

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    				=     {
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}





class A__    ( A ):



 """simple docstring"""







 _lowercase     :					Tuple      =						'''roberta-prelayernorm'''

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






      '''simple docstring'''




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

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





class A__    ( A ):



 """simple docstring"""







 @property
 def    __magic_name__       (		self :	Dict       ):






      '''simple docstring'''




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









def 	_snake_case		(    SCREAMING_SNAKE_CASE				)       ->      "list[int]":

     """simple docstring"""







     if upper_limit < 0:
          raise ValueError("Limit for the Catalan sequence must be ≥ 0"				)

     _lowerCAmelCase   :					Optional[Any]        =    [0] * (upper_limit + 1)

     # Base case: C(0) = C(1) = 1
     _lowerCAmelCase   :					Optional[int]        =    1
     if upper_limit > 0:
          _lowerCAmelCase   :					Any        =    1

     # Recurrence relation: C(i) = sum(C(j).C(i-j-1)), from j = 0 to i
     for i in range(2		,							upper_limit + 1				):
          for j in range(SCREAMING_SNAKE_CASE				):
               catalan_list[i] += catalan_list[j] * catalan_list[i - j - 1]

     return catalan_list


if __name__ == "__main__":
  print('\n********* Catalan Numbers Using Dynamic Programming ************\n')
  print('\n*** Enter -1 at any time to quit ***')
  print('\nEnter the upper limit (≥ 0) for the Catalan number sequence: ', end='')
  try:
    while True:
      __UpperCAmelCase    				=     int(input().strip())
      if N < 0:
        print('\n********* Goodbye!! ************')
        break
      else:
        print(f'''The Catalan numbers from 0 through {N} are:''')
        print(catalan_numbers(N))
        print('Try another upper limit for the sequence: ', end='')
  except (NameError, ValueError):
    print('\n********* Invalid input, goodbye! ************\n')

  import doctest

  doctest.testmod()






