


import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
 __lowerCAmelCase			=							'''pt'''
elif is_tf_available():
 __lowerCAmelCase			=							'''tf'''
else:
 __lowerCAmelCase			=							'''jax'''





class   __a      (   __UpperCamelCase	,	unittest.TestCase				):
 __lowercase			:							List[Any]       					=			PerceiverTokenizer
 __lowercase			:							str       					=			False
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[Any]:




        '''simple docstring'''
        super().setUp()
        lowercase__:       str        =       PerceiverTokenizer()
        tokenizer.save_pretrained(self.tmpdirname			)
 @cached_property
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    int:




        '''simple docstring'''
        return PerceiverTokenizer.from_pretrained('deepmind/language-perceiver'			)
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			**lowerCAmelCase__			) ->    PerceiverTokenizer:




        '''simple docstring'''
        return self.tokenizer_class.from_pretrained(self.tmpdirname    ,			**lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			lowerCAmelCase__    ,			lowerCAmelCase__=False    ,			lowerCAmelCase__=20    ,			lowerCAmelCase__=5			) ->    Tuple[str, list]:




        '''simple docstring'''
        # XXX The default common tokenizer tests assume that every ID is decodable on its own.
        # This assumption is invalid for Perceiver because single bytes might not be
        # valid utf-8 (byte 128 for instance).
        # Here we're overriding the smallest possible method to provide
        # a clean sequence without making the same assumption.

        lowercase__:       str        =       []
        for i in range(len(lowerCAmelCase__			)			):
               try:
                      lowercase__:       List[Any]        =       tokenizer.decode([i]    ,			clean_up_tokenization_spaces=lowerCAmelCase__			)
               except UnicodeDecodeError:
                      pass
               toks.append((i, tok)			)

        lowercase__:       Tuple        =       list(filter(lambda lowerCAmelCase__			: re.match(R'^[ a-zA-Z]+$'    ,			t[1]			)    ,			lowerCAmelCase__			)			)
        lowercase__:       Tuple        =       list(filter(lambda lowerCAmelCase__			: [t[0]] == tokenizer.encode(t[1]    ,			add_special_tokens=lowerCAmelCase__			)    ,			lowerCAmelCase__			)			)
        if max_length is not None and len(lowerCAmelCase__			) > max_length:
               lowercase__:       Dict        =       toks[:max_length]
        if min_length is not None and len(lowerCAmelCase__			) < min_length and len(lowerCAmelCase__			) > 0:
               while len(lowerCAmelCase__			) < min_length:
                      lowercase__:       Dict        =       toks + toks
        # toks_str = [t[1] for t in toks]
        lowercase__:       str        =       [t[0] for t in toks]

        # Ensure consistency
        lowercase__:       Optional[Any]        =       tokenizer.decode(lowerCAmelCase__    ,			clean_up_tokenization_spaces=lowerCAmelCase__			)
        if " " not in output_txt and len(lowerCAmelCase__			) > 1:
               lowercase__:       Tuple        =       (
                   tokenizer.decode([toks_ids[0]]    ,			clean_up_tokenization_spaces=lowerCAmelCase__			)
                   + ' '
                   + tokenizer.decode(toks_ids[1:]    ,			clean_up_tokenization_spaces=lowerCAmelCase__			)
               )
        if with_prefix_space:
               lowercase__:       Dict        =       ' ' + output_txt
        lowercase__:       List[Any]        =       tokenizer.encode(lowerCAmelCase__    ,			add_special_tokens=lowerCAmelCase__			)
        return output_txt, output_ids
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Dict:




        '''simple docstring'''
        lowercase__:       Optional[Any]        =       self.perceiver_tokenizer
        lowercase__:       Union[str, Any]        =       'Unicode €.'
        lowercase__:       Dict        =       tokenizer(lowerCAmelCase__			)
        lowercase__:       Tuple        =       [4, 91, 116, 111, 105, 117, 106, 107, 38, 232, 136, 178, 52, 5]
        self.assertEqual(encoded['input_ids']    ,			lowerCAmelCase__			)

