

'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase :       Tuple			   =     logging.get_logger(__name__)

UpperCAmelCase :       Tuple			   =     {
    'junnyu/roformer_chinese_small': 'https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json',
    'junnyu/roformer_chinese_base': 'https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json',
    'junnyu/roformer_chinese_char_small': (
        'https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json'
    ),
    'junnyu/roformer_chinese_char_base': (
        'https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json'
    ),
    'junnyu/roformer_small_discriminator': (
        'https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json'
    ),
    'junnyu/roformer_small_generator': (
        'https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json'
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}







class 						lowerCAmelCase__   (      a					):



 """simple docstring"""



 lowerCAmelCase__  					=      "roformer"
 def __init__(		self					:       int					,							__SCREAMING_SNAKE_CASE					:       Dict=50_000					,							__SCREAMING_SNAKE_CASE					:       str=None					,							__SCREAMING_SNAKE_CASE					:       Optional[Any]=768					,							__SCREAMING_SNAKE_CASE					:       Tuple=12					,							__SCREAMING_SNAKE_CASE					:       Tuple=12					,							__SCREAMING_SNAKE_CASE					:       int=3_072					,							__SCREAMING_SNAKE_CASE					:       Dict="gelu"					,							__SCREAMING_SNAKE_CASE					:       Dict=0.1					,							__SCREAMING_SNAKE_CASE					:       List[Any]=0.1					,							__SCREAMING_SNAKE_CASE					:       List[Any]=1_536					,							__SCREAMING_SNAKE_CASE					:       Tuple=2					,							__SCREAMING_SNAKE_CASE					:       Optional[int]=0.02					,							__SCREAMING_SNAKE_CASE					:       List[str]=1E-12					,							__SCREAMING_SNAKE_CASE					:       List[str]=0					,							__SCREAMING_SNAKE_CASE					:       Optional[Any]=False					,							__SCREAMING_SNAKE_CASE					:       str=True					,							**__SCREAMING_SNAKE_CASE					:       List[str]					,							)  -> Optional[Any]:


      """simple docstring"""




      super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE					,							**__SCREAMING_SNAKE_CASE			)

      __SCREAMING_SNAKE_CASE     =      vocab_size
      __SCREAMING_SNAKE_CASE     =      hidden_size if embedding_size is None else embedding_size
      __SCREAMING_SNAKE_CASE     =      hidden_size
      __SCREAMING_SNAKE_CASE     =      num_hidden_layers
      __SCREAMING_SNAKE_CASE     =      num_attention_heads
      __SCREAMING_SNAKE_CASE     =      hidden_act
      __SCREAMING_SNAKE_CASE     =      intermediate_size
      __SCREAMING_SNAKE_CASE     =      hidden_dropout_prob
      __SCREAMING_SNAKE_CASE     =      attention_probs_dropout_prob
      __SCREAMING_SNAKE_CASE     =      max_position_embeddings
      __SCREAMING_SNAKE_CASE     =      type_vocab_size
      __SCREAMING_SNAKE_CASE     =      initializer_range
      __SCREAMING_SNAKE_CASE     =      layer_norm_eps
      __SCREAMING_SNAKE_CASE     =      rotary_value
      __SCREAMING_SNAKE_CASE     =      use_cache







class 						lowerCAmelCase__   (      a					):



 """simple docstring"""



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


      """simple docstring"""




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









'''simple docstring'''



from itertools import count







def    a__       (  a__ = 50						):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE     =      [1] * min_block_length

     for n in count(a__						):
          fill_count_functions.append(1						)

          for block_length in range(a__      ,    n + 1						):
               for block_start in range(n - block_length						):
                    fill_count_functions[n] += fill_count_functions[
                        n - block_start - block_length - 1
                    ]

               fill_count_functions[n] += 1

          if fill_count_functions[n] > 1_00_00_00:
               break

     return n


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






