


'''simple docstring'''



import numpy as np




def 	_a	(						_lowercase					:	List[Any]  ):





     '''simple docstring'''






     __UpperCAmelCase							,   __UpperCAmelCase	: str  							=			a.shape
     __UpperCAmelCase	: Optional[Any]  							=			min(__UpperCamelCase			,					__UpperCamelCase  )
     __UpperCAmelCase	: Dict  							=			np.eye(__UpperCamelCase  )
     __UpperCAmelCase	: Optional[int]  							=			a.copy()

     for k in range(t - 1  ):
          # select a column of modified matrix A':
          __UpperCAmelCase	: Tuple  							=			r[k:, [k]]
          # construct first basis vector
          __UpperCAmelCase	: str  							=			np.zeros_like(__UpperCamelCase  )
          __UpperCAmelCase	: Optional[int]  							=			1.0
          # determine scaling factor
          __UpperCAmelCase	: List[str]  							=			np.linalg.norm(__UpperCamelCase  )
          # construct vector v for Householder reflection
          __UpperCAmelCase	: Optional[int]  							=			x + np.sign(x[0]  ) * alpha * ea
          v /= np.linalg.norm(__UpperCamelCase  )

          # construct the Householder matrix
          __UpperCAmelCase	: Union[str, Any]  							=			np.eye(m - k  ) - 2.0 * v @ v.T
          # pad with ones and zeros as necessary
          __UpperCAmelCase	: List[str]  							=			np.block([[np.eye(__UpperCamelCase  ), np.zeros((k, m - k)  )], [np.zeros((m - k, k)  ), q_k]]  )

          __UpperCAmelCase	: Optional[int]  							=			q @ q_k.T
          __UpperCAmelCase	: Dict  							=			q_k @ r

     return q, r


if __name__ == "__main__":
      import doctest

      doctest.testmod()





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


lowercase__      :			Optional[Any]           =					logging.get_logger(__name__)

lowercase__      :			Optional[int]           =					{
    "uw-madison/yoso-4096": "https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json",
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}




class 			a__       (					UpperCamelCase__      ):
     a		:			Dict							=	"""yoso"""







     def __init__(	self  ,		A=50265  ,		A=768  ,		A=12  ,		A=12  ,		A=3072  ,		A="gelu"  ,		A=0.1  ,		A=0.1  ,		A=4096  ,		A=1  ,		A=0.0_2  ,		A=1e-12  ,		A="absolute"  ,		A=True  ,		A=9  ,		A=64  ,		A=None  ,		A=True  ,		A=True  ,		A=1  ,		A=0  ,		A=2  ,		**A  ,		)  ->    Dict:



          '''simple docstring'''



          super().__init__(pad_token_id=A  ,		bos_token_id=A  ,		eos_token_id=A  ,		**A )

          a      =      vocab_size
          a      =      max_position_embeddings
          a      =      hidden_size
          a      =      num_hidden_layers
          a      =      num_attention_heads
          a      =      intermediate_size
          a      =      hidden_act
          a      =      hidden_dropout_prob
          a      =      attention_probs_dropout_prob
          a      =      initializer_range
          a      =      type_vocab_size
          a      =      layer_norm_eps
          a      =      position_embedding_type
          a      =      use_expectation
          a      =      hash_code_len
          a      =      num_hash
          a      =      conv_window
          a      =      use_fast_hash
          a      =      lsh_backward

