



'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

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


lowercase_			=  logging.get_logger(__name__)

lowercase_			=  {
    "mnaylor/mega-base-wikitext": "https://huggingface.co/mnaylor/mega-base-wikitext/resolve/main/config.json",
}






class __A      (  snake_case__						):



 '''simple docstring'''







 __lowerCamelCase   :	Tuple										=	'mega'



 def __init__(self			,       A=30_522			,       A=128			,       A=4			,       A=256			,       A=16			,       A=True			,       A=64			,       A=False			,       A=-1			,       A=None			,       A=True			,       A="scalenorm"			,       A=True			,       A="silu"			,       A="softmax"			,       A=0.1			,       A=0.1			,       A=0.1			,       A=False			,       A=True			,       A=256			,       A=True			,       A=0.1			,       A=2_048			,       A=False			,       A=2			,       A=0.02			,       A=0.2			,       A=0.02			,       A=1.0			,       A=1			,       A=0			,       A=2			,       A="rotary"			,       A=None			,       A=True			,       A=True			,       **A			,       )   ->					Any:


      """simple docstring"""



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

      _a     =  vocab_size
      _a     =  hidden_size
      _a     =  num_hidden_layers
      _a     =  activation
      _a     =  attention_activation
      _a     =  intermediate_size
      _a     =  ema_projection_size
      _a     =  bidirectional
      _a     =  shared_representation_size
      _a     =  use_chunking
      _a     =  chunk_size
      _a     =  truncation
      _a     =  normalize_before_mega
      _a     =  normalization_type
      _a     =  norm_affine
      _a     =  dropout_prob
      _a     =  hidden_dropout_prob
      _a     =  attention_probs_dropout_prob
      _a     =  use_feature_dropout
      _a     =  use_normalized_ffn
      _a     =  nffn_hidden_size
      _a     =  normalize_before_ffn
      _a     =  nffn_activation_dropout_prob
      _a     =  max_positions
      _a     =  add_token_type_embeddings
      _a     =  type_vocab_size
      _a     =  initializer_range
      _a     =  ema_delta_alpha_range
      _a     =  ema_beta_range
      _a     =  ema_gamma_omega_range
      _a     =  relative_positional_bias
      _a     =  use_cache
      _a     =  classifier_dropout
      _a     =  add_lm_hidden_dense_layer
      _a     =  1  # not used but required by Hugging Face






class __A      (  snake_case__						):



 '''simple docstring'''







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


      """simple docstring"""



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








'''simple docstring'''





from math import gcd




def lowerCAmelCase  (__A = 12_000):



     """simple docstring"""



     _a     =  0
     for d in range(max_d + 1):
          for n in range(d // 3 + 1  ,     (d + 1) // 2):
               if gcd(__A  ,     __A) == 1:
                    fractions_number += 1
     return fractions_number


if __name__ == "__main__":
  print(F"""{solution() = }""")



