



'''simple docstring'''





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


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

A__    :   int           =					{
    '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__						(    snake_case_				):
 A__				= '''realm'''
 def __init__(   self						:							int      ,     __a						:							str=30522      ,     __a						:							List[str]=768      ,     __a						:							Optional[int]=128      ,     __a						:							Any=12      ,     __a						:							Optional[Any]=12      ,     __a						:							int=8      ,     __a						:							str=3072      ,     __a						:							List[Any]="gelu_new"      ,     __a						:							Dict=0.1      ,     __a						:							Tuple=0.1      ,     __a						:							List[Any]=512      ,     __a						:							Any=2      ,     __a						:							List[str]=0.0_2      ,     __a						:							List[Any]=1e-12      ,     __a						:							Any=256      ,     __a						:							Tuple=10      ,     __a						:							List[str]=1e-3      ,     __a						:							Any=5      ,     __a						:							List[Any]=320      ,     __a						:							str=13353718      ,     __a						:							Dict=5000      ,     __a						:							Optional[Any]=1      ,     __a						:							List[str]=0      ,     __a						:							Any=2      ,     **__a						:							Optional[Any]      ,     )      ->   List[Any]:







       '''simple docstring'''
       super().__init__(pad_token_id=A_      ,     bos_token_id=A_      ,     eos_token_id=A_      ,     **A_  )

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

       # Reader config
       __snake_case :   Dict													=    span_hidden_size
       __snake_case :   Optional[Any]													=    max_span_width
       __snake_case :   Any													=    reader_layer_norm_eps
       __snake_case :   Optional[Any]													=    reader_beam_size
       __snake_case :   Optional[Any]													=    reader_seq_len

       # Retrieval config
       __snake_case :   List[str]													=    num_block_records
       __snake_case :   Union[str, Any]													=    searcher_beam_size





'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase







def 		A_(     A						:		str):
							if not sentence:
														return ""
							UpperCamelCase   			=     dict(zip(A		,     A))
							return lower_to_upper.get(sentence[0]		,     sentence[0]) + sentence[1:]


if __name__ == "__main__":
						from doctest import testmod

						testmod()




