'''simple docstring'''

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


UpperCamelCase__     :	Optional[int]				=			logging.get_logger(__name__)

UpperCamelCase__     :	Dict				=			{}


class 				_lowercase	(      _UpperCAmelCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      Tuple      							=   """llama"""
      UpperCAmelCase_      :      List[str]      							=   ["""past_key_values"""]




      def __init__(				self					,lowerCamelCase_=32000					,lowerCamelCase_=4096					,lowerCamelCase_=11008					,lowerCamelCase_=32					,lowerCamelCase_=32					,lowerCamelCase_=None					,lowerCamelCase_="silu"					,lowerCamelCase_=2048					,lowerCamelCase_=0.02					,lowerCamelCase_=1e-6					,lowerCamelCase_=True					,lowerCamelCase_=0					,lowerCamelCase_=1					,lowerCamelCase_=2					,lowerCamelCase_=1					,lowerCamelCase_=False					,lowerCamelCase_=None					,**lowerCamelCase_					,)			->			Union[str, Any]:



         '''simple docstring'''



         UpperCAmelCase__							:				Tuple   				=  vocab_size
         UpperCAmelCase__							:				Dict   				=  max_position_embeddings
         UpperCAmelCase__							:				List[Any]   				=  hidden_size
         UpperCAmelCase__							:				List[Any]   				=  intermediate_size
         UpperCAmelCase__							:				int   				=  num_hidden_layers
         UpperCAmelCase__							:				Union[str, Any]   				=  num_attention_heads

         # for backward compatibility
         if num_key_value_heads is None:
            UpperCAmelCase__							:				int   				=  num_attention_heads

         UpperCAmelCase__							:				Tuple   				=  num_key_value_heads
         UpperCAmelCase__							:				Optional[Any]   				=  hidden_act
         UpperCAmelCase__							:				Any   				=  initializer_range
         UpperCAmelCase__							:				Any   				=  rms_norm_eps
         UpperCAmelCase__							:				Tuple   				=  pretraining_tp
         UpperCAmelCase__							:				List[Any]   				=  use_cache
         UpperCAmelCase__							:				str   				=  rope_scaling
         self._rope_scaling_validation()

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




      def 		lowerCAmelCase__					(				self							)			->			Optional[Any]:



         '''simple docstring'''



         if self.rope_scaling is None:
            return

         if not isinstance(self.rope_scaling					,lowercase__							) 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}'''							)
         UpperCAmelCase__							:				int   				=  self.rope_scaling.get('''type'''					,lowercase__							)
         UpperCAmelCase__							:				Optional[Any]   				=  self.rope_scaling.get('''factor'''					,lowercase__							)
         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(lowercase__					,lowercase__							) or rope_scaling_factor <= 1.0:
            raise ValueError(f'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''							)





'''simple docstring'''

import unittest

import numpy as np







def __UpperCamelCase(   _A					:				np.ndarray  ,			_A					:				np.ndarray  ,			_A					:				np.ndarray  ,			_A					:				np.ndarray | None = None  ,			):
   '''simple docstring'''
   UpperCAmelCase__							:				Any   				=  np.shape(_A    )
   UpperCAmelCase__							:				List[Any]   				=  np.shape(_A    )
   UpperCAmelCase__							:				Tuple   				=  np.shape(_A    )

   if shape_a[0] != shape_b[0]:
      UpperCAmelCase__							:				Any   				=  (
          '''Expected the same number of rows for A and B. '''
          F'''Instead found A of size {shape_a} and B of size {shape_b}'''
      )
      raise ValueError(_A    )

   if shape_b[1] != shape_c[1]:
      UpperCAmelCase__							:				List[str]   				=  (
          '''Expected the same number of columns for B and C. '''
          F'''Instead found B of size {shape_b} and C of size {shape_c}'''
      )
      raise ValueError(_A    )

   UpperCAmelCase__							:				Optional[Any]   				=  pseudo_inv
   if a_inv is None:
      try:
         UpperCAmelCase__							:				str   				=  np.linalg.inv(_A    )
      except np.linalg.LinAlgError:
         raise ValueError(
             '''Input matrix A is not invertible. Cannot compute Schur complement.'''    )

   return mat_c - mat_b.T @ a_inv @ mat_b


class 				_lowercase	(      unittest.TestCase   ):
      '''simple docstring'''


      def 		lowerCAmelCase__					(				self							)			->			None:



         '''simple docstring'''



         UpperCAmelCase__							:				int   				=  np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]							)
         UpperCAmelCase__							:				List[Any]   				=  np.array([[0, 3], [3, 0], [2, 3]]							)
         UpperCAmelCase__							:				Optional[Any]   				=  np.array([[2, 1], [6, 3]]							)

         UpperCAmelCase__							:				Tuple   				=  schur_complement(lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_							)

         UpperCAmelCase__							:				Tuple   				=  np.block([[a, b], [b.T, c]]							)

         UpperCAmelCase__							:				int   				=  np.linalg.det(lowerCamelCase_							)
         UpperCAmelCase__							:				Optional[Any]   				=  np.linalg.det(lowerCamelCase_							)
         UpperCAmelCase__							:				Union[str, Any]   				=  np.linalg.det(lowerCamelCase_							)

         self.assertAlmostEqual(lowerCamelCase_					,det_a * det_s							)




      def 		lowerCAmelCase__					(				self							)			->			None:



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[Any]   				=  np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]							)
         UpperCAmelCase__							:				Tuple   				=  np.array([[0, 3], [3, 0], [2, 3]]							)
         UpperCAmelCase__							:				Tuple   				=  np.array([[2, 1], [6, 3]]							)

         with self.assertRaises(lowerCamelCase_							):
            schur_complement(lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self							)			->			None:



         '''simple docstring'''



         UpperCAmelCase__							:				Dict   				=  np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]							)
         UpperCAmelCase__							:				str   				=  np.array([[0, 3], [3, 0], [2, 3]]							)
         UpperCAmelCase__							:				Any   				=  np.array([[2, 1, 3], [6, 3, 5]]							)

         with self.assertRaises(lowerCamelCase_							):
            schur_complement(lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_							)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  unittest.main()




