




"""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_	(					lowerCamelCase_      ,     unittest.TestCase							):



 '''simple docstring'''
 UpperCAmelCase   :					int				  =     MvpTokenizer
 UpperCAmelCase   :					List[Any]				  =     MvpTokenizerFast
 UpperCAmelCase   :					Optional[int]				  =     True
 UpperCAmelCase   :					Tuple				  =     filter_roberta_detectors

 def       lowerCAmelCase_							(			self	:	Optional[Any]		):
       super().setUp()
       _A        =       [
           'l',
           'o',
           'w',
           'e',
           'r',
           's',
           't',
           'i',
           'd',
           'n',
           '\u0120',
           '\u0120l',
           '\u0120n',
           '\u0120lo',
           '\u0120low',
           'er',
           '\u0120lowest',
           '\u0120newer',
           '\u0120wider',
           '<unk>',
       ]
       _A        =       dict(zip(__snake_case   ,							range(len(__snake_case		)		)		)		)
       _A        =       ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
       _A        =       {'unk_token': '<unk>'}

       _A        =       os.path.join(self.tmpdirname   ,							VOCAB_FILES_NAMES['vocab_file']		)
       _A        =       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(__snake_case		) + '\n'		)
       with open(self.merges_file   ,							'w'   ,							encoding='utf-8'		) as fp:
             fp.write('\n'.join(__snake_case		)		)

 def       lowerCAmelCase_							(			self	:	Optional[Any]   ,							**_UpperCAmelCase	:	Tuple		):
       kwargs.update(self.special_tokens_map		)
       return self.tokenizer_class.from_pretrained(self.tmpdirname   ,							**__snake_case		)

 def       lowerCAmelCase_							(			self	:	Optional[Any]   ,							**_UpperCAmelCase	:	Dict		):
       kwargs.update(self.special_tokens_map		)
       return self.rust_tokenizer_class.from_pretrained(self.tmpdirname   ,							**__snake_case		)

 def       lowerCAmelCase_							(			self	:	Any   ,							_UpperCAmelCase	:	Union[str, Any]		):
       return "lower newer", "lower newer"

 @cached_property
 def       lowerCAmelCase_							(			self	:	Tuple		):
       return MvpTokenizer.from_pretrained('RUCAIBox/mvp'		)

 @cached_property
 def       lowerCAmelCase_							(			self	:	Optional[int]		):
       return MvpTokenizerFast.from_pretrained('RUCAIBox/mvp'		)

 @require_torch
 def       lowerCAmelCase_							(			self	:	Optional[int]		):
       _A        =       ['A long paragraph for summarization.', 'Another paragraph for summarization.']
       _A        =       [0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             _A        =       tokenizer(__snake_case   ,							max_length=len(__snake_case		)   ,							padding=__snake_case   ,							return_tensors='pt'		)
             self.assertIsInstance(__snake_case   ,							__snake_case		)

             self.assertEqual((2, 9)   ,							batch.input_ids.shape		)
             self.assertEqual((2, 9)   ,							batch.attention_mask.shape		)
             _A        =       batch.input_ids.tolist()[0]
             self.assertListEqual(__snake_case   ,							__snake_case		)
             # Test that special tokens are reset

 @require_torch
 def       lowerCAmelCase_							(			self	:	Union[str, Any]		):
       _A        =       ['A long paragraph for summarization.', 'Another paragraph for summarization.']
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             _A        =       tokenizer(__snake_case   ,							padding=__snake_case   ,							return_tensors='pt'		)
             # check if input_ids are returned and no labels
             self.assertIn('input_ids'   ,							__snake_case		)
             self.assertIn('attention_mask'   ,							__snake_case		)
             self.assertNotIn('labels'   ,							__snake_case		)
             self.assertNotIn('decoder_attention_mask'   ,							__snake_case		)

 @require_torch
 def       lowerCAmelCase_							(			self	:	Any		):
       _A        =       [
           'Summary of the text.',
           'Another summary.',
       ]
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             _A        =       tokenizer(text_target=__snake_case   ,							max_length=32   ,							padding='max_length'   ,							return_tensors='pt'		)
             self.assertEqual(32   ,							targets['input_ids'].shape[1]		)

 @require_torch
 def       lowerCAmelCase_							(			self	:	int		):
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             _A        =       tokenizer(
                 ['I am a small frog' * 1_024, 'I am a small frog']   ,							padding=__snake_case   ,							truncation=__snake_case   ,							return_tensors='pt'		)
             self.assertIsInstance(__snake_case   ,							__snake_case		)
             self.assertEqual(batch.input_ids.shape   ,							(2, 1_024)		)

