



from __future__ import annotations

import math
import random
from collections.abc import Collection
from typing import overload

class       snake_case__:

					"""simple docstring"""






					def __init__(							self					:	Optional[int]      ,   SCREAMING_SNAKE_CASE					:	Collection[float] | None = None     ):


									if components is None:
													lowercase__     :    Optional[Any]													=     []
									lowercase__     :    int													=     list(lowercase_     )







					def __len__(							self					:	Optional[int]     ):
									return len(self.__components     )







					def __str__(							self					:	List[Any]     ):
									return "(" + ",".join(map(lowercase_      ,   self.__components     )     ) + ")"







					def __add__(							self					:	Dict      ,   SCREAMING_SNAKE_CASE					:	Vector     ):
									lowercase__     :    Dict													=     len(self     )
									if size == len(lowercase_     ):
													lowercase__     :    Dict													=     [self.__components[i] + other.component(lowercase_     ) for i in range(lowercase_     )]
													return Vector(lowercase_     )
									else:
													raise Exception("must have the same size"     )







					def __sub__(							self					:	Union[str, Any]      ,   SCREAMING_SNAKE_CASE					:	Vector     ):
									lowercase__     :    Optional[Any]													=     len(self     )
									if size == len(lowercase_     ):
													lowercase__     :    Optional[Any]													=     [self.__components[i] - other.component(lowercase_     ) for i in range(lowercase_     )]
													return Vector(lowercase_     )
									else:  # error case
													raise Exception("must have the same size"     )







					@overload
					def __mul__(							self					:	Optional[Any]      ,   SCREAMING_SNAKE_CASE					:	float     ):
									...







					@overload
					def __mul__(							self					:	Union[str, Any]      ,   SCREAMING_SNAKE_CASE					:	Vector     ):
									...







					def __mul__(							self					:	int      ,   SCREAMING_SNAKE_CASE					:	float | Vector     ):


									if isinstance(lowercase_      ,   (float, int)     ):
													lowercase__     :    int													=     [c * other for c in self.__components]
													return Vector(lowercase_     )
									elif isinstance(lowercase_      ,   lowercase_     ) and len(self     ) == len(lowercase_     ):
													lowercase__     :    Optional[int]													=     len(self     )
													lowercase__     :    List[str]													=     [self.__components[i] * other.component(lowercase_     ) for i in range(lowercase_     )]
													return sum(lowercase_     )
									else:  # error case
													raise Exception("invalid operand!"     )







					def  snake_case     (							self					:	Dict     ):
									return Vector(self.__components     )







					def  snake_case     (							self					:	Optional[int]      ,   SCREAMING_SNAKE_CASE					:	int     ):


									if isinstance(lowercase_      ,   lowercase_     ) and -len(self.__components     ) <= i < len(self.__components     ):
													return self.__components[i]
									else:
													raise Exception("index out of range"     )







					def  snake_case     (							self					:	Any      ,   SCREAMING_SNAKE_CASE					:	int      ,   SCREAMING_SNAKE_CASE					:	float     ):
									assert -len(self.__components     ) <= pos < len(self.__components     )
									lowercase__     :    Any													=     value







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


									if len(self.__components     ) == 0:
													raise Exception("Vector is empty"     )
									lowercase__     :    Dict													=     [c**2 for c in self.__components]
									return math.sqrt(sum(lowercase_     )     )







					def  snake_case     (							self					:	Optional[Any]      ,   SCREAMING_SNAKE_CASE					:	Vector      ,   SCREAMING_SNAKE_CASE					:	bool = False     ):
									lowercase__     :    Union[str, Any]													=     self * other
									lowercase__     :    Any													=     self.euclidean_length() * other.euclidean_length()
									if deg:
													return math.degrees(math.acos(num / den     )     )
									else:
													return math.acos(num / den     )






def 					__lowerCamelCase					(   lowerCamelCase__						):

				"""simple docstring"""


				assert isinstance(__a     , __a						)
				return Vector([0] * dimension						)


def 					__lowerCamelCase					(   lowerCamelCase__     , lowerCamelCase__						):

				"""simple docstring"""


				assert isinstance(__a     , __a						) and (isinstance(__a     , __a						))
				lowercase__     :    List[str]													=     [0] * dimension
				lowercase__     :    Union[str, Any]													=     1
				return Vector(__a						)


def 					__lowerCamelCase					(   lowerCamelCase__     , lowerCamelCase__     , lowerCamelCase__						):

