




import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       CLIPTokenizer
 lowercase_							       =       CLIPTokenizerFast
 lowercase_							       =       True
 lowercase_							       =       {}
 lowercase_							       =       False



 def  lowerCAmelCase_    (				self    :						Optional[Any]		):
       super().setUp()

       # fmt: off
       SCREAMING_SNAKE_CASE_      		=     ['l', 'o', 'w', 'e', 'r', 's', 't', 'i', 'd', 'n', 'lo', 'l</w>', 'w</w>', 'r</w>', 't</w>', 'low</w>', 'er</w>', 'lowest</w>', 'newer</w>', 'wider', '<unk>', '<|startoftext|>', '<|endoftext|>']
       # fmt: on
       SCREAMING_SNAKE_CASE_      		=     dict(zip(_lowerCAmelCase							,							range(len(_lowerCAmelCase		)		)		)		)
       SCREAMING_SNAKE_CASE_      		=     ['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>']
       SCREAMING_SNAKE_CASE_      		=     {'unk_token': '<unk>'}

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



 def  lowerCAmelCase_    (				self    :						str							,							**_lowerCAmelCase    :						Optional[Any]		):
       kwargs.update(self.special_tokens_map		)
       return CLIPTokenizer.from_pretrained(self.tmpdirname							,							**_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Tuple							,							**_lowerCAmelCase    :						int		):
       kwargs.update(self.special_tokens_map		)
       return CLIPTokenizerFast.from_pretrained(self.tmpdirname							,							**_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						int							,							_lowerCAmelCase    :						List[Any]		):
       SCREAMING_SNAKE_CASE_      		=     'lower newer'
       SCREAMING_SNAKE_CASE_      		=     'lower newer'
       return input_text, output_text



 def  lowerCAmelCase_    (				self    :						str		):
       SCREAMING_SNAKE_CASE_      		=     CLIPTokenizer(self.vocab_file							,							self.merges_file							,							**self.special_tokens_map		)
       SCREAMING_SNAKE_CASE_      		=     'lower newer'
       SCREAMING_SNAKE_CASE_      		=     ['lo', 'w', 'er</w>', 'n', 'e', 'w', 'er</w>']
       SCREAMING_SNAKE_CASE_      		=     tokenizer.tokenize(_lowerCAmelCase		)
       self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     tokens + [tokenizer.unk_token]
       SCREAMING_SNAKE_CASE_      		=     [10, 2, 16, 9, 3, 2, 16, 20]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase		)							,							_lowerCAmelCase		)



 @require_ftfy
 def  lowerCAmelCase_    (				self    :						Dict		):
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"		):
                   SCREAMING_SNAKE_CASE_      		=     self.tokenizer_class.from_pretrained(_lowerCAmelCase							,							**_lowerCAmelCase		)
                   SCREAMING_SNAKE_CASE_      		=     self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase							,							**_lowerCAmelCase		)

                   SCREAMING_SNAKE_CASE_      		=     'A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d.'
                   SCREAMING_SNAKE_CASE_      		=     tokenizer_s.tokenize(_lowerCAmelCase		)
                   SCREAMING_SNAKE_CASE_      		=     tokenizer_r.tokenize(_lowerCAmelCase		)

                   self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)

                   # Test that the tokenization is identical on an example containing a character (Latin Small Letter A
                   # with Tilde) encoded in 2 different ways
                   SCREAMING_SNAKE_CASE_      		=     'xa\u0303y' + ' ' + 'x\xe3y'
                   SCREAMING_SNAKE_CASE_      		=     tokenizer_s.tokenize(_lowerCAmelCase		)
                   SCREAMING_SNAKE_CASE_      		=     tokenizer_r.tokenize(_lowerCAmelCase		)

                   self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)

                   # Test that the tokenization is identical on unicode of space type
                   SCREAMING_SNAKE_CASE_      		=     [
                       '\u0009',  # (horizontal tab, '\t')
                       '\u000B',  # (vertical tab)
                       '\u000C',  # (form feed)
                       '\u0020',  # (space, ' ')
                       '\u200E',  # (left-to-right mark):w
                       '\u200F',  # (right-to-left mark)
                   ]
                   for unicode_seq in spaces_unicodes:
                         SCREAMING_SNAKE_CASE_      		=     tokenizer_s.tokenize(_lowerCAmelCase		)
                         SCREAMING_SNAKE_CASE_      		=     tokenizer_r.tokenize(_lowerCAmelCase		)

                         self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)

                   # Test that the tokenization is identical on unicode of line break type
                   SCREAMING_SNAKE_CASE_      		=     [
                       '\u000A',  # (line feed, '\n')
                       '\r\n',  # (carriage return and line feed, '\r\n')
                       '\u000D',  # (carriage return, '\r')
                       '\r',  # (carriage return, '\r')
                       '\u000D',  # (carriage return, '\r')
                       '\u2028',  # (line separator)
                       '\u2029',  # (paragraph separator)
                       # "\u0085", # (next line)
                   ]

                   # The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
                   # it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
                   # space (and thus into an empty list).

                   for unicode_seq in line_break_unicodes:
                         SCREAMING_SNAKE_CASE_      		=     tokenizer_s.tokenize(_lowerCAmelCase		)
                         SCREAMING_SNAKE_CASE_      		=     tokenizer_r.tokenize(_lowerCAmelCase		)

                         self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space`
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"		):
                   SCREAMING_SNAKE_CASE_      		=     'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
                   SCREAMING_SNAKE_CASE_      		=     F"{text_of_1_token} {text_of_1_token}"