 @require_torch
 def       lowerCAmelCase_							(			self	:	List[Any]		):
       _A        =       ['A long paragraph for summarization.']
       _A        =       [
           'Summary of the text.',
       ]
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             _A        =       tokenizer(__snake_case   ,							text_target=__snake_case   ,							return_tensors='pt'		)
             _A        =       inputs['input_ids']
             _A        =       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       lowerCAmelCase_							(			self	:	Union[str, Any]		):
       pass



 def       lowerCAmelCase_							(			self	:	Tuple		):
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
                   _A        =       self.rust_tokenizer_class.from_pretrained(__snake_case   ,							**__snake_case		)
                   _A        =       self.tokenizer_class.from_pretrained(__snake_case   ,							**__snake_case		)
                   _A        =       'A, <mask> AllenNLP sentence.'
                   _A        =       tokenizer_r.encode_plus(__snake_case   ,							add_special_tokens=__snake_case   ,							return_token_type_ids=__snake_case		)
                   _A        =       tokenizer_p.encode_plus(__snake_case   ,							add_special_tokens=__snake_case   ,							return_token_type_ids=__snake_case		)

                   # 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']		)   ,							)

                   _A        =       tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']		)
                   _A        =       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(
                       __snake_case   ,							['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']		)
                   self.assertSequenceEqual(
                       __snake_case   ,							['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']		)







"""simple docstring"""

import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation






def 						_snake_case					( _snake_case							: int = 8							)   -> str:






      '''simple docstring'''


      _A        =       ascii_letters + digits + punctuation
      return "".join(secrets.choice(_snake_case							) for _ in range(_snake_case							)							)






def 						_snake_case					( _snake_case							: str    ,  _snake_case							: int							)   -> str:






      '''simple docstring'''


      i -= len(_snake_case							)
      _A        =       i // 3
      _A        =       i % 3
      # chars = chars_incl + random_letters(ascii_letters, i / 3 + remainder) +
      #     random_number(digits, i / 3) + random_characters(punctuation, i / 3)
      _A        =       (
          chars_incl
          + random(_snake_case    ,  quotient + remainder							)
          + random(_snake_case    ,  _snake_case							)
          + random(_snake_case    ,  _snake_case							)
      )
      _A        =       list(_snake_case							)
      shuffle(_snake_case							)
      return "".join(_snake_case							)

      # random is a generalised function for letters, characters and numbers






def 						_snake_case					( _snake_case							: str    ,  _snake_case							: int							)   -> str:






      '''simple docstring'''


      return "".join(secrets.choice(_snake_case							) for _ in range(_snake_case							)							)






def 						_snake_case					( _snake_case							: Dict    ,  _snake_case							: Optional[int]							)   -> int:






      '''simple docstring'''


      pass  # Put your code here...






def 						_snake_case					( _snake_case							: Any    ,  _snake_case							: str							)   -> Dict:






      '''simple docstring'''


      pass  # Put your code here...






def 						_snake_case					( _snake_case							: Union[str, Any]    ,  _snake_case							: int							)   -> int:






      '''simple docstring'''


      pass  # Put your code here...






def 						_snake_case					( _snake_case							: str    ,  _snake_case							: int = 8							)   -> bool:






      '''simple docstring'''


      if len(_snake_case							) < min_length:
            # Your Password must be at least 8 characters long
            return False

      _A        =       any(char in ascii_uppercase for char in password							)
      _A        =       any(char in ascii_lowercase for char in password							)
      _A        =       any(char in digits for char in password							)
      _A        =       any(char in punctuation for char in password							)

      return upper and lower and num and spec_char
      # Passwords should contain UPPERCASE, lowerase
      # numbers, and special characters






def 						_snake_case					( )   -> Optional[Any]:






      '''simple docstring'''


      _A        =       int(input('Please indicate the max length of your password: '							).strip()							)
      _A        =       input(
          'Please indicate the characters that must be in your password: '							).strip()
      print('Password generated:'    ,  password_generator(_snake_case							)							)
      print(
          'Alternative Password generated:'    ,  alternative_password_generator(_snake_case    ,  _snake_case							)    ,  )
      print('[If you are thinking of using this passsword, You better save it.]'							)


if __name__ == "__main__":
       main()

