


'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

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


A__:    Tuple					    =       logging.get_logger(__name__)

A__:    int					    =       {
    '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/config.json''',
    '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/config.json''',
    '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/config.json''',
    '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/config.json''',
    '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json''',
    '''roberta-large-openai-detector''': '''https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json''',
}







class A__       (						UpperCAmelCase__      ):
      __UpperCamelCase       :  Tuple	       =							"roberta"






      def __init__( self			:List[Any]     ,						SCREAMING_SNAKE_CASE			:List[str]=5_0_2_6_5     ,						SCREAMING_SNAKE_CASE			:Optional[int]=7_6_8     ,						SCREAMING_SNAKE_CASE			:List[str]=1_2     ,						SCREAMING_SNAKE_CASE			:Dict=1_2     ,						SCREAMING_SNAKE_CASE			:List[Any]=3_0_7_2     ,						SCREAMING_SNAKE_CASE			:List[str]="gelu"     ,						SCREAMING_SNAKE_CASE			:Tuple=0.1     ,						SCREAMING_SNAKE_CASE			:List[Any]=0.1     ,						SCREAMING_SNAKE_CASE			:str=5_1_2     ,						SCREAMING_SNAKE_CASE			:List[Any]=2     ,						SCREAMING_SNAKE_CASE			:List[Any]=0.02     ,						SCREAMING_SNAKE_CASE			:Optional[int]=1e-12     ,						SCREAMING_SNAKE_CASE			:Optional[Any]=1     ,						SCREAMING_SNAKE_CASE			:str=0     ,						SCREAMING_SNAKE_CASE			:Dict=2     ,						SCREAMING_SNAKE_CASE			:Dict="absolute"     ,						SCREAMING_SNAKE_CASE			:Tuple=True     ,						SCREAMING_SNAKE_CASE			:Any=None     ,						**SCREAMING_SNAKE_CASE			:List[str]     ,						)       ->					Union[str, Any]:




             '''simple docstring'''
             super().__init__(pad_token_id=SCREAMING_SNAKE_CASE     ,						bos_token_id=SCREAMING_SNAKE_CASE     ,						eos_token_id=SCREAMING_SNAKE_CASE     ,						**SCREAMING_SNAKE_CASE	)

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







class A__       (						UpperCAmelCase__      ):






      @property
      def __UpperCAmelCase       ( self			:Tuple	)       ->					Mapping[str, Mapping[int, str]]:




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






'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


A__:    str					    =       {}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A__:    Tuple					    =       ['''GPTSw3Tokenizer''']


if TYPE_CHECKING:
   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_gpt_swa import GPTSwaTokenizer

else:
   import sys

   A__:    str					    =       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


