



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


SCREAMING_SNAKE_CASE_				= logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_				= {
    """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_						(						a_				):
							__lowerCAmelCase    					=					"realm"






							def __init__(   self			,     a_=3_0_5_2_2			,     a_=7_6_8			,     a_=1_2_8			,     a_=1_2			,     a_=1_2			,     a_=8			,     a_=3_0_7_2			,     a_="gelu_new"			,     a_=0.1			,     a_=0.1			,     a_=5_1_2			,     a_=2			,     a_=0.02			,     a_=1e-12			,     a_=2_5_6			,     a_=1_0			,     a_=1e-3			,     a_=5			,     a_=3_2_0			,     a_=1_3_3_5_3_7_1_8			,     a_=5_0_0_0			,     a_=1			,     a_=0			,     a_=2			,     **a_			,     ):
									super().__init__(pad_token_id=a_			,     bos_token_id=a_			,     eos_token_id=a_			,     **a_      )

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

									# Reader config
									a_     :      str 						=     span_hidden_size
									a_     :      Union[str, Any] 						=     max_span_width
									a_     :      Tuple 						=     reader_layer_norm_eps
									a_     :      List[Any] 						=     reader_beam_size
									a_     :      str 						=     reader_seq_len

									# Retrieval config
									a_     :      str 						=     num_block_records
									a_     :      int 						=     searcher_beam_size




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


SCREAMING_SNAKE_CASE_				= logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_				= {
    """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_						(						a_				):
							__lowerCAmelCase    					=					"realm"






							def __init__(   self			,     a_=3_0_5_2_2			,     a_=7_6_8			,     a_=1_2_8			,     a_=1_2			,     a_=1_2			,     a_=8			,     a_=3_0_7_2			,     a_="gelu_new"			,     a_=0.1			,     a_=0.1			,     a_=5_1_2			,     a_=2			,     a_=0.02			,     a_=1e-12			,     a_=2_5_6			,     a_=1_0			,     a_=1e-3			,     a_=5			,     a_=3_2_0			,     a_=1_3_3_5_3_7_1_8			,     a_=5_0_0_0			,     a_=1			,     a_=0			,     a_=2			,     **a_			,     ):
									super().__init__(pad_token_id=a_			,     bos_token_id=a_			,     eos_token_id=a_			,     **a_      )

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

									# Reader config
									a_     :      str 						=     span_hidden_size
									a_     :      Union[str, Any] 						=     max_span_width
									a_     :      Tuple 						=     reader_layer_norm_eps
									a_     :      List[Any] 						=     reader_beam_size
									a_     :      str 						=     reader_seq_len

									# Retrieval config
									a_     :      str 						=     num_block_records
									a_     :      int 						=     searcher_beam_size