






from collections import OrderedDict
from typing import Mapping

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


snake_case_   :	Optional[Any]							      =logging.get_logger(__name__)

snake_case_   :	Dict							      ={
    '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/config.json''',
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}





class        a__      (	lowerCAmelCase__		):
		UpperCAmelCase_							:       str 					= 'rembert'






		def __init__(      self							, lowercase__=250300							, lowercase__=1152							, lowercase__=32							, lowercase__=18							, lowercase__=256							, lowercase__=1664							, lowercase__=4608							, lowercase__="gelu"							, lowercase__=0.0							, lowercase__=0.0							, lowercase__=0.1							, lowercase__=512							, lowercase__=2							, lowercase__=0.02							, lowercase__=1e-12							, lowercase__=True							, lowercase__=0							, lowercase__=312							, lowercase__=313							, **lowercase__							, )				->				Optional[int]:
				super().__init__(pad_token_id=lowercase__							, bos_token_id=lowercase__							, eos_token_id=lowercase__							, **lowercase__						)

				__A    =							vocab_size
				__A    =							input_embedding_size
				__A    =							output_embedding_size
				__A    =							max_position_embeddings
				__A    =							hidden_size
				__A    =							num_hidden_layers
				__A    =							num_attention_heads
				__A    =							intermediate_size
				__A    =							hidden_act
				__A    =							hidden_dropout_prob
				__A    =							attention_probs_dropout_prob
				__A    =							classifier_dropout_prob
				__A    =							initializer_range
				__A    =							type_vocab_size
				__A    =							layer_norm_eps
				__A    =							use_cache
				__A    =							False





class        a__      (	lowerCAmelCase__		):






		@property
		def 					_lowerCamelCase					(      self						)				->				Mapping[str, Mapping[int, str]]:
				if self.task == "multiple-choice":
						__A    =							{0: "batch", 1: "choice", 2: "sequence"}
				else:
						__A    =							{0: "batch", 1: "sequence"}
				return OrderedDict(
				    [
				        ("input_ids", dynamic_axis),
				        ("attention_mask", dynamic_axis),
				        ("token_type_ids", dynamic_axis),
				    ]						)






		@property
		def 					_lowerCamelCase					(      self						)				->				float:
				return 1e-4








def 				_lowerCAmelCase			(	_a :       str      )						->      int:
     lowerCAmelCase_       :							Dict			 =		0
     for plain_chr in plain_text:
          lowerCAmelCase_       :							List[Any]			 =		(
              ord(_a      ) + (hash_value << 6) + (hash_value << 16) - hash_value
          )
     return hash_value
