
'''simple docstring'''







import argparse
from pathlib import Path

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



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Tuple	,			_SCREAMING_SNAKE_CASE		:   str	,			_SCREAMING_SNAKE_CASE		:   str	,			_SCREAMING_SNAKE_CASE		:   Path	,			_SCREAMING_SNAKE_CASE		:   str = None	,			_SCREAMING_SNAKE_CASE		:   str = None	,			_SCREAMING_SNAKE_CASE		:   str = None	,			):
						if config_name_or_path is None:
												_SCREAMING_SNAKE_CASE				= "facebook/rag-token-base" if model_type == "rag_token" else "facebook/rag-sequence-base"

						if generator_tokenizer_name_or_path is None:
												_SCREAMING_SNAKE_CASE				= generator_name_or_path

						if question_encoder_tokenizer_name_or_path is None:
												_SCREAMING_SNAKE_CASE				= question_encoder_name_or_path

						_SCREAMING_SNAKE_CASE				= RagTokenForGeneration if model_type == "rag_token" else RagSequenceForGeneration

						# Save model.
						_SCREAMING_SNAKE_CASE				= RagConfig.from_pretrained(_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE  )

						_SCREAMING_SNAKE_CASE				= gen_config
						_SCREAMING_SNAKE_CASE				= question_encoder_config

						_SCREAMING_SNAKE_CASE				= model_class.from_pretrained_question_encoder_generator(
						    _SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE	,			config=_SCREAMING_SNAKE_CASE  )
						rag_model.save_pretrained(_SCREAMING_SNAKE_CASE  )

						# Sanity check.
						model_class.from_pretrained(_SCREAMING_SNAKE_CASE  )

						# Save tokenizers.
						_SCREAMING_SNAKE_CASE				= AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE  )
						gen_tokenizer.save_pretrained(dest_dir / "generator_tokenizer/"  )
						_SCREAMING_SNAKE_CASE				= AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE  )
						question_encoder_tokenizer.save_pretrained(dest_dir / "question_encoder_tokenizer/"  )


if __name__ == "__main__":
						_snake_case				:   Any     =  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``"""
						    ),
						)

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

						_snake_case				:   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'''







def 			_a		(	_SCREAMING_SNAKE_CASE		:   list[int]	,			_SCREAMING_SNAKE_CASE		:   list[int]  ):

						# Check if the input is valid
						if not len(_SCREAMING_SNAKE_CASE  ) == len(_SCREAMING_SNAKE_CASE  ) == 3:
												raise ValueError("Please enter a valid equation."  )
						if equationa[0] == equationa[1] == equationa[0] == equationa[1] == 0:
												raise ValueError("Both a & b of two equations can't be zero."  )

						# Extract the coefficients
						_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE				= equationa
						_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE				= equationa

						# Calculate the determinants of the matrices
						_SCREAMING_SNAKE_CASE				= aa * ba - aa * ba
						_SCREAMING_SNAKE_CASE				= ca * ba - ca * ba
						_SCREAMING_SNAKE_CASE				= aa * ca - aa * ca

						# Check if the system of linear equations has a solution (using Cramer's rule)
						if determinant == 0:
												if determinant_x == determinant_y == 0:
																		raise ValueError("Infinite solutions. (Consistent system)"  )
												else:
																		raise ValueError("No solution. (Inconsistent system)"  )
						else:
												if determinant_x == determinant_y == 0:
																		# Trivial solution (Inconsistent system)
																		return (0.0, 0.0)
												else:
																		_SCREAMING_SNAKE_CASE				= determinant_x / determinant
																		_SCREAMING_SNAKE_CASE				= determinant_y / determinant
																		# Non-Trivial Solution (Consistent system)
																		return (x, y)