				"""simple docstring"""


				assert (
				    isinstance(__a     , __a						)
				    and isinstance(__a     , __a						)
				    and (isinstance(__a     , (int, float)						))
				)
				return x * scalar + y


def 					__lowerCamelCase					(   lowerCamelCase__     , lowerCamelCase__     , lowerCamelCase__						):

				"""simple docstring"""


				random.seed(__a						)
				lowercase__     :    List[str]													=     [random.randint(__a     , __a						) for _ in range(__a						)]
				return Vector(__a						)

class       snake_case__:

					"""simple docstring"""






					def __init__(							self					:	Any      ,   SCREAMING_SNAKE_CASE					:	list[list[float]]      ,   SCREAMING_SNAKE_CASE					:	int      ,   SCREAMING_SNAKE_CASE					:	int     ):
									lowercase__     :    Any													=     matrix
									lowercase__     :    Any													=     w
									lowercase__     :    Union[str, Any]													=     h







					def __str__(							self					:	Dict     ):
									lowercase__     :    Optional[int]													=     ''''''
									for i in range(self.__height     ):
													ans += "|"
													for j in range(self.__width     ):
																	if j < self.__width - 1:
																					ans += str(self.__matrix[i][j]     ) + ","
																	else:
																					ans += str(self.__matrix[i][j]     ) + "|\n"
									return ans







					def __add__(							self					:	str      ,   SCREAMING_SNAKE_CASE					:	Matrix     ):


									if self.__width == other.width() and self.__height == other.height():
													lowercase__     :    Tuple													=     []
													for i in range(self.__height     ):
																	lowercase__     :    Tuple													=     [
																	    self.__matrix[i][j] + other.component(lowercase_      ,   lowercase_     )
																	    for j in range(self.__width     )
																	]
																	matrix.append(lowercase_     )
													return Matrix(lowercase_      ,   self.__width      ,   self.__height     )
									else:
													raise Exception("matrix must have the same dimension!"     )







					def __sub__(							self					:	Optional[Any]      ,   SCREAMING_SNAKE_CASE					:	Matrix     ):


									if self.__width == other.width() and self.__height == other.height():
													lowercase__     :    Optional[int]													=     []
													for i in range(self.__height     ):
																	lowercase__     :    int													=     [
																	    self.__matrix[i][j] - other.component(lowercase_      ,   lowercase_     )
																	    for j in range(self.__width     )
																	]
																	matrix.append(lowercase_     )
													return Matrix(lowercase_      ,   self.__width      ,   self.__height     )
									else:
													raise Exception("matrices must have the same dimension!"     )







					@overload
					def __mul__(							self					:	str      ,   SCREAMING_SNAKE_CASE					:	float     ):
									...







					@overload
					def __mul__(							self					:	Optional[int]      ,   SCREAMING_SNAKE_CASE					:	Vector     ):
									...







					def __mul__(							self					:	List[str]      ,   SCREAMING_SNAKE_CASE					:	float | Vector     ):


									if isinstance(lowercase_      ,   lowercase_     ):  # matrix-vector
													if len(lowercase_     ) == self.__width:
																	lowercase__     :    Optional[Any]													=     zero_vector(self.__height     )
																	for i in range(self.__height     ):
																					lowercase__     :    int													=     [
																					    self.__matrix[i][j] * other.component(lowercase_     )
																					    for j in range(self.__width     )
																					]
																					ans.change_component(lowercase_      ,   sum(lowercase_     )     )
																	return ans
													else:
																	raise Exception(
																	    "vector must have the same size as the "
																	    "number of columns of the matrix!"     )
									elif isinstance(lowercase_      ,   (int, float)     ):  # matrix-scalar
													lowercase__     :    Optional[Any]													=     [
													    [self.__matrix[i][j] * other for j in range(self.__width     )]
													    for i in range(self.__height     )
													]
													return Matrix(lowercase_      ,   self.__width      ,   self.__height     )
									return None







					def  snake_case     (							self					:	Optional[Any]     ):
									return self.__height







					def  snake_case     (							self					:	Tuple     ):
									return self.__width







					def  snake_case     (							self					:	List[Any]      ,   SCREAMING_SNAKE_CASE					:	int      ,   SCREAMING_SNAKE_CASE					:	int     ):


									if 0 <= x < self.__height and 0 <= y < self.__width:
													return self.__matrix[x][y]
									else:
													raise Exception("change_component: indices out of bounds"     )







					def  snake_case     (							self					:	Optional[Any]      ,   SCREAMING_SNAKE_CASE					:	int      ,   SCREAMING_SNAKE_CASE					:	int      ,   SCREAMING_SNAKE_CASE					:	float     ):


