


"""simple docstring"""






from __future__ import annotations

from typing import Any


class     __lowerCamelCase  :

					'''simple docstring'''


					def __init__(      self    ,				__UpperCAmelCase    ,				__UpperCAmelCase    ,				__UpperCAmelCase = 0							)       ->							None:
										_a	,      _a    	=				row, column
										_a    	=				[[default_value for c in range(__UpperCAmelCase							)] for r in range(__UpperCAmelCase							)]


					def __str__(      self							)       ->							str:
										_a    	=				F'Matrix consist of {self.row} rows and {self.column} columns\n'

										# Make string identifier
										_a    	=				0
										for row_vector in self.array:
															for obj in row_vector:
																				_a    	=				max(__UpperCAmelCase    ,				len(str(__UpperCAmelCase							)							)							)
										_a    	=				F'%{max_element_length}s'

										# Make string and return
										def single_line(__UpperCAmelCase							) -> str:
															nonlocal string_format_identifier
															_a    	=				'''['''
															line += ", ".join(string_format_identifier % (obj,) for obj in row_vector							)
															line += "]"
															return line

										s += "\n".join(single_line(__UpperCAmelCase							) for row_vector in self.array							)
										return s


					def __repr__(      self							)       ->							str:
										return str(self							)


					def 							_UpperCAmelCase      (      self    ,				__UpperCAmelCase							)       ->							bool:
										if not (isinstance(__UpperCAmelCase    ,				(list, tuple)							) and len(__UpperCAmelCase							) == 2):
															return False
										elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
															return False
										else:
															return True


					def __getitem__(      self    ,				__UpperCAmelCase							)       ->							Any:
										assert self.validate_indicies(__UpperCAmelCase							)
										return self.array[loc[0]][loc[1]]


					def __setitem__(      self    ,				__UpperCAmelCase    ,				__UpperCAmelCase							)       ->							None:
										assert self.validate_indicies(__UpperCAmelCase							)
										_a    	=				value


					def __add__(      self    ,				__UpperCAmelCase							)       ->							Matrix:
										assert isinstance(__UpperCAmelCase    ,				__UpperCAmelCase							)
										assert self.row == another.row and self.column == another.column

										# Add
										_a    	=				Matrix(self.row    ,				self.column							)
										for r in range(self.row							):
															for c in range(self.column							):
																				_a    	=				self[r, c] + another[r, c]
										return result


					def __neg__(      self							)       ->							Matrix:
										_a    	=				Matrix(self.row    ,				self.column							)
										for r in range(self.row							):
															for c in range(self.column							):
																				_a    	=				-self[r, c]
										return result


					def __sub__(      self    ,				__UpperCAmelCase							)       ->							Matrix:
										return self + (-another)


					def __mul__(      self    ,				__UpperCAmelCase							)       ->							Matrix:

										if isinstance(__UpperCAmelCase    ,				(int, float)							):  # Scalar multiplication
															_a    	=				Matrix(self.row    ,				self.column							)
															for r in range(self.row							):
																				for c in range(self.column							):
																									_a    	=				self[r, c] * another
															return result
										elif isinstance(__UpperCAmelCase    ,				__UpperCAmelCase							):  # Matrix multiplication
															assert self.column == another.row
															_a    	=				Matrix(self.row    ,				another.column							)
															for r in range(self.row							):
																				for c in range(another.column							):
																									for i in range(self.column							):
																														result[r, c] += self[r, i] * another[i, c]
															return result
										else:
															_a    	=				F'Unsupported type given for another ({type(__UpperCAmelCase							)})'
															raise TypeError(__UpperCAmelCase							)


					def 							_UpperCAmelCase      (      self							)       ->							Matrix:
										_a    	=				Matrix(self.column    ,				self.row							)
										for r in range(self.row							):
															for c in range(self.column							):
																				_a    	=				self[r, c]
										return result





					def 							_UpperCAmelCase      (      self    ,				__UpperCAmelCase    ,				__UpperCAmelCase							)       ->							Any:
										assert isinstance(__UpperCAmelCase    ,				__UpperCAmelCase							) and isinstance(__UpperCAmelCase    ,				__UpperCAmelCase							)
										assert self.row == self.column == u.row == v.row  # u, v should be column vector
										assert u.column == v.column == 1  # u, v should be column vector

										# Calculate
										_a    	=				v.transpose()
										_a    	=				(v_t * self * u)[0, 0] + 1
										if numerator_factor == 0:
															return None  # It's not invertable
										return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":
			def       A_   (   ):






								"""simple docstring"""

								_a    	=				Matrix(3,     3,     0       )
								for i in range(3       ):
													_a    	=				1
								print(f'a^(-1) is {ainv}'       )
								# u, v
								_a    	=				Matrix(3,     1,     0       )
								_a	,      _a	,      _a    	=				1, 2, -3
								_a    	=				Matrix(3,     1,     0       )
								_a	,      _a	,      _a    	=				4, -2, 5
								print(f'u is {u}'       )
								print(f'v is {v}'       )
								print(f'uv^T is {u * v.transpose()}'       )
								# Sherman Morrison
								print(f'(a + uv^T)^(-1) is {ainv.sherman_morrison(_lowerCAmelCase,     _lowerCAmelCase       )}'       )
			def       A_   (   ):






								"""simple docstring"""

								import doctest

								doctest.testmod()

			testa()



"""simple docstring"""






import argparse

import torch

from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging


logging.set_verbosity_info()
def       A_   (   _lowerCAmelCase     :					Dict,     _lowerCAmelCase     :					List[Any],     _lowerCAmelCase     :					Union[str, Any]       ):






     """simple docstring"""

     _a    	=				BertConfig.from_json_file(_lowerCAmelCase       )
     print(f'Building PyTorch model from configuration: {config}'       )
     _a    	=				BertForPreTraining(_lowerCAmelCase       )

     # Load weights from tf checkpoint
     load_tf_weights_in_bert(_lowerCAmelCase,     _lowerCAmelCase,     _lowerCAmelCase       )

     # Save pytorch-model
     print(f'Save PyTorch model to {pytorch_dump_path}'       )
     torch.save(model.state_dict(),     _lowerCAmelCase       )


if __name__ == "__main__":
   __snake_case		=       argparse.ArgumentParser()
   # Required parameters
   parser.add_argument(
       '''--tf_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
   )
   parser.add_argument(
       '''--bert_config_file''',
       default=None,
       type=str,
       required=True,
       help=(
           '''The config json file corresponding to the pre-trained BERT model. \n'''
           '''This specifies the model architecture.'''
       ),
   )
   parser.add_argument(
       '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
   )
   __snake_case		=       parser.parse_args()
   convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)