'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

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


_lowercase		:					int													=		logging.get_logger(__name__)

_lowercase		:					Optional[Any]													=		{
    "google/rembert": "https://huggingface.co/google/rembert/resolve/main/config.json",
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}





class        __magic_name__		(       _UpperCAmelCase):
			UpperCamelCase__							=			'''rembert'''







			def __init__(      self							:    int							,     lowercase_							:    Union[str, Any]=250300							,     lowercase_							:    Optional[int]=1152							,     lowercase_							:    Union[str, Any]=32							,     lowercase_							:    Tuple=18							,     lowercase_							:    List[Any]=256							,     lowercase_							:    List[str]=1664							,     lowercase_							:    Optional[Any]=4608							,     lowercase_							:    Tuple="gelu"							,     lowercase_							:    Optional[Any]=0.0							,     lowercase_							:    int=0.0							,     lowercase_							:    str=0.1							,     lowercase_							:    Dict=512							,     lowercase_							:    List[Any]=2							,     lowercase_							:    Dict=0.02							,     lowercase_							:    Optional[Any]=1E-12							,     lowercase_							:    Union[str, Any]=True							,     lowercase_							:    Tuple=0							,     lowercase_							:    str=312							,     lowercase_							:    List[str]=313							,     **lowercase_							:    Optional[Any]							,     ):
										super().__init__(pad_token_id=lowercase_							,     bos_token_id=lowercase_							,     eos_token_id=lowercase_							,     **lowercase_       )

										lowercase_   :     str									=			vocab_size
										lowercase_   :     Union[str, Any]									=			input_embedding_size
										lowercase_   :     Union[str, Any]									=			output_embedding_size
										lowercase_   :     Optional[Any]									=			max_position_embeddings
										lowercase_   :     int									=			hidden_size
										lowercase_   :     Optional[int]									=			num_hidden_layers
										lowercase_   :     Dict									=			num_attention_heads
										lowercase_   :     int									=			intermediate_size
										lowercase_   :     Any									=			hidden_act
										lowercase_   :     List[Any]									=			hidden_dropout_prob
										lowercase_   :     int									=			attention_probs_dropout_prob
										lowercase_   :     List[Any]									=			classifier_dropout_prob
										lowercase_   :     Optional[int]									=			initializer_range
										lowercase_   :     Dict									=			type_vocab_size
										lowercase_   :     Union[str, Any]									=			layer_norm_eps
										lowercase_   :     Any									=			use_cache
										lowercase_   :     List[Any]									=			False





class        __magic_name__		(       _UpperCAmelCase):







			@property
			def       SCREAMING_SNAKE_CASE_	(      self							:    str       ):
										if self.task == "multiple-choice":
																	lowercase_   :     Union[str, Any]									=			{0: """batch""", 1: """choice""", 2: """sequence"""}
										else:
																	lowercase_   :     Any									=			{0: """batch""", 1: """sequence"""}
										return OrderedDict(
										    [
										        ("""input_ids""", dynamic_axis),
										        ("""attention_mask""", dynamic_axis),
										        ("""token_type_ids""", dynamic_axis),
										    ]       )







			@property
			def       SCREAMING_SNAKE_CASE_	(      self							:    Dict       ):
										return 1E-4









from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase__        =				logging.get_logger(__name__)

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







class  lowerCamelCase__  (			lowerCAmelCase):
     SCREAMING_SNAKE_CASE__      =     '''rembert'''





     def __init__(self						,	UpperCAmelCase=2_5_0_3_0_0						,	UpperCAmelCase=1_1_5_2						,	UpperCAmelCase=3_2						,	UpperCAmelCase=1_8						,	UpperCAmelCase=2_5_6						,	UpperCAmelCase=1_6_6_4						,	UpperCAmelCase=4_6_0_8						,	UpperCAmelCase="gelu"						,	UpperCAmelCase=0.0						,	UpperCAmelCase=0.0						,	UpperCAmelCase=0.1						,	UpperCAmelCase=5_1_2						,	UpperCAmelCase=2						,	UpperCAmelCase=0.02						,	UpperCAmelCase=1e-12						,	UpperCAmelCase=True						,	UpperCAmelCase=0						,	UpperCAmelCase=3_1_2						,	UpperCAmelCase=3_1_3						,	**UpperCAmelCase						,	)	->  Tuple:
      super().__init__(pad_token_id=UpperCAmelCase						,	bos_token_id=UpperCAmelCase						,	eos_token_id=UpperCAmelCase						,	**UpperCAmelCase			)

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







class  lowerCamelCase__  (			lowerCAmelCase):





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





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

