





'''simple docstring'''




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

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

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
  lowercase__       : Any         =       '''pt'''
elif is_tf_available():
  lowercase__       : Tuple         =       '''tf'''
else:
  lowercase__       : Union[str, Any]         =       '''jax'''


class 					SCREAMING_SNAKE_CASE       (a__   ,						unittest.TestCase				):
     lowerCAmelCase						     =			ByTaTokenizer
     lowerCAmelCase						     =			False


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          super().setUp()
          __A		:					Any						=			ByTaTokenizer()
          tokenizer.save_pretrained(self.tmpdirname)


     @cached_property
     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          return ByTaTokenizer.from_pretrained('google/byt5-small')


     def 				SCREAMING_SNAKE_CASE    (		self		,      **_UpperCAmelCase):

          '''simple docstring'''






          return self.tokenizer_class.from_pretrained(self.tmpdirname		,      **_UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase=False		,      _UpperCAmelCase=20		,      _UpperCAmelCase=5):

          '''simple docstring'''






          __A		:					Optional[Any]						=			[]
          for i in range(len(_UpperCAmelCase)):
               try:
                    __A		:					Optional[Any]						=			tokenizer.decode([i]		,      clean_up_tokenization_spaces=_UpperCAmelCase)
               except UnicodeDecodeError:
                    pass
               toks.append((i, tok))

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

          # Ensure consistency
          __A		:					Optional[Any]						=			tokenizer.decode(_UpperCAmelCase		,      clean_up_tokenization_spaces=_UpperCAmelCase)
          if " " not in output_txt and len(_UpperCAmelCase) > 1:
               __A		:					Union[str, Any]						=			(
                   tokenizer.decode([toks_ids[0]]		,      clean_up_tokenization_spaces=_UpperCAmelCase)
                   + ' '
                   + tokenizer.decode(toks_ids[1:]		,      clean_up_tokenization_spaces=_UpperCAmelCase)
               )
          if with_prefix_space:
               __A		:					Dict						=			' ' + output_txt
          __A		:					int						=			tokenizer.encode(_UpperCAmelCase		,      add_special_tokens=_UpperCAmelCase)
          return output_txt, output_ids


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					List[Any]						=			self.ta_base_tokenizer
          __A		:					Tuple						=			tokenizer(['hi</s>', 'I went to the gym</s>', '</s>'])
          __A		:					List[Any]						=			tokenizer(['hi', 'I went to the gym', ''])
          self.assertListEqual(batch_with_eos_added['input_ids']		,      batch_without_eos_added['input_ids'])


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					Optional[int]						=			self.ta_base_tokenizer
          __A		:					Any						=			'Unicode €.'
          __A		:					Union[str, Any]						=			tokenizer(_UpperCAmelCase)
          __A		:					Optional[Any]						=			[88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
          self.assertEqual(encoded['input_ids']		,      _UpperCAmelCase)

          # decoding
          __A		:					List[str]						=			tokenizer.decode(_UpperCAmelCase)
          self.assertEqual(_UpperCAmelCase		,      'Unicode €.</s>')

          __A		:					Any						=			tokenizer('e è é ê ë')
          __A		:					List[str]						=			[104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
          self.assertEqual(encoded['input_ids']		,      _UpperCAmelCase)
          # decoding
          __A		:					Optional[int]						=			tokenizer.decode(_UpperCAmelCase)
          self.assertEqual(_UpperCAmelCase		,      'e è é ê ë</s>')

          # encode/decode, but with `encode` instead of `__call__`
          self.assertEqual(tokenizer.decode(tokenizer.encode('e è é ê ë'))		,      'e è é ê ë</s>')


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					Union[str, Any]						=			self.ta_base_tokenizer
          __A		:					Optional[Any]						=			['A long paragraph for summarization.', 'Another paragraph for summarization.']
          # fmt: off
          __A		:					Tuple						=			[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
          # fmt: on
          __A		:					str						=			tokenizer(_UpperCAmelCase		,      padding=_UpperCAmelCase		,      return_tensors=_UpperCAmelCase)
          self.assertIsInstance(_UpperCAmelCase		,      _UpperCAmelCase)

          if FRAMEWORK != "jax":
               __A		:					Optional[Any]						=			list(batch.input_ids.numpy()[0])
          else:
               __A		:					str						=			list(batch.input_ids.tolist()[0])

          self.assertListEqual(_UpperCAmelCase		,      _UpperCAmelCase)

          self.assertEqual((2, 37)		,      batch.input_ids.shape)
          self.assertEqual((2, 37)		,      batch.attention_mask.shape)


