
'''simple docstring'''


import argparse
from pathlib import Path

from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration




def lowercase_	(   _lowercase			,       _lowercase			,       _lowercase			,       _lowercase			,       _lowercase = None			,       _lowercase = None			,       _lowercase = None			,       )     ->							Dict:
     '''simple docstring'''

     if config_name_or_path is None:
          lowerCamelCase_					:      Union[str, Any]     =		'''facebook/rag-token-base''' if model_type == '''rag_token''' else '''facebook/rag-sequence-base'''

     if generator_tokenizer_name_or_path is None:
          lowerCamelCase_					:      str     =		generator_name_or_path

     if question_encoder_tokenizer_name_or_path is None:
          lowerCamelCase_					:      List[Any]     =		question_encoder_name_or_path

     lowerCamelCase_					:      Dict     =		RagTokenForGeneration if model_type == '''rag_token''' else RagSequenceForGeneration

     # Save model.
     lowerCamelCase_					:      str     =		RagConfig.from_pretrained(lowerCamelCase_				)
     lowerCamelCase_					:      Optional[int]     =		AutoConfig.from_pretrained(lowerCamelCase_				)
     lowerCamelCase_					:      List[Any]     =		AutoConfig.from_pretrained(lowerCamelCase_				)

     lowerCamelCase_					:      Tuple     =		gen_config
     lowerCamelCase_					:      Dict     =		question_encoder_config

     lowerCamelCase_					:      str     =		model_class.from_pretrained_question_encoder_generator(
         lowerCamelCase_			,       lowerCamelCase_			,       config=lowerCamelCase_				)
     rag_model.save_pretrained(lowerCamelCase_				)

     # Sanity check.
     model_class.from_pretrained(lowerCamelCase_				)

     # Save tokenizers.
     lowerCamelCase_					:      Optional[Any]     =		AutoTokenizer.from_pretrained(lowerCamelCase_				)
     gen_tokenizer.save_pretrained(dest_dir / '''generator_tokenizer/'''				)
     lowerCamelCase_					:      str     =		AutoTokenizer.from_pretrained(lowerCamelCase_				)
     question_encoder_tokenizer.save_pretrained(dest_dir / '''question_encoder_tokenizer/'''				)


if __name__ == "__main__":
     __lowercase							:   str					=     argparse.ArgumentParser()
     parser.add_argument(
         '''--model_type''',
         choices=['''rag_sequence''', '''rag_token'''],
         required=True,
         type=str,
         help='''RAG model type: rag_sequence, rag_token''',
     )
     parser.add_argument('''--dest''', type=str, required=True, help='''Path to the output checkpoint directory.''')
     parser.add_argument('''--generator_name_or_path''', type=str, required=True, help='''Generator model identifier''')
     parser.add_argument(
         '''--question_encoder_name_or_path''', type=str, required=True, help='''Question encoder model identifier'''
     )

     parser.add_argument(
         '''--generator_tokenizer_name_or_path''',
         type=str,
         help='''Generator tokenizer identifier, if not specified, resolves to ``generator_name_or_path``''',
     )
     parser.add_argument(
         '''--question_encoder_tokenizer_name_or_path''',
         type=str,
         help='''Question encoder tokenizer identifier, if not specified, resolves to ``question_encoder_name_or_path``''',
     )
     parser.add_argument(
         '''--config_name_or_path''',
         type=str,
         help=(
             '''Identifier of the model config to use, if not provided, resolves to a base config for a given'''
             ''' ``model_type``'''
         ),
     )

     __lowercase							:   List[str]					=     parser.parse_args()

     __lowercase							:   Optional[int]					=     Path(args.dest)
     dest_dir.mkdir(exist_ok=True)

     consolidate(
         args.model_type,
         args.generator_name_or_path,
         args.question_encoder_name_or_path,
         dest_dir,
         args.config_name_or_path,
         args.generator_tokenizer_name_or_path,
         args.question_encoder_tokenizer_name_or_path,
     )




'''simple docstring'''


from __future__ import annotations

from decimal import Decimal

from numpy import array




def lowercase_	(   _lowercase				)     ->							list[list[float]]:
					'''simple docstring'''

					lowerCamelCase_					:      Tuple     =		Decimal

					# Check if the provided matrix has 2 rows and 2 columns
					# since this implementation only works for 2x2 matrices
					if len(_lowercase				) == 2 and len(matrix[0]				) == 2 and len(matrix[1]				) == 2:
										# Calculate the determinant of the matrix
										lowerCamelCase_					:      Union[str, Any]     =		float(
										    d(matrix[0][0]				) * d(matrix[1][1]				) - d(matrix[1][0]				) * d(matrix[0][1]				)				)
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''				)