        # decoding
        lowercase__:       List[str]        =       tokenizer.decode(lowerCAmelCase__			)
        self.assertEqual(lowerCAmelCase__    ,			'[CLS]Unicode €.[SEP]'			)

        lowercase__:       Any        =       tokenizer('e è é ê ë'			)
        lowercase__:       str        =       [4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
        self.assertEqual(encoded['input_ids']    ,			lowerCAmelCase__			)
        # decoding
        lowercase__:       Dict        =       tokenizer.decode(lowerCAmelCase__			)
        self.assertEqual(lowerCAmelCase__    ,			'[CLS]e è é ê ë[SEP]'			)

        # encode/decode, but with `encode` instead of `__call__`
        self.assertEqual(tokenizer.decode(tokenizer.encode('e è é ê ë'			)			)    ,			'[CLS]e è é ê ë[SEP]'			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    int:




        '''simple docstring'''
        lowercase__:       Dict        =       self.perceiver_tokenizer
        lowercase__:       List[Any]        =       ['A long paragraph for summarization.', 'Another paragraph for summarization.']
        # fmt: off
        lowercase__:       Optional[Any]        =       [4, 71, 38, 114, 117, 116, 109, 38, 118, 103, 120, 103, 109, 120, 103, 118, 110, 38, 108, 117, 120, 38, 121, 123, 115, 115, 103, 120, 111, 128, 103, 122, 111, 117, 116, 52, 5, 0]
        # fmt: on
        lowercase__:       Dict        =       tokenizer(lowerCAmelCase__    ,			padding=lowerCAmelCase__    ,			return_tensors=lowerCAmelCase__			)
        self.assertIsInstance(lowerCAmelCase__    ,			lowerCAmelCase__			)

        if FRAMEWORK != "jax":
               lowercase__:       Tuple        =       list(batch.input_ids.numpy()[0]			)
        else:
               lowercase__:       Tuple        =       list(batch.input_ids.tolist()[0]			)

        self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)

        self.assertEqual((2, 38)    ,			batch.input_ids.shape			)
        self.assertEqual((2, 38)    ,			batch.attention_mask.shape			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Union[str, Any]:




        '''simple docstring'''
        lowercase__:       List[Any]        =       self.perceiver_tokenizer
        lowercase__:       Dict        =       ['A long paragraph for summarization.', 'Another paragraph for summarization.']
        lowercase__:       str        =       tokenizer(lowerCAmelCase__    ,			padding=lowerCAmelCase__    ,			return_tensors=lowerCAmelCase__			)
        # check if input_ids are returned and no decoder_input_ids
        self.assertIn('input_ids'    ,			lowerCAmelCase__			)
        self.assertIn('attention_mask'    ,			lowerCAmelCase__			)
        self.assertNotIn('decoder_input_ids'    ,			lowerCAmelCase__			)
        self.assertNotIn('decoder_attention_mask'    ,			lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[int]:




        '''simple docstring'''
        lowercase__:       List[str]        =       self.perceiver_tokenizer
        lowercase__:       Optional[int]        =       [
            'Summary of the text.',
            'Another summary.',
        ]
        lowercase__:       Tuple        =       tokenizer(
            text_target=lowerCAmelCase__    ,			max_length=32    ,			padding='max_length'    ,			truncation=lowerCAmelCase__    ,			return_tensors=lowerCAmelCase__			)
        self.assertEqual(32    ,			targets['input_ids'].shape[1]			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[str]:




        '''simple docstring'''
        # safety check on max_len default value so we are sure the test works
        lowercase__:       Union[str, Any]        =       self.get_tokenizers()
        for tokenizer in tokenizers:
               with self.subTest(F'{tokenizer.__class__.__name__}'			):
                      self.assertNotEqual(tokenizer.model_max_length    ,			42			)

