

from __future__ import annotations

class 				a  :


						def __init__(       self						,					A_	):







										'''simple docstring'''


										_UpperCAmelCase       :		List[Any] 		=    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:
														_UpperCAmelCase       :		Optional[Any] 		=    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
														_UpperCAmelCase       :		List[str] 		=    rows
										else:
														_UpperCAmelCase       :		List[str] 		=    []


						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


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


						@property
						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


										return len(self.rows	)


						@property
						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


										return len(self.rows[0]	)


						@property
						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


										return (self.num_rows, self.num_columns)


						@property
						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


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


						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


										_UpperCAmelCase       :		Union[str, Any] 		=    [
										    [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        _UpperCAmelCase				(       self	):







										'''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	):







										'''simple docstring'''


										return bool(self.determinant()	)


						def        _UpperCAmelCase				(       self						,					A_						,					A_	):







										'''simple docstring'''


										_UpperCAmelCase       :		Union[str, 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        _UpperCAmelCase				(       self						,					A_						,					A_	):







										'''simple docstring'''


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


						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


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


						def        _UpperCAmelCase				(       self	):







										'''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	):







										'''simple docstring'''


										_UpperCAmelCase       :		List[str] 		=    [
										    [self.cofactors().rows[column][row] for column in range(self.num_columns	)]
										    for row in range(self.num_rows	)
										]
										return Matrix(A_	)


						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


										_UpperCAmelCase       :		str 		=    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	):







										'''simple docstring'''


										return str(self.rows	)


						def __str__(       self	):







										'''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        _UpperCAmelCase				(       self						,					A_						,					A_ = None	):







										'''simple docstring'''


										_UpperCAmelCase       :		Any 		=    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:
														_UpperCAmelCase       :		Tuple 		=    self.rows[0:position] + [row] + self.rows[position:]


						def        _UpperCAmelCase				(       self						,					A_						,					A_ = None	):







										'''simple docstring'''


										_UpperCAmelCase       :		int 		=    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:
														_UpperCAmelCase       :		Optional[Any] 		=    [self.rows[i] + [column[i]] for i in range(self.num_rows	)]
										else:
														_UpperCAmelCase       :		str 		=    [
														    self.rows[i][0:position] + [column[i]] + self.rows[i][position:]
														    for i in range(self.num_rows	)
														]


						def __eq__(       self						,					A_	):







										'''simple docstring'''


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


						def __ne__(       self						,					A_	):







										'''simple docstring'''


										return not self == other


						def __neg__(       self	):







										'''simple docstring'''


										return self * -1


						def __add__(       self						,					A_	):







										'''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						,					A_	):







										'''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						,					A_	):







										'''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						,					A_	):







										'''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"	)
										_UpperCAmelCase       :		str 		=    self
										for _ in range(other - 1	):
														result *= self
										return result





						@classmethod
						def        _UpperCAmelCase				(       cls						,					A_						,					A_	):







										'''simple docstring'''


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


if __name__ == "__main__":
					import doctest

					doctest.testmod()





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


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_        =      {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}

class 				a  (	UpperCAmelCase				):
						_lowercase    						=			"openai-gpt"
						_lowercase    						=			{
						    "max_position_embeddings": "n_positions",
						    "hidden_size": "n_embd",
						    "num_attention_heads": "n_head",
						    "num_hidden_layers": "n_layer",
						}


						def __init__(       self						,					A_=40478						,					A_=512						,					A_=768						,					A_=12						,					A_=12						,					A_="gelu"						,					A_=0.1						,					A_=0.1						,					A_=0.1						,					A_=1e-5						,					A_=0.02						,					A_="cls_index"						,					A_=True						,					A_=None						,					A_=True						,					A_=0.1						,					**A_						,					):







										'''simple docstring'''


										_UpperCAmelCase       :		Any 		=    vocab_size
										_UpperCAmelCase       :		str 		=    n_positions
										_UpperCAmelCase       :		List[Any] 		=    n_embd
										_UpperCAmelCase       :		Dict 		=    n_layer
										_UpperCAmelCase       :		Any 		=    n_head
										_UpperCAmelCase       :		int 		=    afn
										_UpperCAmelCase       :		int 		=    resid_pdrop
										_UpperCAmelCase       :		Tuple 		=    embd_pdrop
										_UpperCAmelCase       :		Optional[Any] 		=    attn_pdrop
										_UpperCAmelCase       :		Any 		=    layer_norm_epsilon
										_UpperCAmelCase       :		List[str] 		=    initializer_range
										_UpperCAmelCase       :		Union[str, Any] 		=    summary_type
										_UpperCAmelCase       :		List[Any] 		=    summary_use_proj
										_UpperCAmelCase       :		Optional[Any] 		=    summary_activation
										_UpperCAmelCase       :		int 		=    summary_first_dropout
										_UpperCAmelCase       :		List[str] 		=    summary_proj_to_labels
										super().__init__(**A_	)