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					List[Any]						=			self.ta_base_tokenizer
          __A		:					str						=			['A long paragraph for summarization.', 'Another paragraph for summarization.']
          __A		:					Tuple						=			tokenizer(_UpperCAmelCase		,      padding=_UpperCAmelCase		,      return_tensors=_UpperCAmelCase)
          # check if input_ids are returned and no decoder_input_ids
          self.assertIn('input_ids'		,      _UpperCAmelCase)
          self.assertIn('attention_mask'		,      _UpperCAmelCase)
          self.assertNotIn('decoder_input_ids'		,      _UpperCAmelCase)
          self.assertNotIn('decoder_attention_mask'		,      _UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					Tuple						=			self.ta_base_tokenizer
          __A		:					Any						=			[
              'Summary of the text.',
              'Another summary.',
          ]
          __A		:					Optional[Any]						=			tokenizer(
              text_target=_UpperCAmelCase		,      max_length=32		,      padding='max_length'		,      truncation=_UpperCAmelCase		,      return_tensors=_UpperCAmelCase)
          self.assertEqual(32		,      targets['input_ids'].shape[1])


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					str						=			self.ta_base_tokenizer
          __A		:					Optional[Any]						=			['A long paragraph for summarization. </s>']
          __A		:					Dict						=			['Summary of the text. </s>']
          # fmt: off
          __A		:					str						=			[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
          __A		:					List[str]						=			[86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
          # fmt: on

          __A		:					Any						=			tokenizer(_UpperCAmelCase		,      text_target=_UpperCAmelCase)

          self.assertEqual(_UpperCAmelCase		,      batch['input_ids'][0])
          self.assertEqual(_UpperCAmelCase		,      batch['labels'][0])


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					List[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
          __A		:					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
                    __A		:					Dict						=			tempfile.mkdtemp()

                    __A		:					Dict						=			' He is very happy, UNwant\u00E9d,running'
                    __A		:					List[str]						=			tokenizer.encode(_UpperCAmelCase		,      add_special_tokens=_UpperCAmelCase)
                    tokenizer.save_pretrained(_UpperCAmelCase)

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

                    shutil.rmtree(_UpperCAmelCase)

          __A		:					List[Any]						=			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
                    __A		:					List[str]						=			tempfile.mkdtemp()

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

                    __A		:					Dict						=			tokenizer.__class__.from_pretrained(_UpperCAmelCase)
                    __A		:					Optional[Any]						=			after_tokenizer.encode(_UpperCAmelCase		,      add_special_tokens=_UpperCAmelCase)
                    self.assertListEqual(_UpperCAmelCase		,      _UpperCAmelCase)
                    self.assertIn('new_additional_special_token'		,      after_tokenizer.additional_special_tokens)
                    self.assertEqual(after_tokenizer.model_max_length		,      42)

                    __A		:					str						=			tokenizer.__class__.from_pretrained(_UpperCAmelCase		,      model_max_length=43)
                    self.assertEqual(tokenizer.model_max_length		,      43)

                    shutil.rmtree(_UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					List[Any]						=			[]
          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(_UpperCAmelCase)

                    with open(os.path.join(_UpperCAmelCase		,      'special_tokens_map.json')		,      encoding='utf-8') as json_file:
                         __A		:					Tuple						=			json.load(_UpperCAmelCase)

                    with open(os.path.join(_UpperCAmelCase		,      'tokenizer_config.json')		,      encoding='utf-8') as json_file:
                         __A		:					List[Any]						=			json.load(_UpperCAmelCase)

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

                    __A		:					Union[str, Any]						=			added_tokens_extra_ids + [
                        'an_additional_special_token'
                    ]
                    __A		:					List[Any]						=			added_tokens_extra_ids + [
                        'an_additional_special_token'
                    ]

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

                    # 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
                    __A		:					Any						=			tokenizer_class.from_pretrained(
                        _UpperCAmelCase		,      )
                    self.assertIn(
                        'an_additional_special_token'		,      tokenizer_without_change_in_init.additional_special_tokens)
                    # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
                    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
                    __A		:					Union[str, Any]						=			added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'		,      lstrip=_UpperCAmelCase)]
                    __A		:					int						=			tokenizer_class.from_pretrained(
                        _UpperCAmelCase		,      additional_special_tokens=_UpperCAmelCase		,      )

                    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):

          '''simple docstring'''






          __A		:					Optional[int]						=			[]
          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(_UpperCAmelCase)

                    __A		:					Optional[Any]						=			tokenizer_class.from_pretrained(_UpperCAmelCase)

                    self.assertTrue(tokenizer.decode([255]) == '')


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          pass


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          pass


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          pass


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          pass


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					Dict						=			self.get_tokenizers(fast=_UpperCAmelCase		,      do_lower_case=_UpperCAmelCase)
          for tokenizer in tokenizers:
               with self.subTest(F'{tokenizer.__class__.__name__}'):
                    __A		:					List[str]						=			['t', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 'x', 't', '</s>']
                    __A		:					Tuple						=			tokenizer.convert_tokens_to_string(_UpperCAmelCase)

                    self.assertIsInstance(_UpperCAmelCase		,      _UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					Optional[Any]						=			self.get_tokenizers()
          for tokenizer in tokenizers:
               with self.subTest(F'{tokenizer.__class__.__name__}'):
                    __A		:					Tuple						=			[
                        'bos_token',
                        'eos_token',
                        'unk_token',
                        'sep_token',
                        'pad_token',
                        'cls_token',
                        'mask_token',
                    ]

