






from __future__ import annotations

class 		__a				:
		def __init__(      self      ,   _SCREAMING_SNAKE_CASE						)			->	Any:




									"""simple docstring"""





									_UpperCAmelCase					=      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(_SCREAMING_SNAKE_CASE						) != 0:
																_UpperCAmelCase					=      len(rows[0]						)
																if cols == 0:
																							raise error
																for row in rows:
																							if len(_SCREAMING_SNAKE_CASE						) != cols:
																														raise error
																							for value in row:
																														if not isinstance(_SCREAMING_SNAKE_CASE      ,   (int, float)						):
																																					raise error
																_UpperCAmelCase					=      rows
									else:
																_UpperCAmelCase					=      []
		def      UpperCAmelCase__    (      self						)			->	list[list[int]]:




									"""simple docstring"""





									return [[row[i] for row in self.rows] for i in range(len(self.rows[0]						)						)]
		@property
		def      UpperCAmelCase__    (      self						)			->	int:




									"""simple docstring"""





									return len(self.rows						)
		@property
		def      UpperCAmelCase__    (      self						)			->	int:




									"""simple docstring"""





									return len(self.rows[0]						)
		@property
		def      UpperCAmelCase__    (      self						)			->	tuple[int, int]:




									"""simple docstring"""





									return (self.num_rows, self.num_columns)
		@property
		def      UpperCAmelCase__    (      self						)			->	bool:




									"""simple docstring"""





									return self.order[0] == self.order[1]
		def      UpperCAmelCase__    (      self						)			->	Matrix:




									"""simple docstring"""





									_UpperCAmelCase					=      [
									    [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(_SCREAMING_SNAKE_CASE						)
		def      UpperCAmelCase__    (      self						)			->	int:




									"""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      UpperCAmelCase__    (      self						)			->	bool:




									"""simple docstring"""





									return bool(self.determinant()						)
		def      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						)			->	int:




									"""simple docstring"""





									_UpperCAmelCase					=      [
									    [
									        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(_SCREAMING_SNAKE_CASE						).determinant()
		def      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						)			->	int:




									"""simple docstring"""





									if (row + column) % 2 == 0:
																return self.get_minor(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						)
									return -1 * self.get_minor(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						)
		def      UpperCAmelCase__    (      self						)			->	Matrix:




									"""simple docstring"""





									return Matrix(
									    [
									        [self.get_minor(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						) for column in range(self.num_columns						)]
									        for row in range(self.num_rows						)
									    ]						)
		def      UpperCAmelCase__    (      self						)			->	Matrix:




									"""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      UpperCAmelCase__    (      self						)			->	Matrix:




									"""simple docstring"""





									_UpperCAmelCase					=      [
									    [self.cofactors().rows[column][row] for column in range(self.num_columns						)]
									    for row in range(self.num_rows						)
									]
									return Matrix(_SCREAMING_SNAKE_CASE						)
		def      UpperCAmelCase__    (      self						)			->	Matrix:




									"""simple docstring"""





									_UpperCAmelCase					=      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						)			->	str:




									"""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(_SCREAMING_SNAKE_CASE						) for value in row]						) + '.]'
									            for row in self.rows
									        ]						)
									    + "]"
									)
		def      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE = None						)			->	None:




									"""simple docstring"""





									_UpperCAmelCase					=      TypeError('Row must be a list containing all ints and/or floats'						)
									if not isinstance(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						):
																raise type_error
									for value in row:
																if not isinstance(_SCREAMING_SNAKE_CASE      ,   (int, float)						):
																							raise type_error
									if len(_SCREAMING_SNAKE_CASE						) != 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(_SCREAMING_SNAKE_CASE						)
									else:
																_UpperCAmelCase					=      self.rows[0:position] + [row] + self.rows[position:]
		def      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE = None						)			->	None:




									"""simple docstring"""





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




									"""simple docstring"""





									if not isinstance(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						):
																return NotImplemented
									return self.rows == other.rows
		def __ne__(      self      ,   _SCREAMING_SNAKE_CASE						)			->	bool:




									"""simple docstring"""





									return not self == other
		def __neg__(      self						)			->	Matrix:




									"""simple docstring"""





									return self * -1
		def __add__(      self      ,   _SCREAMING_SNAKE_CASE						)			->	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      ,   _SCREAMING_SNAKE_CASE						)			->	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      ,   _SCREAMING_SNAKE_CASE						)			->	Matrix:




									"""simple docstring"""





									if isinstance(_SCREAMING_SNAKE_CASE      ,   (int, float)						):
																return Matrix(
																    [[int(element * other						) for element in row] for row in self.rows]						)
									elif isinstance(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						):
																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(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						) 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      ,   _SCREAMING_SNAKE_CASE						)			->	Matrix:




									"""simple docstring"""





									if not isinstance(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						):
																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'						)
									_UpperCAmelCase					=      self
									for _ in range(other - 1						):
																result *= self
									return result






		@classmethod
		def      UpperCAmelCase__    (      cls      ,   _SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						)			->	int:




									"""simple docstring"""





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


if __name__ == "__main__":
		import doctest

		doctest.testmod()




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase__  :Any             =							{'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XGLMConfig''']}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :Optional[Any]             =							['''XGLMTokenizer''']

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :str             =							['''XGLMTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :List[str]             =							[
		    '''XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''XGLMForCausalLM''',
		    '''XGLMModel''',
		    '''XGLMPreTrainedModel''',
		]


try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :str             =							[
		    '''FlaxXGLMForCausalLM''',
		    '''FlaxXGLMModel''',
		    '''FlaxXGLMPreTrainedModel''',
		]


try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :List[Any]             =							[
		    '''TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''TFXGLMForCausalLM''',
		    '''TFXGLMModel''',
		    '''TFXGLMPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_xglm import XGLMTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_xglm_fast import XGLMTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_xglm import (
				    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFXGLMForCausalLM,
				    TFXGLMModel,
				    TFXGLMPreTrainedModel,
				)


else:
		import sys

		lowerCAmelCase__  :Any             =							_LazyModule(__name__, globals()['''__file__'''], _import_structure)
