






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


snake_case     					=		logging.get_logger(__name__)

snake_case     					=		{
    "bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/config.json",
    "bert-large-uncased": "https://huggingface.co/bert-large-uncased/resolve/main/config.json",
    "bert-base-cased": "https://huggingface.co/bert-base-cased/resolve/main/config.json",
    "bert-large-cased": "https://huggingface.co/bert-large-cased/resolve/main/config.json",
    "bert-base-multilingual-uncased": "https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json",
    "bert-base-multilingual-cased": "https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json",
    "bert-base-chinese": "https://huggingface.co/bert-base-chinese/resolve/main/config.json",
    "bert-base-german-cased": "https://huggingface.co/bert-base-german-cased/resolve/main/config.json",
    "bert-large-uncased-whole-word-masking": (
        "https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json"
    ),
    "bert-large-cased-whole-word-masking": (
        "https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json"
    ),
    "bert-large-uncased-whole-word-masking-finetuned-squad": (
        "https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json"
    ),
    "bert-large-cased-whole-word-masking-finetuned-squad": (
        "https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json"
    ),
    "bert-base-cased-finetuned-mrpc": "https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json",
    "bert-base-german-dbmdz-cased": "https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json",
    "bert-base-german-dbmdz-uncased": "https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json",
    "cl-tohoku/bert-base-japanese": "https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json",
    "cl-tohoku/bert-base-japanese-whole-word-masking": (
        "https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json"
    ),
    "cl-tohoku/bert-base-japanese-char": (
        "https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json"
    ),
    "cl-tohoku/bert-base-japanese-char-whole-word-masking": (
        "https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json"
    ),
    "TurkuNLP/bert-base-finnish-cased-v1": (
        "https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json"
    ),
    "TurkuNLP/bert-base-finnish-uncased-v1": (
        "https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json"
    ),
    "wietsedv/bert-base-dutch-cased": "https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json",
    # See all BERT models at https://huggingface.co/models?filter=bert
}


class 			SCREAMING_SNAKE_CASE      (      _a       ):
     '''simple docstring'''


     UpperCamelCase_				:		Any								=						"""bert"""


     def __init__(					self							:						str       ,			UpperCAmelCase_							:						List[Any]=3_0522       ,			UpperCAmelCase_							:						Any=768       ,			UpperCAmelCase_							:						List[str]=12       ,			UpperCAmelCase_							:						int=12       ,			UpperCAmelCase_							:						Optional[int]=3072       ,			UpperCAmelCase_							:						Dict="gelu"       ,			UpperCAmelCase_							:						int=0.1       ,			UpperCAmelCase_							:						Optional[int]=0.1       ,			UpperCAmelCase_							:						str=512       ,			UpperCAmelCase_							:						Optional[Any]=2       ,			UpperCAmelCase_							:						Optional[int]=0.02       ,			UpperCAmelCase_							:						str=1E-12       ,			UpperCAmelCase_							:						int=0       ,			UpperCAmelCase_							:						str="absolute"       ,			UpperCAmelCase_							:						Tuple=True       ,			UpperCAmelCase_							:						List[str]=None       ,			**UpperCAmelCase_							:						Optional[int]       ,			):
       super().__init__(pad_token_id=UpperCAmelCase_       ,			**UpperCAmelCase_   )

       SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     vocab_size
       SCREAMING_SNAKE_CASE							:   Union[str, Any]						    =     hidden_size
       SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     num_hidden_layers
       SCREAMING_SNAKE_CASE							:   str						    =     num_attention_heads
       SCREAMING_SNAKE_CASE							:   Tuple						    =     hidden_act
       SCREAMING_SNAKE_CASE							:   Tuple						    =     intermediate_size
       SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     hidden_dropout_prob
       SCREAMING_SNAKE_CASE							:   Dict						    =     attention_probs_dropout_prob
       SCREAMING_SNAKE_CASE							:   Dict						    =     max_position_embeddings
       SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     type_vocab_size
       SCREAMING_SNAKE_CASE							:   List[Any]						    =     initializer_range
       SCREAMING_SNAKE_CASE							:   Tuple						    =     layer_norm_eps
       SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     position_embedding_type
       SCREAMING_SNAKE_CASE							:   Dict						    =     use_cache
       SCREAMING_SNAKE_CASE							:   List[str]						    =     classifier_dropout





class 			SCREAMING_SNAKE_CASE      (      _a       ):
     '''simple docstring'''


     @property
     def 					_A							(					self							:						int   ):

       if self.task == "multiple-choice":
         SCREAMING_SNAKE_CASE							:   str						    =     {0: 'batch', 1: 'choice', 2: 'sequence'}
       else:
         SCREAMING_SNAKE_CASE							:   int						    =     {0: 'batch', 1: 'sequence'}
       return OrderedDict(
           [
               ("input_ids", dynamic_axis),
               ("attention_mask", dynamic_axis),
               ("token_type_ids", dynamic_axis),
           ]   )










def 							UpperCamelCase_( lowerCamelCase_					)       ->		int:

    if not isinstance(lowerCamelCase_				,					lowerCamelCase_					):
        raise ValueError('multiplicative_persistence() only accepts integral values'					)
    if num < 0:
        raise ValueError('multiplicative_persistence() does not accept negative values'					)

    _lowercase			:				List[str] 						=						0
    _lowercase			:				Optional[int] 						=						str(lowerCamelCase_					)

    while len(lowerCamelCase_					) != 1:
        _lowercase			:				Any 						=						[int(lowerCamelCase_					) for i in num_string]

        _lowercase			:				List[Any] 						=						1
        for i in range(0				,					len(lowerCamelCase_					)					):
            total *= numbers[i]

        _lowercase			:				Optional[Any] 						=						str(lowerCamelCase_					)

        steps += 1
    return steps



def 							UpperCamelCase_( lowerCamelCase_					)       ->		int:

    if not isinstance(lowerCamelCase_				,					lowerCamelCase_					):
        raise ValueError('additive_persistence() only accepts integral values'					)
    if num < 0:
        raise ValueError('additive_persistence() does not accept negative values'					)

    _lowercase			:				Optional[int] 						=						0
    _lowercase			:				str 						=						str(lowerCamelCase_					)

    while len(lowerCamelCase_					) != 1:
        _lowercase			:				Dict 						=						[int(lowerCamelCase_					) for i in num_string]

        _lowercase			:				Any 						=						0
        for i in range(0				,					len(lowerCamelCase_					)					):
            total += numbers[i]

        _lowercase			:				Dict 						=						str(lowerCamelCase_					)

        steps += 1
    return steps


if __name__ == "__main__":
 import doctest

 doctest.testmod()