										# Creates a copy of the matrix with swapped positions of the elements
										lowerCamelCase_					:      Optional[Any]     =		[[0.0, 0.0], [0.0, 0.0]]
										lowerCamelCase_,      lowerCamelCase_					:      int     =		matrix[1][1], matrix[0][0]
										lowerCamelCase_,      lowerCamelCase_					:      Dict     =		-matrix[1][0], -matrix[0][1]

										# Calculate the inverse of the matrix
										return [
										    [(float(d(_lowercase				)				) / determinant) or 0.0 for n in row] for row in swapped_matrix
										]
					elif (
					    len(_lowercase				) == 3
					    and len(matrix[0]				) == 3
					    and len(matrix[1]				) == 3
					    and len(matrix[2]				) == 3
					):
										# Calculate the determinant of the matrix using Sarrus rule
										lowerCamelCase_					:      Tuple     =		float(
										    (
										        (d(matrix[0][0]				) * d(matrix[1][1]				) * d(matrix[2][2]				))
										        + (d(matrix[0][1]				) * d(matrix[1][2]				) * d(matrix[2][0]				))
										        + (d(matrix[0][2]				) * d(matrix[1][0]				) * d(matrix[2][1]				))
										    )
										    - (
										        (d(matrix[0][2]				) * d(matrix[1][1]				) * d(matrix[2][0]				))
										        + (d(matrix[0][1]				) * d(matrix[1][0]				) * d(matrix[2][2]				))
										        + (d(matrix[0][0]				) * d(matrix[1][2]				) * d(matrix[2][1]				))
										    )				)
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''				)

										# Creating cofactor matrix
										lowerCamelCase_					:      Any     =		[
										    [d(0.0				), d(0.0				), d(0.0				)],
										    [d(0.0				), d(0.0				), d(0.0				)],
										    [d(0.0				), d(0.0				), d(0.0				)],
										]
										lowerCamelCase_					:      Union[str, Any]     =		(d(matrix[1][1]				) * d(matrix[2][2]				)) - (
										    d(matrix[1][2]				) * d(matrix[2][1]				)
										)
										lowerCamelCase_					:      Any     =		-(
										    (d(matrix[1][0]				) * d(matrix[2][2]				)) - (d(matrix[1][2]				) * d(matrix[2][0]				))
										)
										lowerCamelCase_					:      Tuple     =		(d(matrix[1][0]				) * d(matrix[2][1]				)) - (
										    d(matrix[1][1]				) * d(matrix[2][0]				)
										)
										lowerCamelCase_					:      Optional[Any]     =		-(
										    (d(matrix[0][1]				) * d(matrix[2][2]				)) - (d(matrix[0][2]				) * d(matrix[2][1]				))
										)
										lowerCamelCase_					:      Tuple     =		(d(matrix[0][0]				) * d(matrix[2][2]				)) - (
										    d(matrix[0][2]				) * d(matrix[2][0]				)
										)
										lowerCamelCase_					:      List[Any]     =		-(
										    (d(matrix[0][0]				) * d(matrix[2][1]				)) - (d(matrix[0][1]				) * d(matrix[2][0]				))
										)
										lowerCamelCase_					:      Any     =		(d(matrix[0][1]				) * d(matrix[1][2]				)) - (
										    d(matrix[0][2]				) * d(matrix[1][1]				)
										)
										lowerCamelCase_					:      Tuple     =		-(
										    (d(matrix[0][0]				) * d(matrix[1][2]				)) - (d(matrix[0][2]				) * d(matrix[1][0]				))
										)
										lowerCamelCase_					:      str     =		(d(matrix[0][0]				) * d(matrix[1][1]				)) - (
										    d(matrix[0][1]				) * d(matrix[1][0]				)
										)

										# Transpose the cofactor matrix (Adjoint matrix)
										lowerCamelCase_					:      str     =		array(_lowercase				)
										for i in range(3				):
															for j in range(3				):
																				lowerCamelCase_					:      int     =		cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
										lowerCamelCase_					:      int     =		array(_lowercase				)
										for i in range(3				):
															for j in range(3				):
																				inverse_matrix[i][j] /= d(_lowercase				)

        # Calculate the inverse of the matrix
										return [[float(d(_lowercase				)				) or 0.0 for n in row] for row in inverse_matrix]
					raise ValueError('''Please provide a matrix of size 2x2 or 3x3.'''				)


