






"""simple docstring"""


import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class       lowercase(  __a ,    unittest.TestCase				):







 '''simple docstring'''





 lowercase__				      =      LongformerTokenizer
 lowercase__				      =      True
 lowercase__				      =      LongformerTokenizerFast
 lowercase__				      =      True


 def 				UpperCamelCase_     (       self:	Any	):




   '''simple docstring'''



   super().setUp()

   # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
   _snake_case							:	List[Any]			=						[
       """l""",
       """o""",
       """w""",
       """e""",
       """r""",
       """s""",
       """t""",
       """i""",
       """d""",
       """n""",
       """\u0120""",
       """\u0120l""",
       """\u0120n""",
       """\u0120lo""",
       """\u0120low""",
       """er""",
       """\u0120lowest""",
       """\u0120newer""",
       """\u0120wider""",
       """<unk>""",
   ]
   _snake_case							:	List[str]			=						dict(zip(a_,   range(len(a_	)	)	)	)
   _snake_case							:	List[Any]			=						["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
   _snake_case							:	Any			=						{"""unk_token""": """<unk>"""}

   _snake_case							:	int			=						os.path.join(self.tmpdirname,   VOCAB_FILES_NAMES["""vocab_file"""]	)
   _snake_case							:	Tuple			=						os.path.join(self.tmpdirname,   VOCAB_FILES_NAMES["""merges_file"""]	)
   with open(self.vocab_file,   """w""",   encoding="""utf-8"""	) as fp:
     fp.write(json.dumps(a_	) + """\n"""	)
   with open(self.merges_file,   """w""",   encoding="""utf-8"""	) as fp:
     fp.write("""\n""".join(a_	)	)


 def 				UpperCamelCase_     (       self:	Union[str, Any],   **a_:	List[Any]	):




   '''simple docstring'''



   kwargs.update(self.special_tokens_map	)
   return self.tokenizer_class.from_pretrained(self.tmpdirname,   **a_	)


 def 				UpperCamelCase_     (       self:	str,   **a_:	str	):




   '''simple docstring'''



   kwargs.update(self.special_tokens_map	)
   return self.rust_tokenizer_class.from_pretrained(self.tmpdirname,   **a_	)


 def 				UpperCamelCase_     (       self:	Tuple,   a_:	Tuple	):




   '''simple docstring'''



   _snake_case							:	int			=						"""lower newer"""
   _snake_case							:	Optional[int]			=						"""lower newer"""
   return input_text, output_text


 def 				UpperCamelCase_     (       self:	Optional[int]	):




   '''simple docstring'''



   _snake_case							:	Any			=						self.tokenizer_class(self.vocab_file,   self.merges_file,   **self.special_tokens_map	)
   _snake_case							:	int			=						"""lower newer"""
   _snake_case							:	Union[str, Any]			=						["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
   _snake_case							:	int			=						tokenizer.tokenize(a_	)  # , add_prefix_space=True)
   self.assertListEqual(a_,   a_	)

   _snake_case							:	Any			=						tokens + [tokenizer.unk_token]
   _snake_case							:	str			=						[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(a_	),   a_	)


 def 				UpperCamelCase_     (       self:	List[Any]	):




   '''simple docstring'''



   _snake_case							:	int			=						self.get_tokenizer()

   self.assertListEqual(tokenizer.encode("""Hello world!""",   add_special_tokens=a_	),   [0, 31_414, 232, 328, 2]	)
   self.assertListEqual(
       tokenizer.encode("""Hello world! cécé herlolip 418""",   add_special_tokens=a_	),   [0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2],   )


 @slow
 def 				UpperCamelCase_     (       self:	Optional[int]	):




   '''simple docstring'''



   _snake_case							:	Optional[int]			=						self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""	)

   _snake_case							:	Union[str, Any]			=						tokenizer.encode("""sequence builders""",   add_special_tokens=a_	)
   _snake_case							:	Tuple			=						tokenizer.encode("""multi-sequence build""",   add_special_tokens=a_	)

   _snake_case							:	Tuple			=						tokenizer.encode(
       """sequence builders""",   add_special_tokens=a_,   add_prefix_space=a_	)
   _snake_case							:	Optional[Any]			=						tokenizer.encode(
       """sequence builders""",   """multi-sequence build""",   add_special_tokens=a_,   add_prefix_space=a_	)

   _snake_case							:	List[str]			=						tokenizer.build_inputs_with_special_tokens(a_	)
   _snake_case							:	Union[str, Any]			=						tokenizer.build_inputs_with_special_tokens(a_,   a_	)

   assert encoded_sentence == encoded_text_from_decode
   assert encoded_pair == encoded_pair_from_decode


 def 				UpperCamelCase_     (       self:	str	):