                   SCREAMING_SNAKE_CASE_      		=     self.rust_tokenizer_class.from_pretrained(
                       _lowerCAmelCase							,							use_fast=_lowerCAmelCase							,							)
                   SCREAMING_SNAKE_CASE_      		=     tokenizer_r(_lowerCAmelCase							,							return_offsets_mapping=_lowerCAmelCase							,							add_special_tokens=_lowerCAmelCase		)
                   self.assertEqual(encoding.offset_mapping[0]							,							(0, len(_lowerCAmelCase		))		)
                   self.assertEqual(
                       encoding.offset_mapping[1]							,							(len(_lowerCAmelCase		) + 1, len(_lowerCAmelCase		) + 1 + len(_lowerCAmelCase		))							,							)

                   SCREAMING_SNAKE_CASE_      		=     F" {text}"

                   SCREAMING_SNAKE_CASE_      		=     self.rust_tokenizer_class.from_pretrained(
                       _lowerCAmelCase							,							use_fast=_lowerCAmelCase							,							)
                   SCREAMING_SNAKE_CASE_      		=     tokenizer_r(_lowerCAmelCase							,							return_offsets_mapping=_lowerCAmelCase							,							add_special_tokens=_lowerCAmelCase		)
                   self.assertEqual(encoding.offset_mapping[0]							,							(1, 1 + len(_lowerCAmelCase		))		)
                   self.assertEqual(
                       encoding.offset_mapping[1]							,							(1 + len(_lowerCAmelCase		) + 1, 1 + len(_lowerCAmelCase		) + 1 + len(_lowerCAmelCase		))							,							)



 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       # Test related to the breaking change introduced in transformers v4.17.0
       # We need to check that an error in raised when the user try to load a previous version of the tokenizer.
       with self.assertRaises(_lowerCAmelCase		) as context:
             self.rust_tokenizer_class.from_pretrained('robot-test/old-clip-tokenizer'		)

       self.assertTrue(
           context.exception.args[0].startswith(
               'The `backend_tokenizer` provided does not match the expected format.'		)		)



 @require_ftfy
 def  lowerCAmelCase_    (				self    :						Dict		):
       super().test_tokenization_python_rust_equals()




 def  lowerCAmelCase_    (				self    :						Any		):
       # CLIP always lower cases letters
       pass





from __future__ import annotations

from typing import TypedDict





class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE   ):


 '''simple docstring'''







 lowercase_							       =       42
 lowercase_							       =       42


def    UpperCAmelCase_				( __UpperCAmelCase		:      str				)   ->					list[str]:
      if not isinstance(__UpperCAmelCase     ,     __UpperCAmelCase				):
            raise TypeError('The parameter s type must be str.'				)

      return [s[i:] + s[:i] for i in range(len(__UpperCAmelCase				)				)]

def    UpperCAmelCase_				( __UpperCAmelCase		:      str				)   ->					BWTTransformDict:
      if not isinstance(__UpperCAmelCase     ,     __UpperCAmelCase				):
            raise TypeError('The parameter s type must be str.'				)
      if not s:
            raise ValueError('The parameter s must not be empty.'				)

      SCREAMING_SNAKE_CASE_      		=     all_rotations(__UpperCAmelCase				)
      rotations.sort()  # sort the list of rotations in alphabetically order
      # make a string composed of the last char of each rotation
      SCREAMING_SNAKE_CASE_      		=     {
          "bwt_string": "".join([word[-1] for word in rotations]				),
          "idx_original_string": rotations.index(__UpperCAmelCase				),
      }
      return response

def    UpperCAmelCase_				( __UpperCAmelCase		:      str     ,     __UpperCAmelCase		:      int				)   ->					str:
      if not isinstance(__UpperCAmelCase     ,     __UpperCAmelCase				):
            raise TypeError('The parameter bwt_string type must be str.'				)
      if not bwt_string:
            raise ValueError('The parameter bwt_string must not be empty.'				)
      try:
            SCREAMING_SNAKE_CASE_      		=     int(__UpperCAmelCase				)
      except ValueError:
            raise TypeError(
                'The parameter idx_original_string type must be int or passive'
                ' of cast to int.'				)
      if idx_original_string < 0:
            raise ValueError('The parameter idx_original_string must not be lower than 0.'				)
      if idx_original_string >= len(__UpperCAmelCase				):
            raise ValueError(
                'The parameter idx_original_string must be lower than' ' len(bwt_string).'				)

      SCREAMING_SNAKE_CASE_      		=     [''] * len(__UpperCAmelCase				)
      for _ in range(len(__UpperCAmelCase				)				):
            for i in range(len(__UpperCAmelCase				)				):
                  SCREAMING_SNAKE_CASE_      		=     bwt_string[i] + ordered_rotations[i]
            ordered_rotations.sort()
      return ordered_rotations[idx_original_string]


if __name__ == "__main__":
   lowerCamelCase__					:  Optional[int]      							=				'Provide a string that I will generate its BWT transform: '
   lowerCamelCase__					:  List[str]      							=				input(entry_msg).strip()
   lowerCamelCase__					:  int      							=				bwt_transform(s)
   print(
       f'''Burrows Wheeler transform for string \'{s}\' results '''
       f'''in \'{result['bwt_string']}\''''
   )
   lowerCamelCase__					:  Dict      							=				reverse_bwt(result['bwt_string'], result['idx_original_string'])
   print(
       f'''Reversing Burrows Wheeler transform for entry \'{result['bwt_string']}\' '''
       f'''we get original string \'{original_string}\''''
   )