


"""simple docstring"""





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


snake_case__		:     str    				=				logging.get_logger(__name__)

snake_case__		:     Union[str, Any]    				=				{
    '''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__			):
     __UpperCamelCase  =					'''realm'''






     def __init__(	self  :					Optional[int]					,				UpperCamelCase_  :					Tuple=3_0_5_2_2					,				UpperCamelCase_  :					Tuple=7_6_8					,				UpperCamelCase_  :					List[str]=1_2_8					,				UpperCamelCase_  :					List[str]=1_2					,				UpperCamelCase_  :					Union[str, Any]=1_2					,				UpperCamelCase_  :					Dict=8					,				UpperCamelCase_  :					Dict=3_0_7_2					,				UpperCamelCase_  :					List[Any]="gelu_new"					,				UpperCamelCase_  :					Optional[Any]=0.1					,				UpperCamelCase_  :					List[str]=0.1					,				UpperCamelCase_  :					List[str]=5_1_2					,				UpperCamelCase_  :					List[Any]=2					,				UpperCamelCase_  :					Dict=0.02					,				UpperCamelCase_  :					List[str]=1E-12					,				UpperCamelCase_  :					Any=2_5_6					,				UpperCamelCase_  :					Optional[int]=1_0					,				UpperCamelCase_  :					int=1E-3					,				UpperCamelCase_  :					str=5					,				UpperCamelCase_  :					Optional[Any]=3_2_0					,				UpperCamelCase_  :					Any=1_3_3_5_3_7_1_8					,				UpperCamelCase_  :					Optional[Any]=5_0_0_0					,				UpperCamelCase_  :					Union[str, Any]=1					,				UpperCamelCase_  :					Tuple=0					,				UpperCamelCase_  :					Optional[Any]=2					,				**UpperCamelCase_  :					Optional[Any]					,				):
           super().__init__(pad_token_id=UpperCamelCase_					,				bos_token_id=UpperCamelCase_					,				eos_token_id=UpperCamelCase_					,				**UpperCamelCase_				)

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

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

           # Retrieval config
           lowerCAmelCase					:	int       =   num_block_records
           lowerCAmelCase					:	Union[str, Any]       =   searcher_beam_size









"""simple docstring"""





from __future__ import annotations

from typing import Any



class 		snake_case_(       a__			):
     pass



class 		snake_case_:






     def __init__(	self  :					Any					,				UpperCamelCase_  :					Any				):
           lowerCAmelCase					:	Any       =   data
           lowerCAmelCase					:	Node | None       =   None






     def __iter__(	self  :					int				):
           lowerCAmelCase					:	Any       =   self
           lowerCAmelCase					:	Union[str, Any]       =   []
           while node:
                 if node in visited:
                       raise ContainsLoopError
                 visited.append(UpperCamelCase_				)
                 yield node.data
                 lowerCAmelCase					:	Optional[int]       =   node.next_node






     @property
     def      lowerCamelCase__     (	self  :					str				):
           try:
                 list(self				)
                 return False
           except ContainsLoopError:
                 return True


if __name__ == "__main__":
 snake_case__		:     Dict    				=				Node(1)
 snake_case__		:     Any    				=				Node(2)
 snake_case__		:     int    				=				Node(3)
 snake_case__		:     Any    				=				Node(4)
 print(root_node.has_loop)  # False
 snake_case__		:     Tuple    				=				root_node.next_node
 print(root_node.has_loop)  # True

 snake_case__		:     List[Any]    				=				Node(5)
 snake_case__		:     int    				=				Node(6)
 snake_case__		:     List[Any]    				=				Node(5)
 snake_case__		:     Dict    				=				Node(6)
 print(root_node.has_loop)  # False

 snake_case__		:     Any    				=				Node(1)
 print(root_node.has_loop)  # False


