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


snake_case :		Union[str, Any]							      =  logging.get_logger(__name__)

snake_case :		Any							      =  {}





class       _snake_case					(     snake_case				):
			UpperCamelCase__          =    'llama'
			UpperCamelCase__          =    ['past_key_values']







			def __init__(				self						,   _a=32_000						,   _a=4_096						,   _a=11_008						,   _a=32						,   _a=32						,   _a=None						,   _a="silu"						,   _a=2_048						,   _a=0.02						,   _a=1e-6						,   _a=True						,   _a=0						,   _a=1						,   _a=2						,   _a=1						,   _a=False						,   _a=None						,   **_a						,   ):
				__magic_name__		:		Optional[Any]	   =     vocab_size
				__magic_name__		:		List[str]	   =     max_position_embeddings
				__magic_name__		:		Dict	   =     hidden_size
				__magic_name__		:		Tuple	   =     intermediate_size
				__magic_name__		:		Any	   =     num_hidden_layers
				__magic_name__		:		Union[str, Any]	   =     num_attention_heads

				# for backward compatibility
				if num_key_value_heads is None:
					__magic_name__		:		List[str]	   =     num_attention_heads

				__magic_name__		:		Union[str, Any]	   =     num_key_value_heads
				__magic_name__		:		str	   =     hidden_act
				__magic_name__		:		List[str]	   =     initializer_range
				__magic_name__		:		List[str]	   =     rms_norm_eps
				__magic_name__		:		Optional[int]	   =     pretraining_tp
				__magic_name__		:		Any	   =     use_cache
				__magic_name__		:		Optional[int]	   =     rope_scaling
				self._rope_scaling_validation()

				super().__init__(
				    pad_token_id=_a						,   bos_token_id=_a						,   eos_token_id=_a						,   tie_word_embeddings=_a						,   **_a						,   )







			def 			SCREAMING_SNAKE_CASE    (				self		):
				if self.rope_scaling is None:
					return

				if not isinstance(self.rope_scaling						,   _a		) or len(self.rope_scaling		) != 2:
					raise ValueError(
					    "`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, "
					    f'''got {self.rope_scaling}'''		)
				__magic_name__		:		Optional[Any]	   =     self.rope_scaling.get("type"						,   _a		)
				__magic_name__		:		Dict	   =     self.rope_scaling.get("factor"						,   _a		)
				if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
					raise ValueError(
					    f'''`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'''		)
				if rope_scaling_factor is None or not isinstance(_a						,   _a		) or rope_scaling_factor <= 1.0:
					raise ValueError(f'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''		)


def   lowerCAmelCase_						(					_snake_case      :  list[list[int | float]]   )				->		int:







	'''simple docstring'''


	__magic_name__		:		Any	   =     len(_snake_case   )
	__magic_name__		:		Optional[Any]	   =     len(matrix[0]   )
	__magic_name__		:		Union[str, Any]	   =     min(_snake_case      ,   _snake_case   )

	for row in range(_snake_case   ):
		# Check if diagonal element is not zero
		if matrix[row][row] != 0:
			# Eliminate all the elements below the diagonal
			for col in range(row + 1      ,   _snake_case   ):
				__magic_name__		:		Optional[Any]	   =     matrix[col][row] / matrix[row][row]
				for i in range(_snake_case      ,   _snake_case   ):
					matrix[col][i] -= multiplier * matrix[row][i]
		else:
			# Find a non-zero diagonal element to swap rows
			__magic_name__		:		str	   =     True
			for i in range(row + 1      ,   _snake_case   ):
				if matrix[i][row] != 0:
					__magic_name__   ,    __magic_name__		:		List[str]	   =     matrix[i], matrix[row]
					__magic_name__		:		Union[str, Any]	   =     False
					break
			if reduce:
				rank -= 1
				for i in range(_snake_case   ):
					__magic_name__		:		Any	   =     matrix[i][rank]

            # Reduce the row pointer by one to stay on the same row
			row -= 1

	return rank


if __name__ == "__main__":
				import doctest

				doctest.testmod()