   '''simple docstring'''



   _snake_case							:	Optional[Any]			=						self.get_tokenizer()

   _snake_case							:	Dict			=						"""Encode this sequence."""
   _snake_case							:	Optional[Any]			=						tokenizer.byte_encoder[""" """.encode("""utf-8"""	)[0]]

   # Testing encoder arguments
   _snake_case							:	Union[str, Any]			=						tokenizer.encode(a_,   add_special_tokens=a_,   add_prefix_space=a_	)
   _snake_case							:	Optional[int]			=						tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
   self.assertNotEqual(a_,   a_	)

   _snake_case							:	Optional[int]			=						tokenizer.encode(a_,   add_special_tokens=a_,   add_prefix_space=a_	)
   _snake_case							:	Optional[int]			=						tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
   self.assertEqual(a_,   a_	)

   tokenizer.add_special_tokens({"""bos_token""": """<s>"""}	)
   _snake_case							:	Union[str, Any]			=						tokenizer.encode(a_,   add_special_tokens=a_	)
   _snake_case							:	str			=						tokenizer.convert_ids_to_tokens(encoded[1]	)[0]
   self.assertNotEqual(a_,   a_	)

   # Testing spaces after special tokens
   _snake_case							:	List[str]			=						"""<mask>"""
   tokenizer.add_special_tokens(
       {"""mask_token""": AddedToken(a_,   lstrip=a_,   rstrip=a_	)}	)  # mask token has a left space
   _snake_case							:	str			=						tokenizer.convert_tokens_to_ids(a_	)

   _snake_case							:	int			=						"""Encode <mask> sequence"""
   _snake_case							:	Tuple			=						"""Encode <mask>sequence"""

   _snake_case							:	List[str]			=						tokenizer.encode(a_	)
   _snake_case							:	Optional[int]			=						encoded.index(a_	)
   _snake_case							:	Tuple			=						tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
   self.assertEqual(a_,   a_	)

   _snake_case							:	Union[str, Any]			=						tokenizer.encode(a_	)
   _snake_case							:	Optional[int]			=						encoded.index(a_	)
   _snake_case							:	Any			=						tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
   self.assertNotEqual(a_,   a_	)


 def 				UpperCamelCase_     (       self:	Tuple	):




   '''simple docstring'''



   pass


 def 				UpperCamelCase_     (       self:	List[str]	):




   '''simple docstring'''



   for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
     with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"	):
       _snake_case							:	str			=						self.rust_tokenizer_class.from_pretrained(a_,   **a_	)
       _snake_case							:	Dict			=						self.tokenizer_class.from_pretrained(a_,   **a_	)
       _snake_case							:	List[str]			=						"""A, <mask> AllenNLP sentence."""
       _snake_case							:	Tuple			=						tokenizer_r.encode_plus(a_,   add_special_tokens=a_,   return_token_type_ids=a_	)
       _snake_case							:	Optional[int]			=						tokenizer_p.encode_plus(a_,   add_special_tokens=a_,   return_token_type_ids=a_	)

       # token_type_ids should put 0 everywhere
       self.assertEqual(sum(tokens_r["""token_type_ids"""]	),   sum(tokens_p["""token_type_ids"""]	)	)

       # attention_mask should put 1 everywhere, so sum over length should be 1
       self.assertEqual(
           sum(tokens_r["""attention_mask"""]	) / len(tokens_r["""attention_mask"""]	),   sum(tokens_p["""attention_mask"""]	) / len(tokens_p["""attention_mask"""]	),   )

       _snake_case							:	int			=						tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]	)
       _snake_case							:	int			=						tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]	)

       # Rust correctly handles the space before the mask while python doesnt
       self.assertSequenceEqual(tokens_p["""input_ids"""],   [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]	)
       self.assertSequenceEqual(tokens_r["""input_ids"""],   [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]	)

       self.assertSequenceEqual(
           a_,   ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]	)
       self.assertSequenceEqual(
           a_,   ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]	)


 def 				UpperCamelCase_     (       self:	List[str]	):




   '''simple docstring'''



   for trim_offsets, add_prefix_space in itertools.product([True, False],   repeat=2	):
     _snake_case							:	Any			=						self.rust_tokenizer_class.from_pretrained(
         self.tmpdirname,   use_fast=a_,   add_prefix_space=a_,   trim_offsets=a_	)

