
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


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

lowerCAmelCase					:    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 			SCREAMING_SNAKE_CASE__      (     snake_case_):
				lowerCAmelCase_     			=							"""realm"""







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







											'''simple docstring'''






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

											# Common config
											UpperCamelCase   			=     vocab_size
											UpperCamelCase   			=     max_position_embeddings
											UpperCamelCase   			=     hidden_size
											UpperCamelCase   			=     retriever_proj_size
											UpperCamelCase   			=     num_hidden_layers
											UpperCamelCase   			=     num_attention_heads
											UpperCamelCase   			=     num_candidates
											UpperCamelCase   			=     intermediate_size
											UpperCamelCase   			=     hidden_act
											UpperCamelCase   			=     hidden_dropout_prob
											UpperCamelCase   			=     attention_probs_dropout_prob
											UpperCamelCase   			=     initializer_range
											UpperCamelCase   			=     type_vocab_size
											UpperCamelCase   			=     layer_norm_eps

											# Reader config
											UpperCamelCase   			=     span_hidden_size
											UpperCamelCase   			=     max_span_width
											UpperCamelCase   			=     reader_layer_norm_eps
											UpperCamelCase   			=     reader_beam_size
											UpperCamelCase   			=     reader_seq_len

											# Retrieval config
											UpperCamelCase   			=     num_block_records
											UpperCamelCase   			=     searcher_beam_size







'''simple docstring'''







from ...configuration_utils import PretrainedConfig


class        A__   (   _snake_case      ):
    lowercase						       =		"bert-generation"



    def __init__(       self		,					UpperCamelCase__=50358		,					UpperCamelCase__=1024		,					UpperCamelCase__=24		,					UpperCamelCase__=16		,					UpperCamelCase__=4096		,					UpperCamelCase__="gelu"		,					UpperCamelCase__=0.1		,					UpperCamelCase__=0.1		,					UpperCamelCase__=512		,					UpperCamelCase__=0.02		,					UpperCamelCase__=1e-1_2		,					UpperCamelCase__=0		,					UpperCamelCase__=2		,					UpperCamelCase__=1		,					UpperCamelCase__="absolute"		,					UpperCamelCase__=True		,					**UpperCamelCase__		,					)    ->   Any:





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

           A_						       =   vocab_size
           A_						       =   hidden_size
           A_						       =   num_hidden_layers
           A_						       =   num_attention_heads
           A_						       =   hidden_act
           A_						       =   intermediate_size
           A_						       =   hidden_dropout_prob
           A_						       =   attention_probs_dropout_prob
           A_						       =   max_position_embeddings
           A_						       =   initializer_range
           A_						       =   layer_norm_eps
           A_						       =   position_embedding_type
           A_						       =   use_cache
