





__lowerCamelCase :  Optional[int]										=  [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__lowerCamelCase :  Dict										=  [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__lowerCamelCase :  str										=  {
    0: """Sunday""",
    1: """Monday""",
    2: """Tuesday""",
    3: """Wednesday""",
    4: """Thursday""",
    5: """Friday""",
    6: """Saturday""",
}



def 	A_       (  _lowerCAmelCase							,     _lowerCAmelCase							,     _lowerCAmelCase  )		->				str:
 assert len(str(_lowerCAmelCase  )  ) > 2, "year should be in YYYY format"
 assert 1 <= month <= 12, "month should be between 1 to 12"
 assert 1 <= day <= 31, "day should be between 1 to 31"

 # Doomsday algorithm:
 UpperCamelCase			:      int 			=     year // 100
 UpperCamelCase			:      Optional[Any] 			=     (5 * (century % 4) + 2) % 7
 UpperCamelCase			:      str 			=     year % 100
 UpperCamelCase			:      List[str] 			=     centurian % 12
 UpperCamelCase			:      Union[str, Any] 			=     (
     (centurian // 12) + centurian_m + (centurian_m // 4) + century_anchor
 ) % 7
 UpperCamelCase			:      List[str] 			=     (
     DOOMSDAY_NOT_LEAP[month - 1]
     if (year % 4 != 0) or (centurian == 0 and (year % 400) == 0)
     else DOOMSDAY_LEAP[month - 1]
 )
 UpperCamelCase			:      Dict 			=     (dooms_day + day - day_anchor) % 7
 return WEEK_DAY_NAMES[week_day]


if __name__ == "__main__":
    import doctest

    doctest.testmod()









from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase :  Tuple										=  logging.get_logger(__name__)

__lowerCamelCase :  str										=  {
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}



class       A__     ( __snake_case    ):
      _UpperCAmelCase			:Union[str, Any]							=     'camembert'





      def __init__(				self ,							A_=3_0522 ,							A_=768 ,							A_=12 ,							A_=12 ,							A_=3072 ,							A_="gelu" ,							A_=0.1 ,							A_=0.1 ,							A_=512 ,							A_=2 ,							A_=0.02 ,							A_=1e-12 ,							A_=1 ,							A_=0 ,							A_=2 ,							A_="absolute" ,							A_=True ,							A_=None ,							**A_ ,							):
       '''simple docstring'''




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

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



class       A__     ( __snake_case    ):





      @property
      def  __UpperCamelCase(				self     ):
       '''simple docstring'''




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