     _snake_case							:	Optional[Any]			=						json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()	)
     _snake_case							:	Any			=						json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()	)

     self.assertEqual(pre_tokenizer_state["""add_prefix_space"""],   a_	)

     self.assertEqual(post_processor_state["""add_prefix_space"""],   a_	)
     self.assertEqual(post_processor_state["""trim_offsets"""],   a_	)


 def 				UpperCamelCase_     (       self:	List[str]	):




   '''simple docstring'''



   for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
     with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"	):
       _snake_case							:	Optional[int]			=						"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
       _snake_case							:	int			=						f"{text_of_1_token} {text_of_1_token}"

       _snake_case							:	Optional[int]			=						self.rust_tokenizer_class.from_pretrained(
           a_,   use_fast=a_,   add_prefix_space=a_,   trim_offsets=a_	)
       _snake_case							:	Dict			=						tokenizer_r(a_,   return_offsets_mapping=a_,   add_special_tokens=a_	)
       self.assertEqual(encoding.offset_mapping[0],   (0, len(a_	))	)
       self.assertEqual(
           encoding.offset_mapping[1],   (len(a_	) + 1, len(a_	) + 1 + len(a_	)),   )

       _snake_case							:	Union[str, Any]			=						self.rust_tokenizer_class.from_pretrained(
           a_,   use_fast=a_,   add_prefix_space=a_,   trim_offsets=a_	)
       _snake_case							:	str			=						tokenizer_r(a_,   return_offsets_mapping=a_,   add_special_tokens=a_	)
       self.assertEqual(encoding.offset_mapping[0],   (0, len(a_	))	)
       self.assertEqual(
           encoding.offset_mapping[1],   (len(a_	) + 1, len(a_	) + 1 + len(a_	)),   )

       _snake_case							:	Union[str, Any]			=						self.rust_tokenizer_class.from_pretrained(
           a_,   use_fast=a_,   add_prefix_space=a_,   trim_offsets=a_	)
       _snake_case							:	Dict			=						tokenizer_r(a_,   return_offsets_mapping=a_,   add_special_tokens=a_	)
       self.assertEqual(encoding.offset_mapping[0],   (0, len(a_	))	)
       self.assertEqual(
           encoding.offset_mapping[1],   (len(a_	), len(a_	) + 1 + len(a_	)),   )

       _snake_case							:	Tuple			=						self.rust_tokenizer_class.from_pretrained(
           a_,   use_fast=a_,   add_prefix_space=a_,   trim_offsets=a_	)
       _snake_case							:	Union[str, Any]			=						tokenizer_r(a_,   return_offsets_mapping=a_,   add_special_tokens=a_	)
       self.assertEqual(encoding.offset_mapping[0],   (0, len(a_	))	)
       self.assertEqual(
           encoding.offset_mapping[1],   (len(a_	), len(a_	) + 1 + len(a_	)),   )

       _snake_case							:	Tuple			=						f" {text}"

       # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
       #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
       # )
       # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
       # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
       # self.assertEqual(
       #     encoding.offset_mapping[1],
       #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
       # )

       _snake_case							:	Optional[Any]			=						self.rust_tokenizer_class.from_pretrained(
           a_,   use_fast=a_,   add_prefix_space=a_,   trim_offsets=a_	)
       _snake_case							:	Union[str, Any]			=						tokenizer_r(a_,   return_offsets_mapping=a_,   add_special_tokens=a_	)
       self.assertEqual(encoding.offset_mapping[0],   (1, 1 + len(a_	))	)
       self.assertEqual(
           encoding.offset_mapping[1],   (1 + len(a_	) + 1, 1 + len(a_	) + 1 + len(a_	)),   )

       _snake_case							:	Tuple			=						self.rust_tokenizer_class.from_pretrained(
           a_,   use_fast=a_,   add_prefix_space=a_,   trim_offsets=a_	)
       _snake_case							:	Any			=						tokenizer_r(a_,   return_offsets_mapping=a_,   add_special_tokens=a_	)
       self.assertEqual(encoding.offset_mapping[0],   (0, 1 + len(a_	))	)
       self.assertEqual(
           encoding.offset_mapping[1],   (1 + len(a_	), 1 + len(a_	) + 1 + len(a_	)),   )

       _snake_case							:	List[str]			=						self.rust_tokenizer_class.from_pretrained(
           a_,   use_fast=a_,   add_prefix_space=a_,   trim_offsets=a_	)
       _snake_case							:	Optional[Any]			=						tokenizer_r(a_,   return_offsets_mapping=a_,   add_special_tokens=a_	)
       self.assertEqual(encoding.offset_mapping[0],   (0, 1 + len(a_	))	)
       self.assertEqual(
           encoding.offset_mapping[1],   (1 + len(a_	), 1 + len(a_	) + 1 + len(a_	)),   )








"""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() = }''')


