.rows[i][j] + other.rows[i][j] for j in range(self.num_columns    )]
								        for i in range(self.num_rows    )
								    ]    )




				def __sub__(	self		:       Tuple,    lowerCamelCase		:       Matrix    ):

								'''simple docstring'''
								if self.order != other.order:
												raise ValueError('''Subtraction requires matrices of the same order'''    )
								return Matrix(
								    [
								        [self.rows[i][j] - other.rows[i][j] for j in range(self.num_columns    )]
								        for i in range(self.num_rows    )
								    ]    )




				def __mul__(	self		:       str,    lowerCamelCase		:       Matrix | int | float    ):

								'''simple docstring'''
								if isinstance(lowerCamelCase,    (int, float)    ):
												return Matrix(
												    [[int(element * other    ) for element in row] for row in self.rows]    )
								elif isinstance(lowerCamelCase,    lowerCamelCase    ):
												if self.num_columns != other.num_rows:
																raise ValueError(
																    '''The number of columns in the first matrix must '''
																    '''be equal to the number of rows in the second'''    )
												return Matrix(
												    [
												        [Matrix.dot_product(lowerCamelCase,    lowerCamelCase    ) for column in other.columns()]
												        for row in self.rows
												    ]    )
								else:
												raise TypeError(
												    '''A Matrix can only be multiplied by an int, float, or another matrix'''    )




				def __pow__(	self		:       List[str],    lowerCamelCase		:       int    ):

								'''simple docstring'''
								if not isinstance(lowerCamelCase,    lowerCamelCase    ):
												raise TypeError('''A Matrix can only be raised to the power of an int'''    )
								if not self.is_square:
												raise ValueError('''Only square matrices can be raised to a power'''    )
								if other == 0:
												return self.identity()
								if other < 0:
												if self.is_invertable():
																return self.inverse() ** (-other)
												raise ValueError(
												    '''Only invertable matrices can be raised to a negative power'''    )
								lowercase__  					=     self
								for _ in range(other - 1    ):
												result *= self
								return result




				@classmethod
				def 							lowercase__  (	cls		:       List[Any],    lowerCamelCase		:       list[int],    lowerCamelCase		:       list[int]    ):

								'''simple docstring'''
								return sum(row[i] * column[i] for i in range(len(lowerCamelCase    )    )    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A__      :     Optional[int]       =					{
    'configuration_clap': [
        'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
        'ClapAudioConfig',
        'ClapConfig',
        'ClapTextConfig',
    ],
    'processing_clap': ['ClapProcessor'],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__      :     str       =					[
							    'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'ClapModel',
							    'ClapPreTrainedModel',
							    'ClapTextModel',
							    'ClapTextModelWithProjection',
							    'ClapAudioModel',
							    'ClapAudioModelWithProjection',
							]
							A__      :     List[Any]       =					['ClapFeatureExtractor']

if TYPE_CHECKING:
							from .configuration_clap import (
							    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
							    ClapAudioConfig,
							    ClapConfig,
							    ClapTextConfig,
							)
							from .processing_clap import ClapProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_clap import ClapFeatureExtractor
														from .modeling_clap import (
														    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ClapAudioModel,
														    ClapAudioModelWithProjection,
														    ClapModel,
														    ClapPreTrainedModel,
														    ClapTextModel,
														    ClapTextModelWithProjection,
														)


else:
							import sys

							A__      :     int       =					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




