





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


_UpperCAmelCase             =							logging.get_logger(__name__)

_UpperCAmelCase             =							{
    'google/realm-cc-news-pretrained-embedder': (
        'https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json'
    ),
    'google/realm-cc-news-pretrained-encoder': (
        'https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json'
    ),
    'google/realm-cc-news-pretrained-scorer': (
        'https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json'
    ),
    'google/realm-cc-news-pretrained-openqa': (
        'https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json'
    ),
    'google/realm-orqa-nq-openqa': 'https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json',
    'google/realm-orqa-nq-reader': 'https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json',
    'google/realm-orqa-wq-openqa': 'https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json',
    'google/realm-orqa-wq-reader': 'https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json',
    # See all REALM models at https://huggingface.co/models?filter=realm
}






class        snake_case_    (		__lowercase						):
  A_      							=   'realm'






  def __init__(							self			:					List[str]       ,  _snake_case			:					List[str]=30522       ,  _snake_case			:					Union[str, Any]=768       ,  _snake_case			:					List[str]=128       ,  _snake_case			:					Any=12       ,  _snake_case			:					Union[str, Any]=12       ,  _snake_case			:					Union[str, Any]=8       ,  _snake_case			:					Optional[int]=3072       ,  _snake_case			:					Tuple="gelu_new"       ,  _snake_case			:					Optional[Any]=0.1       ,  _snake_case			:					int=0.1       ,  _snake_case			:					Optional[int]=512       ,  _snake_case			:					str=2       ,  _snake_case			:					List[str]=0.02       ,  _snake_case			:					Any=1E-12       ,  _snake_case			:					List[str]=256       ,  _snake_case			:					int=10       ,  _snake_case			:					List[str]=1E-3       ,  _snake_case			:					Optional[int]=5       ,  _snake_case			:					str=320       ,  _snake_case			:					Tuple=13353718       ,  _snake_case			:					int=5000       ,  _snake_case			:					str=1       ,  _snake_case			:					Union[str, Any]=0       ,  _snake_case			:					str=2       ,  **_snake_case			:					Optional[int]       ,  )->Tuple:






   '''simple docstring'''

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

   # Common config
   __lowerCAmelCase					:	Optional[Any]      =       vocab_size
   __lowerCAmelCase					:	Optional[Any]      =       max_position_embeddings
   __lowerCAmelCase					:	Any      =       hidden_size
   __lowerCAmelCase					:	Dict      =       retriever_proj_size
   __lowerCAmelCase					:	Tuple      =       num_hidden_layers
   __lowerCAmelCase					:	str      =       num_attention_heads
   __lowerCAmelCase					:	int      =       num_candidates
   __lowerCAmelCase					:	Any      =       intermediate_size
   __lowerCAmelCase					:	Optional[int]      =       hidden_act
   __lowerCAmelCase					:	int      =       hidden_dropout_prob
   __lowerCAmelCase					:	Optional[int]      =       attention_probs_dropout_prob
   __lowerCAmelCase					:	Union[str, Any]      =       initializer_range
   __lowerCAmelCase					:	Dict      =       type_vocab_size
   __lowerCAmelCase					:	Union[str, Any]      =       layer_norm_eps

   # Reader config
   __lowerCAmelCase					:	Any      =       span_hidden_size
   __lowerCAmelCase					:	Optional[int]      =       max_span_width
   __lowerCAmelCase					:	Any      =       reader_layer_norm_eps
   __lowerCAmelCase					:	Tuple      =       reader_beam_size
   __lowerCAmelCase					:	Dict      =       reader_seq_len

   # Retrieval config
   __lowerCAmelCase					:	Any      =       num_block_records
   __lowerCAmelCase					:	int      =       searcher_beam_size






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:list[list[int | float]]   )      ->   int:
 __lowerCAmelCase					:	str      =       len(SCREAMING_SNAKE_CASE   )
 __lowerCAmelCase					:	Optional[int]      =       len(matrix[0]   )
 __lowerCAmelCase					:	List[Any]      =       min(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   )

 for row in range(SCREAMING_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   ,   SCREAMING_SNAKE_CASE   ):
    __lowerCAmelCase					:	Union[str, Any]      =       matrix[col][row] / matrix[row][row]
    for i in range(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   ):
     matrix[col][i] -= multiplier * matrix[row][i]
  else:
   # Find a non-zero diagonal element to swap rows
   __lowerCAmelCase					:	Optional[int]      =       True
   for i in range(row + 1   ,   SCREAMING_SNAKE_CASE   ):
    if matrix[i][row] != 0:
     __lowerCAmelCase ,					__lowerCAmelCase					:	Union[str, Any]      =       matrix[i], matrix[row]
     __lowerCAmelCase					:	Union[str, Any]      =       False
     break
   if reduce:
    rank -= 1
    for i in range(SCREAMING_SNAKE_CASE   ):
     __lowerCAmelCase					:	int      =       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()