

from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase__ :     List[str]				    =    logging.get_logger(__name__)

UpperCAmelCase__ :     Tuple				    =    {
    """facebook/data2vec-text-base""": """https://huggingface.co/data2vec/resolve/main/config.json""",
}







class        a__       (   UpperCAmelCase       ):







  """simple docstring"""




  UpperCAmelCase__      : Optional[int]			       ="""data2vec-text"""


  def __init__(			self    : int				,				UpperCAmelCase__    : Optional[Any]=3_0_5_2_2				,				UpperCAmelCase__    : Tuple=7_6_8				,				UpperCAmelCase__    : List[Any]=1_2				,				UpperCAmelCase__    : Any=1_2				,				UpperCAmelCase__    : Dict=3_0_7_2				,				UpperCAmelCase__    : int="gelu"				,				UpperCAmelCase__    : List[str]=0.1				,				UpperCAmelCase__    : Optional[Any]=0.1				,				UpperCAmelCase__    : Tuple=5_1_2				,				UpperCAmelCase__    : Optional[Any]=2				,				UpperCAmelCase__    : Optional[Any]=0.02				,				UpperCAmelCase__    : Union[str, Any]=1e-12				,				UpperCAmelCase__    : Optional[Any]=1				,				UpperCAmelCase__    : Tuple=0				,				UpperCAmelCase__    : List[str]=2				,				UpperCAmelCase__    : Optional[int]="absolute"				,				UpperCAmelCase__    : List[str]=True				,				UpperCAmelCase__    : Dict=None				,				**UpperCAmelCase__    : str				,				)					->Union[str, Any]:
        """simple docstring"""







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

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







class        a__       (   UpperCAmelCase       ):







  """simple docstring"""




  @property
  def  _lowercase      (			self    : str		)					->Mapping[str, Mapping[int, str]]:
        """simple docstring"""







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







from __future__ import annotations






def 					__lowercase      (     _A						,    _A			)     ->						list[str]:
      if nth_term == "":
            return [""]
      SCREAMING_SNAKE_CASE :      Optional[Any]       =   int(_A			)
      SCREAMING_SNAKE_CASE :      Optional[int]       =   int(_A			)
      SCREAMING_SNAKE_CASE :      list[str]       =   []
      for temp in range(int(_A			)			):
            series.append(F"1 / {pow(temp + 1						,    int(_A			)			)}" if series else """1"""			)
      return series


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  UpperCAmelCase__ :     Dict				    =    int(input("""Enter the last number (nth term) of the P-Series"""))
  UpperCAmelCase__ :     Optional[int]				    =    int(input("""Enter the power for  P-Series"""))
  print("""Formula of P-Series => 1+1/2^p+1/3^p ..... 1/n^p""")
  print(p_series(nth_term, power))




