from __future__ import annotations





class 					lowercase__						:


						def __init__(       self	:				Optional[int]    ,		UpperCamelCase__	:				list[list[int]]						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    int							=							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(__A						) != 0:
																		SCREAMING_SNAKE_CASE							:    Optional[int]							=							len(rows[0]						)
																		if cols == 0:
																								raise error
																		for row in rows:
																								if len(__A						) != cols:
																														raise error
																								for value in row:
																														if not isinstance(__A    ,		(int, float)						):
																																				raise error
																		SCREAMING_SNAKE_CASE							:    int							=							rows
												else:
																		SCREAMING_SNAKE_CASE							:    int							=							[]


						def        __A       (       self	:				int						):





												'''simple docstring'''





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


						@property
						def        __A       (       self	:				str						):





												'''simple docstring'''





												return len(self.rows						)


						@property
						def        __A       (       self	:				Any						):





												'''simple docstring'''





												return len(self.rows[0]						)


						@property
						def        __A       (       self	:				Optional[Any]						):





												'''simple docstring'''





												return (self.num_rows, self.num_columns)


						@property
						def        __A       (       self	:				Dict						):





												'''simple docstring'''





												return self.order[0] == self.order[1]


						def        __A       (       self	:				Any						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    Dict							=							[
												    [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(__A						)


						def        __A       (       self	:				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        __A       (       self	:				List[str]						):





												'''simple docstring'''





												return bool(self.determinant()						)


						def        __A       (       self	:				Dict    ,		UpperCamelCase__	:				int    ,		UpperCamelCase__	:				int						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    List[Any]							=							[
												    [
												        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(__A						).determinant()


						def        __A       (       self	:				Dict    ,		UpperCamelCase__	:				int    ,		UpperCamelCase__	:				int						):





												'''simple docstring'''





												if (row + column) % 2 == 0:
																		return self.get_minor(__A    ,		__A						)
												return -1 * self.get_minor(__A    ,		__A						)


						def        __A       (       self	:				List[str]						):





												'''simple docstring'''





												return Matrix(
												    [
												        [self.get_minor(__A    ,		__A						) for column in range(self.num_columns						)]
												        for row in range(self.num_rows						)
												    ]						)


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





												'''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        __A       (       self	:				List[str]						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    Any							=							[
												    [self.cofactors().rows[column][row] for column in range(self.num_columns						)]
												    for row in range(self.num_rows						)
												]
												return Matrix(__A						)


						def        __A       (       self	:				Dict						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    Optional[int]							=							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	:				Optional[Any]						):





												'''simple docstring'''





												return str(self.rows						)


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





												'''simple docstring'''





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


						def        __A       (       self	:				List[Any]    ,		UpperCamelCase__	:				list[int]    ,		UpperCamelCase__	:				int | None = None						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    Optional[int]							=							TypeError('''Row must be a list containing all ints and/or floats'''						)
												if not isinstance(__A    ,		__A						):
																		raise type_error
												for value in row:
																		if not isinstance(__A    ,		(int, float)						):
																								raise type_error
												if len(__A						) != 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(__A						)
												else:
																		SCREAMING_SNAKE_CASE							:    List[str]							=							self.rows[0:position] + [row] + self.rows[position:]


						def        __A       (       self	:				Optional[Any]    ,		UpperCamelCase__	:				list[int]    ,		UpperCamelCase__	:				int | None = None						):





												'''simple docstring'''





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


						def __eq__(       self	:				Tuple    ,		UpperCamelCase__	:				object						):





												'''simple docstring'''





												if not isinstance(__A    ,		__A						):
																		return NotImplemented
												return self.rows == other.rows


						def __ne__(       self	:				Any    ,		UpperCamelCase__	:				object						):





												'''simple docstring'''





												return not self == other


						def __neg__(       self	:				List[Any]						):





												'''simple docstring'''





												return self * -1


						def __add__(       self	:				List[str]    ,		UpperCamelCase__	:				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	:				str    ,		UpperCamelCase__	:				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    ,		UpperCamelCase__	:				Matrix | int | float						):





												'''simple docstring'''





												if isinstance(__A    ,		(int, float)						):
																		return Matrix(
																		    [[int(element * other						) for element in row] for row in self.rows]						)
												elif isinstance(__A    ,		__A						):
																		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(__A    ,		__A						) 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	:				Union[str, Any]    ,		UpperCamelCase__	:				int						):





												'''simple docstring'''





												if not isinstance(__A    ,		__A						):
																		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'''						)
												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							self
												for _ in range(other - 1						):
																		result *= self
												return result



						@classmethod
						def        __A       (       cls	:				Tuple    ,		UpperCamelCase__	:				list[int]    ,		UpperCamelCase__	:				list[int]						):





												'''simple docstring'''





												return sum(row[i] * column[i] for i in range(len(__A						)						)						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()












'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__							:							List[str] ={
    '''configuration_bigbird_pegasus''': [
        '''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BigBirdPegasusConfig''',
        '''BigBirdPegasusOnnxConfig''',
    ],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    a__							:							Any =[
        '''BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''BigBirdPegasusForCausalLM''',
        '''BigBirdPegasusForConditionalGeneration''',
        '''BigBirdPegasusForQuestionAnswering''',
        '''BigBirdPegasusForSequenceClassification''',
        '''BigBirdPegasusModel''',
        '''BigBirdPegasusPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_bigbird_pegasus import (
        BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
        BigBirdPegasusConfig,
        BigBirdPegasusOnnxConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_bigbird_pegasus import (
            BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
            BigBirdPegasusForCausalLM,
            BigBirdPegasusForConditionalGeneration,
            BigBirdPegasusForQuestionAnswering,
            BigBirdPegasusForSequenceClassification,
            BigBirdPegasusModel,
            BigBirdPegasusPreTrainedModel,
        )


else:
    import sys

    a__							:							str =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
