




"""simple docstring"""


import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors






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







 '''simple docstring'''





 lowercase__				      =      MvpTokenizer
 lowercase__				      =      MvpTokenizerFast
 lowercase__				      =      True
 lowercase__				      =      filter_roberta_detectors


 def 				UpperCamelCase_     (       self:	List[str]	):




   '''simple docstring'''



   super().setUp()
   _snake_case							:	str			=						[
       """l""",
       """o""",
       """w""",
       """e""",
       """r""",
       """s""",
       """t""",
       """i""",
       """d""",
       """n""",
       """\u0120""",
       """\u0120l""",
       """\u0120n""",
       """\u0120lo""",
       """\u0120low""",
       """er""",
       """\u0120lowest""",
       """\u0120newer""",
       """\u0120wider""",
       """<unk>""",
   ]
   _snake_case							:	Optional[int]			=						dict(zip(a_,   range(len(a_	)	)	)	)
   _snake_case							:	Tuple			=						["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
   _snake_case							:	Optional[int]			=						{"""unk_token""": """<unk>"""}

   _snake_case							:	Tuple			=						os.path.join(self.tmpdirname,   VOCAB_FILES_NAMES["""vocab_file"""]	)
   _snake_case							:	Dict			=						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_:	Dict	):




   '''simple docstring'''



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


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




   '''simple docstring'''



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


 def 				UpperCamelCase_     (       self:	List[Any],   a_:	int	):




   '''simple docstring'''



   return "lower newer", "lower newer"


 @cached_property
 def 				UpperCamelCase_     (       self:	List[str]	):




   '''simple docstring'''



   return MvpTokenizer.from_pretrained("""RUCAIBox/mvp"""	)


 @cached_property
 def 				UpperCamelCase_     (       self:	List[Any]	):




   '''simple docstring'''



   return MvpTokenizerFast.from_pretrained("""RUCAIBox/mvp"""	)


 @require_torch
 def 				UpperCamelCase_     (       self:	Union[str, Any]	):




   '''simple docstring'''



   _snake_case							:	Any			=						["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
   _snake_case							:	List[str]			=						[0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

   for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
     _snake_case							:	List[Any]			=						tokenizer(a_,   max_length=len(a_	),   padding=a_,   return_tensors="""pt"""	)
     self.assertIsInstance(a_,   a_	)

     self.assertEqual((2, 9),   batch.input_ids.shape	)
     self.assertEqual((2, 9),   batch.attention_mask.shape	)
     _snake_case							:	Union[str, Any]			=						batch.input_ids.tolist()[0]
     self.assertListEqual(a_,   a_	)
     # Test that special tokens are reset


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




   '''simple docstring'''



   _snake_case							:	str			=						["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
   for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
     _snake_case							:	Dict			=						tokenizer(a_,   padding=a_,   return_tensors="""pt"""	)
     # check if input_ids are returned and no labels
     self.assertIn("""input_ids""",   a_	)
     self.assertIn("""attention_mask""",   a_	)
     self.assertNotIn("""labels""",   a_	)
     self.assertNotIn("""decoder_attention_mask""",   a_	)


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




   '''simple docstring'''



   _snake_case							:	str			=						[
       """Summary of the text.""",
       """Another summary.""",
   ]
   for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
     _snake_case							:	int			=						tokenizer(text_target=a_,   max_length=32,   padding="""max_length""",   return_tensors="""pt"""	)
     self.assertEqual(32,   targets["""input_ids"""].shape[1]	)


 @require_torch
 def 				UpperCamelCase_     (       self:	Optional[Any]	):




   '''simple docstring'''



   for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
     _snake_case							:	Optional[Any]			=						tokenizer(
         ["""I am a small frog""" * 1_024, """I am a small frog"""],   padding=a_,   truncation=a_,   return_tensors="""pt"""	)
     self.assertIsInstance(a_,   a_	)
     self.assertEqual(batch.input_ids.shape,   (2, 1_024)	)


 @require_torch
 def 				UpperCamelCase_     (       self:	List[str]	):




   '''simple docstring'''



   _snake_case							:	Union[str, Any]			=						["""A long paragraph for summarization."""]
   _snake_case							:	Tuple			=						[
       """Summary of the text.""",
   ]
   for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
     _snake_case							:	Dict			=						tokenizer(a_,   text_target=a_,   return_tensors="""pt"""	)
     _snake_case							:	List[str]			=						inputs["""input_ids"""]
     _snake_case							:	List[str]			=						inputs["""labels"""]
     self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()	)
     self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()	)
     self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()	)
     self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()	)


 def 				UpperCamelCase_     (       self:	Optional[int]	):




   '''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							:	Any			=						self.rust_tokenizer_class.from_pretrained(a_,   **a_	)
       _snake_case							:	Any			=						self.tokenizer_class.from_pretrained(a_,   **a_	)
       _snake_case							:	int			=						"""A, <mask> AllenNLP sentence."""
       _snake_case							:	List[Any]			=						tokenizer_r.encode_plus(a_,   add_special_tokens=a_,   return_token_type_ids=a_	)
       _snake_case							:	List[str]			=						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							:	List[Any]			=						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>"""]	)








"""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() = }''')