        # Now let's start the test
        lowercase__:       List[Any]        =       self.get_tokenizers()
        for tokenizer in tokenizers:
               with self.subTest(F'{tokenizer.__class__.__name__}'			):
                      # Isolate this from the other tests because we save additional tokens/etc
                      lowercase__:       Union[str, Any]        =       tempfile.mkdtemp()

                      lowercase__:       List[Any]        =       ' He is very happy, UNwant\u00E9d,running'
                      lowercase__:       List[str]        =       tokenizer.encode(lowerCAmelCase__    ,			add_special_tokens=lowerCAmelCase__			)
                      tokenizer.save_pretrained(lowerCAmelCase__			)

                      lowercase__:       Dict        =       tokenizer.__class__.from_pretrained(lowerCAmelCase__			)
                      lowercase__:       Optional[Any]        =       after_tokenizer.encode(lowerCAmelCase__    ,			add_special_tokens=lowerCAmelCase__			)
                      self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)

                      shutil.rmtree(lowerCAmelCase__			)

        lowercase__:       str        =       self.get_tokenizers(model_max_length=42			)
        for tokenizer in tokenizers:
               with self.subTest(F'{tokenizer.__class__.__name__}'			):
                      # Isolate this from the other tests because we save additional tokens/etc
                      lowercase__:       Dict        =       tempfile.mkdtemp()

                      lowercase__:       Any        =       ' He is very happy, UNwant\u00E9d,running'
                      tokenizer.add_tokens(['bim', 'bambam']			)
                      lowercase__:       List[str]        =       tokenizer.additional_special_tokens
                      additional_special_tokens.append('new_additional_special_token'			)
                      tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}			)
                      lowercase__:       str        =       tokenizer.encode(lowerCAmelCase__    ,			add_special_tokens=lowerCAmelCase__			)
                      tokenizer.save_pretrained(lowerCAmelCase__			)

                      lowercase__:       Union[str, Any]        =       tokenizer.__class__.from_pretrained(lowerCAmelCase__			)
                      lowercase__:       str        =       after_tokenizer.encode(lowerCAmelCase__    ,			add_special_tokens=lowerCAmelCase__			)
                      self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)
                      self.assertIn('new_additional_special_token'    ,			after_tokenizer.additional_special_tokens			)
                      self.assertEqual(after_tokenizer.model_max_length    ,			42			)

                      lowercase__:       Optional[Any]        =       tokenizer.__class__.from_pretrained(lowerCAmelCase__    ,			model_max_length=43			)
                      self.assertEqual(tokenizer.model_max_length    ,			43			)

                      shutil.rmtree(lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[Any]:




        '''simple docstring'''
        lowercase__:       Tuple        =       []
        if self.test_slow_tokenizer:
               tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())			)

        if self.test_rust_tokenizer:
               tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())			)

        for tokenizer_class, tokenizer_utils in tokenizer_list:
               with tempfile.TemporaryDirectory() as tmp_dir:
                      tokenizer_utils.save_pretrained(lowerCAmelCase__			)

                      with open(os.path.join(lowerCAmelCase__    ,			'special_tokens_map.json'			)    ,			encoding='utf-8'			) as json_file:
                             lowercase__:       List[str]        =       json.load(lowerCAmelCase__			)

                      with open(os.path.join(lowerCAmelCase__    ,			'tokenizer_config.json'			)    ,			encoding='utf-8'			) as json_file:
                             lowercase__:       Dict        =       json.load(lowerCAmelCase__			)

                      lowercase__:       Dict        =       [F'<extra_id_{i}>' for i in range(125			)]

                      lowercase__:       Dict        =       added_tokens_extra_ids + [
                          'an_additional_special_token'
                      ]
                      lowercase__:       Optional[int]        =       added_tokens_extra_ids + [
                          'an_additional_special_token'
                      ]

                      with open(os.path.join(lowerCAmelCase__    ,			'special_tokens_map.json'			)    ,			'w'    ,			encoding='utf-8'			) as outfile:
                             json.dump(lowerCAmelCase__    ,			lowerCAmelCase__			)
                      with open(os.path.join(lowerCAmelCase__    ,			'tokenizer_config.json'			)    ,			'w'    ,			encoding='utf-8'			) as outfile:
                             json.dump(lowerCAmelCase__    ,			lowerCAmelCase__			)

