


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


__SCREAMING_SNAKE_CASE							:    Dict		=    logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE							:    Dict		=    {
    '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      __A     (snake_case__):





							'''simple docstring'''

							__lowercase:		List[Any]							      =    """realm"""



							def __init__(				self							:      Optional[int]		,       UpperCAmelCase_							:      str=30_522		,       UpperCAmelCase_							:      Any=768		,       UpperCAmelCase_							:      Optional[Any]=128		,       UpperCAmelCase_							:      int=12		,       UpperCAmelCase_							:      List[str]=12		,       UpperCAmelCase_							:      Union[str, Any]=8		,       UpperCAmelCase_							:      Optional[Any]=3_072		,       UpperCAmelCase_							:      str="gelu_new"		,       UpperCAmelCase_							:      Optional[Any]=0.1		,       UpperCAmelCase_							:      Optional[int]=0.1		,       UpperCAmelCase_							:      Optional[Any]=512		,       UpperCAmelCase_							:      Optional[int]=2		,       UpperCAmelCase_							:      Dict=0.02		,       UpperCAmelCase_							:      List[Any]=1E-12		,       UpperCAmelCase_							:      Optional[int]=256		,       UpperCAmelCase_							:      Optional[Any]=10		,       UpperCAmelCase_							:      Any=1E-3		,       UpperCAmelCase_							:      Tuple=5		,       UpperCAmelCase_							:      Optional[int]=320		,       UpperCAmelCase_							:      Dict=13_353_718		,       UpperCAmelCase_							:      List[str]=5_000		,       UpperCAmelCase_							:      Union[str, Any]=1		,       UpperCAmelCase_							:      Optional[Any]=0		,       UpperCAmelCase_							:      Tuple=2		,       **UpperCAmelCase_							:      List[Any]		,       )					->Union[str, Any]:



														"""simple docstring"""



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

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

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

														# Retrieval config
														snake_case_           =		num_block_records
														snake_case_           =		searcher_beam_size







"""simple docstring"""
from __future__ import annotations







def 						_a				(      _SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)    ->				list[int]:
							snake_case_           =		0
							snake_case_           =		len(_SCREAMING_SNAKE_CASE				) - 1

							while i < j:
														if nums[i] + nums[j] == target:
																					return [i, j]
														elif nums[i] + nums[j] < target:
																					snake_case_           =		i + 1
														else:
																					snake_case_           =		j - 1

							return []


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				print(f"""{two_pointer([2, 7, 11, 15], 9) = }""")



