




"""simple docstring"""


from __future__ import annotations

import string
from itertools import cycle, product
from pathlib import Path

A_      			=       (
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
A_      			=       [ord(letter) for letter in string.ascii_lowercase]
A_      			=       {ord(char) for char in VALID_CHARS}

A_      			=       ["the", "be", "to", "of", "and", "in", "that", "have"]


def       UpperCAmelCase__ (snake_case__							:      list[int]	,     snake_case__							:      tuple[int, ...]					):
  """simple docstring"""

  _snake_case							:	str			=						""
  _snake_case							:	int
  _snake_case							:	int
  _snake_case							:	int

  for keychar, cipherchar in zip(cycle(snake_case__					)	,     snake_case__					):
    _snake_case							:	List[str]			=						cipherchar ^ keychar
    if decodedchar not in VALID_INTS:
      return None
    decoded += chr(snake_case__					)

  return decoded


def       UpperCAmelCase__ (snake_case__							:      list[int]					):
  """simple docstring"""

  _snake_case							:	list[str]			=						[]
  for key in product(snake_case__	,     repeat=3					):
    _snake_case							:	List[Any]			=						try_key(snake_case__	,     snake_case__					)
    if encoded is not None:
      possibles.append(snake_case__					)
  return possibles


def       UpperCAmelCase__ (snake_case__							:      list[str]	,     snake_case__							:      str					):
  """simple docstring"""

  return [possible for possible in possibles if common_word in possible.lower()]


def       UpperCAmelCase__ (snake_case__							:      str = "p059_cipher.txt"					):
  """simple docstring"""

  _snake_case							:	list[int]
  _snake_case							:	list[str]
  _snake_case							:	str
  _snake_case							:	str
  _snake_case							:	str			=						Path(snake_case__					).parent.joinpath(snake_case__					).read_text(encoding="""utf-8"""					)

  _snake_case							:	List[Any]			=						[int(snake_case__					) for number in data.strip().split(""","""					)]

  _snake_case							:	Optional[Any]			=						filter_valid_chars(snake_case__					)
  for common_word in COMMON_WORDS:
    _snake_case							:	Union[str, Any]			=						filter_common_word(snake_case__	,     snake_case__					)
    if len(snake_case__					) == 1:
      break

  _snake_case							:	Optional[int]			=						possibles[0]
  return sum(ord(snake_case__					) for char in decoded_text					)


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








"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

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


A_      			=       logging.get_logger(__name__)

A_      			=       {
    '''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       lowercase(  __a				):







 '''simple docstring'''





 lowercase__				      =      "roformer"


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




   '''simple docstring'''



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

   _snake_case							:	int			=						vocab_size
   _snake_case							:	int			=						hidden_size if embedding_size is None else embedding_size
   _snake_case							:	Dict			=						hidden_size
   _snake_case							:	Optional[int]			=						num_hidden_layers
   _snake_case							:	Any			=						num_attention_heads
   _snake_case							:	Dict			=						hidden_act
   _snake_case							:	Optional[int]			=						intermediate_size
   _snake_case							:	List[Any]			=						hidden_dropout_prob
   _snake_case							:	Union[str, Any]			=						attention_probs_dropout_prob
   _snake_case							:	Any			=						max_position_embeddings
   _snake_case							:	Tuple			=						type_vocab_size
   _snake_case							:	List[Any]			=						initializer_range
   _snake_case							:	List[Any]			=						layer_norm_eps
   _snake_case							:	Optional[Any]			=						rotary_value
   _snake_case							:	List[str]			=						use_cache







class       lowercase(  __a				):







 '''simple docstring'''





 @property
 def 				UpperCamelCase_     (       self:	Dict	):




   '''simple docstring'''



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