                      # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                      # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                      # "special_tokens_map.json" files
                      lowercase__:       Optional[int]        =       tokenizer_class.from_pretrained(
                          lowerCAmelCase__    ,			)
                      self.assertIn(
                          'an_additional_special_token'    ,			tokenizer_without_change_in_init.additional_special_tokens			)
                      self.assertEqual(
                          ['an_additional_special_token']    ,			tokenizer_without_change_in_init.convert_ids_to_tokens(
                              tokenizer_without_change_in_init.convert_tokens_to_ids(['an_additional_special_token']			)			)    ,			)

                      # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                      lowercase__:       int        =       added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'    ,			lstrip=lowerCAmelCase__			)]
                      lowercase__:       List[str]        =       tokenizer_class.from_pretrained(
                          lowerCAmelCase__    ,			additional_special_tokens=lowerCAmelCase__    ,			)

                      self.assertIn('a_new_additional_special_token'    ,			tokenizer.additional_special_tokens			)
                      self.assertEqual(
                          ['a_new_additional_special_token']    ,			tokenizer.convert_ids_to_tokens(
                              tokenizer.convert_tokens_to_ids(['a_new_additional_special_token']			)			)    ,			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[Any]:




        '''simple docstring'''
        lowercase__:       str        =       self.perceiver_tokenizer
        self.assertEqual(tokenizer.decode([178]			)    ,			'�'			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[str]:




        '''simple docstring'''
        pass
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Any:




        '''simple docstring'''
        pass
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[int]:




        '''simple docstring'''
        pass
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Dict:




        '''simple docstring'''
        pass
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[Any]:




        '''simple docstring'''
        # The default common tokenizer tests uses invalid tokens for Perceiver that can only accept one-character
        # strings and special added tokens as tokens
        lowercase__:       Optional[Any]        =       self.get_tokenizers(fast=lowerCAmelCase__    ,			do_lower_case=lowerCAmelCase__			)
        for tokenizer in tokenizers:
               with self.subTest(F'{tokenizer.__class__.__name__}'			):
                      lowercase__:       Optional[Any]        =       ['[CLS]', 't', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 's', 't', '[SEP]']
                      lowercase__:       Any        =       tokenizer.convert_tokens_to_string(lowerCAmelCase__			)

                      self.assertIsInstance(lowerCAmelCase__    ,			lowerCAmelCase__			)






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   __a      (   __UpperCamelCase	,	unittest.TestCase				):
 __lowercase			:							Optional[int]       					=			CLIPTokenizer
 __lowercase			:							str       					=			CLIPTokenizerFast
 __lowercase			:							Tuple       					=			True
 __lowercase			:							str       					=			{}
 __lowercase			:							Dict       					=			False
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    int:




        '''simple docstring'''
        super().setUp()

        # fmt: off
        lowercase__:       str        =       ['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
        lowercase__:       List[str]        =       dict(zip(lowerCAmelCase__    ,			range(len(lowerCAmelCase__			)			)			)			)
        lowercase__:       int        =       ['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>']
        lowercase__:       Optional[int]        =       {'unk_token': '<unk>'}

        lowercase__:       int        =       os.path.join(self.tmpdirname    ,			VOCAB_FILES_NAMES['vocab_file']			)
        lowercase__:       Union[str, Any]        =       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 		SCREAMING_SNAKE_CASE__       (       self    ,			**lowerCAmelCase__			) ->    List[str]:




        '''simple docstring'''
        kwargs.update(self.special_tokens_map			)
        return CLIPTokenizer.from_pretrained(self.tmpdirname    ,			**lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			**lowerCAmelCase__			) ->    Optional[int]:




        '''simple docstring'''
        kwargs.update(self.special_tokens_map			)
        return CLIPTokenizerFast.from_pretrained(self.tmpdirname    ,			**lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			lowerCAmelCase__			) ->    Union[str, Any]:




        '''simple docstring'''
        lowercase__:       Dict        =       'lower newer'
        lowercase__:       Dict        =       'lower newer'
        return input_text, output_text
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[Any]:




        '''simple docstring'''
        lowercase__:       Union[str, Any]        =       CLIPTokenizer(self.vocab_file    ,			self.merges_file    ,			**self.special_tokens_map			)
        lowercase__:       Dict        =       'lower newer'
        lowercase__:       Union[str, Any]        =       ['lo', 'w', 'er</w>', 'n', 'e', 'w', 'er</w>']
        lowercase__:       Any        =       tokenizer.tokenize(lowerCAmelCase__			)
        self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)

        lowercase__:       Tuple        =       tokens + [tokenizer.unk_token]
        lowercase__:       Tuple        =       [10, 2, 16, 9, 3, 2, 16, 20]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase__			)    ,			lowerCAmelCase__			)
 @require_ftfy
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Tuple:




        '''simple docstring'''
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
               with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'			):
                      lowercase__:       List[str]        =       self.tokenizer_class.from_pretrained(lowerCAmelCase__    ,			**lowerCAmelCase__			)
                      lowercase__:       Optional[int]        =       self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__    ,			**lowerCAmelCase__			)

                      lowercase__:       Optional[int]        =       'A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d.'
                      lowercase__:       Optional[Any]        =       tokenizer_s.tokenize(lowerCAmelCase__			)
                      lowercase__:       Dict        =       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
                      lowercase__:       Dict        =       'xa\u0303y' + ' ' + 'x\xe3y'
                      lowercase__:       Tuple        =       tokenizer_s.tokenize(lowerCAmelCase__			)
                      lowercase__:       int        =       tokenizer_r.tokenize(lowerCAmelCase__			)

                      self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)

                      # Test that the tokenization is identical on unicode of space type
                      lowercase__:       str        =       [
                          '\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:
                             lowercase__:       Optional[Any]        =       tokenizer_s.tokenize(lowerCAmelCase__			)
                             lowercase__:       Tuple        =       tokenizer_r.tokenize(lowerCAmelCase__			)

                             self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)

                      # Test that the tokenization is identical on unicode of line break type
                      lowercase__:       str        =       [
                          '\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:
                             lowercase__:       Optional[int]        =       tokenizer_s.tokenize(lowerCAmelCase__			)
                             lowercase__:       Optional[int]        =       tokenizer_r.tokenize(lowerCAmelCase__			)

                             self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[int]:




        '''simple docstring'''
        # 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})'			):
                      lowercase__:       Optional[int]        =       'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
                      lowercase__:       Optional[int]        =       F'{text_of_1_token} {text_of_1_token}'

                      lowercase__:       int        =       self.rust_tokenizer_class.from_pretrained(
                          lowerCAmelCase__    ,			use_fast=lowerCAmelCase__    ,			)
                      lowercase__:       Dict        =       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__			))    ,			)

                      lowercase__:       Any        =       F' {text}'

                      lowercase__:       Union[str, Any]        =       self.rust_tokenizer_class.from_pretrained(
                          lowerCAmelCase__    ,			use_fast=lowerCAmelCase__    ,			)
                      lowercase__:       int        =       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 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[str]:




        '''simple docstring'''
        # 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 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[Any]:




        '''simple docstring'''
        super().test_tokenization_python_rust_equals()
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Tuple:




        '''simple docstring'''
        # CLIP always lower cases letters
        pass