									if 0 <= x < self.__height and 0 <= y < self.__width:
													lowercase__     :    Dict													=     value
									else:
													raise Exception("change_component: indices out of bounds"     )







					def  snake_case     (							self					:	Optional[int]      ,   SCREAMING_SNAKE_CASE					:	int      ,   SCREAMING_SNAKE_CASE					:	int     ):


									if self.__height != self.__width:
													raise Exception("Matrix is not square"     )
									lowercase__     :    int													=     self.__matrix[:x] + self.__matrix[x + 1 :]
									for i in range(len(lowercase_     )     ):
													lowercase__     :    int													=     minor[i][:y] + minor[i][y + 1 :]
									return Matrix(lowercase_      ,   self.__width - 1      ,   self.__height - 1     ).determinant()







					def  snake_case     (							self					:	Tuple      ,   SCREAMING_SNAKE_CASE					:	int      ,   SCREAMING_SNAKE_CASE					:	int     ):


									if self.__height != self.__width:
													raise Exception("Matrix is not square"     )
									if 0 <= x < self.__height and 0 <= y < self.__width:
													return (-1) ** (x + y) * self.minor(lowercase_      ,   lowercase_     )
									else:
													raise Exception("Indices out of bounds"     )







					def  snake_case     (							self					:	List[str]     ):


									if self.__height != self.__width:
													raise Exception("Matrix is not square"     )
									if self.__height < 1:
													raise Exception("Matrix has no element"     )
									elif self.__height == 1:
													return self.__matrix[0][0]
									elif self.__height == 2:
													return (
													    self.__matrix[0][0] * self.__matrix[1][1]
													    - self.__matrix[0][1] * self.__matrix[1][0]
													)
									else:
													lowercase__     :    int													=     [
													    self.__matrix[0][y] * self.cofactor(0      ,   lowercase_     ) for y in range(self.__width     )
													]
													return sum(lowercase_     )






def 					__lowerCamelCase					(   lowerCamelCase__						):

				"""simple docstring"""


				lowercase__     :    list[list[float]]													=     [[0] * n for _ in range(__a						)]
				return Matrix(__a     , __a     , __a						)


def 					__lowerCamelCase					(   lowerCamelCase__     , lowerCamelCase__     , lowerCamelCase__     , lowerCamelCase__						):

				"""simple docstring"""


				random.seed(__a						)
				lowercase__     :    list[list[float]]													=     [
				    [random.randint(__a     , __a						) for _ in range(__a						)] for _ in range(__a						)
				]
				return Matrix(__a     , __a     , __a						)












"""simple docstring"""






import argparse

import torch

from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


logging.set_verbosity_info()



def 					_A			(__a    ,				__a    ,				__a							) ->       Dict:
    """simple docstring"""






    if gpta_config_file == "":
        SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		GPTaConfig()
    else:
        SCREAMING_SNAKE_CASE_      :  Tuple    						=		GPTaConfig.from_json_file(__a							)
    SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		GPTaModel(__a							)

    # Load weights from numpy
    load_tf_weights_in_gpta(__a    ,				__a    ,				__a							)

    # Save pytorch-model
    SCREAMING_SNAKE_CASE_      :  List[str]    						=		pytorch_dump_folder_path + '''/''' + WEIGHTS_NAME
    SCREAMING_SNAKE_CASE_      :  List[Any]    						=		pytorch_dump_folder_path + '''/''' + CONFIG_NAME
    print(f'Save PyTorch model to {pytorch_weights_dump_path}'							)
    torch.save(model.state_dict()    ,				__a							)
    print(f'Save configuration file to {pytorch_config_dump_path}'							)
    with open(__a    ,				'''w'''    ,				encoding='''utf-8'''							) as f:
        f.write(config.to_json_string()							)


if __name__ == "__main__":
  UpperCAmelCase_   : str   			= argparse.ArgumentParser()
  # Required parameters
  parser.add_argument(
      """--gpt2_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
  )
  parser.add_argument(
      """--pytorch_dump_folder_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
  )
  parser.add_argument(
      """--gpt2_config_file""",
      default="""""",
      type=str,
      help=(
          """An optional config json file corresponding to the pre-trained OpenAI model. \n"""
          """This specifies the model architecture."""
      ),
  )
  UpperCAmelCase_   : Union[str, Any]   			= parser.parse_args()
  convert_gpta_checkpoint_to_pytorch(args.gpta_checkpoint_path, args.gpta_config_file, args.pytorch_dump_folder_path)