                    __A		:					Optional[int]						=			0
                    __A		:					List[Any]						=			tokenizer.convert_ids_to_tokens(
                        _UpperCAmelCase		,      skip_special_tokens=_UpperCAmelCase)

                    for attr in attributes_list:
                         setattr(_UpperCAmelCase		,      attr + '_id'		,      _UpperCAmelCase)
                         self.assertEqual(getattr(_UpperCAmelCase		,      _UpperCAmelCase)		,      _UpperCAmelCase)
                         self.assertEqual(getattr(_UpperCAmelCase		,      attr + '_id')		,      _UpperCAmelCase)

                         setattr(_UpperCAmelCase		,      attr + '_id'		,      _UpperCAmelCase)
                         self.assertEqual(getattr(_UpperCAmelCase		,      _UpperCAmelCase)		,      _UpperCAmelCase)
                         self.assertEqual(getattr(_UpperCAmelCase		,      attr + '_id')		,      _UpperCAmelCase)

                    setattr(_UpperCAmelCase		,      'additional_special_tokens_ids'		,      [])
                    self.assertListEqual(getattr(_UpperCAmelCase		,      'additional_special_tokens')		,      [])
                    self.assertListEqual(getattr(_UpperCAmelCase		,      'additional_special_tokens_ids')		,      [])

                    setattr(_UpperCAmelCase		,      'additional_special_tokens_ids'		,      [token_id_to_test_setters])
                    self.assertListEqual(getattr(_UpperCAmelCase		,      'additional_special_tokens')		,      [token_to_test_setters])
                    self.assertListEqual(getattr(_UpperCAmelCase		,      'additional_special_tokens_ids')		,      [token_id_to_test_setters])






'''simple docstring'''




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_camembert import CamembertTokenizer
else:
  lowercase__       : Optional[int]         =       None


lowercase__       : List[str]         =       logging.get_logger(__name__)

lowercase__       : Optional[Any]         =       {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase__       : List[str]         =       {
    '''vocab_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/tokenizer.json''',
    },
}

lowercase__       : Dict         =       {
    '''camembert-base''': 5_12,
}

lowercase__       : str         =       '''▁'''


class 					SCREAMING_SNAKE_CASE       (a__				):
     lowerCAmelCase						     =			VOCAB_FILES_NAMES
     lowerCAmelCase						     =			PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase						     =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase						     =			['''input_ids''', '''attention_mask''']
     lowerCAmelCase						     =			CamembertTokenizer


     def __init__(		self		,      _UpperCAmelCase=None		,      _UpperCAmelCase=None		,      _UpperCAmelCase="<s>"		,      _UpperCAmelCase="</s>"		,      _UpperCAmelCase="</s>"		,      _UpperCAmelCase="<s>"		,      _UpperCAmelCase="<unk>"		,      _UpperCAmelCase="<pad>"		,      _UpperCAmelCase="<mask>"		,      _UpperCAmelCase=["<s>NOTUSED", "</s>NOTUSED"]		,      **_UpperCAmelCase		,      ):

          '''simple docstring'''






          __A		:					int						=			AddedToken(_UpperCAmelCase		,      lstrip=_UpperCAmelCase		,      rstrip=_UpperCAmelCase) if isinstance(_UpperCAmelCase		,      _UpperCAmelCase) else mask_token

          super().__init__(
              _UpperCAmelCase		,      tokenizer_file=_UpperCAmelCase		,      bos_token=_UpperCAmelCase		,      eos_token=_UpperCAmelCase		,      sep_token=_UpperCAmelCase		,      cls_token=_UpperCAmelCase		,      unk_token=_UpperCAmelCase		,      pad_token=_UpperCAmelCase		,      mask_token=_UpperCAmelCase		,      additional_special_tokens=_UpperCAmelCase		,      **_UpperCAmelCase		,      )

          __A		:					List[str]						=			vocab_file
          __A		:					Optional[int]						=			False if not self.vocab_file else True


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase = None):

          '''simple docstring'''






          if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          __A		:					Optional[Any]						=			[self.cls_token_id]
          __A		:					Optional[int]						=			[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase = None):

          '''simple docstring'''






          __A		:					Optional[int]						=			[self.sep_token_id]
          __A		:					List[str]						=			[self.cls_token_id]

          if token_ids_a is None:
               return len(cls + token_ids_a + sep) * [0]
          return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase = None):

          '''simple docstring'''






          if not self.can_save_slow_tokenizer:
               raise ValueError(
                   'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
                   'tokenizer.')

          if not os.path.isdir(_UpperCAmelCase):
               logger.error(F'Vocabulary path ({save_directory}) should be a directory')
               return
          __A		:					List[Any]						=			os.path.join(
              _UpperCAmelCase		,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

          if os.path.abspath(self.vocab_file) != os.path.abspath(_UpperCAmelCase):
               copyfile(self.vocab_file		,      _UpperCAmelCase)

          return (out_vocab_file,)