

"""simple docstring"""






import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin







class 	__UpperCamelCase    (    a__							,							unittest.TestCase						):
  _UpperCAmelCase          =		CanineTokenizer
  _UpperCAmelCase          =		False

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      super().setUp()
      _lowerCAmelCase       :   str  =    CanineTokenizer()
      tokenizer.save_pretrained(self.tmpdirname      )

  @cached_property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return CanineTokenizer.from_pretrained('google/canine-s'      )

  def __lowerCamelCase		(		self    ,**_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Tuple  =    self.tokenizer_class.from_pretrained(self.tmpdirname    ,**_A      )
      _lowerCAmelCase       :   List[Any]  =    1024
      return tokenizer

  @require_torch
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Optional[Any]  =    self.canine_tokenizer
      _lowerCAmelCase       :   Tuple  =    ['Life is like a box of chocolates.', 'You never know what you\'re gonna get.']
      # fmt: off
      _lowerCAmelCase       :   int  =    [5_7344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 5_7345, 0, 0, 0, 0]
      # fmt: on
      _lowerCAmelCase       :   str  =    tokenizer(_A    ,padding=_A    ,return_tensors='pt'      )
      self.assertIsInstance(_A    ,_A      )

      _lowerCAmelCase       :   Tuple  =    list(batch.input_ids.numpy()[0]      )

      self.assertListEqual(_A    ,_A      )

      self.assertEqual((2, 39)    ,batch.input_ids.shape      )
      self.assertEqual((2, 39)    ,batch.attention_mask.shape      )

  @require_torch
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   List[str]  =    self.canine_tokenizer
      _lowerCAmelCase       :   Optional[int]  =    ['Once there was a man.', 'He wrote a test in HuggingFace Tranformers.']
      _lowerCAmelCase       :   Dict  =    tokenizer(_A    ,padding=_A    ,return_tensors='pt'      )
      # check if input_ids, attention_mask and token_type_ids are returned
      self.assertIn('input_ids'    ,_A      )
      self.assertIn('attention_mask'    ,_A      )
      self.assertIn('token_type_ids'    ,_A      )

  @require_torch
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Optional[int]  =    self.canine_tokenizer
      _lowerCAmelCase       :   Dict  =    [
          'What\'s the weater?',
          'It\'s about 25 degrees.',
      ]
      _lowerCAmelCase       :   Optional[int]  =    tokenizer(
          text_target=_A    ,max_length=32    ,padding='max_length'    ,truncation=_A    ,return_tensors='pt'      )
      self.assertEqual(32    ,targets['input_ids'].shape[1]      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   List[str]  =    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
      _lowerCAmelCase       :   Tuple  =    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
              _lowerCAmelCase       :   str  =    tempfile.mkdtemp()

              _lowerCAmelCase       :   int  =    ' He is very happy, UNwant\u00E9d,running'
              _lowerCAmelCase       :   Tuple  =    tokenizer.encode(_A    ,add_special_tokens=_A      )
              tokenizer.save_pretrained(_A      )

              _lowerCAmelCase       :   str  =    tokenizer.__class__.from_pretrained(_A      )
              _lowerCAmelCase       :   int  =    after_tokenizer.encode(_A    ,add_special_tokens=_A      )
              self.assertListEqual(_A    ,_A      )

              shutil.rmtree(_A      )

      _lowerCAmelCase       :   int  =    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
              _lowerCAmelCase       :   Union[str, Any]  =    tempfile.mkdtemp()

              _lowerCAmelCase       :   str  =    ' He is very happy, UNwant\u00E9d,running'

              _lowerCAmelCase       :   List[str]  =    tokenizer.additional_special_tokens

              # We can add a new special token for Canine as follows:
              _lowerCAmelCase       :   Optional[int]  =    chr(0xE007      )
              additional_special_tokens.append(_A      )
              tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}      )
              _lowerCAmelCase       :   Any  =    tokenizer.encode(_A    ,add_special_tokens=_A      )
              tokenizer.save_pretrained(_A      )

              _lowerCAmelCase       :   int  =    tokenizer.__class__.from_pretrained(_A      )
              _lowerCAmelCase       :   str  =    after_tokenizer.encode(_A    ,add_special_tokens=_A      )
              self.assertListEqual(_A    ,_A      )
              self.assertIn(_A    ,after_tokenizer.additional_special_tokens      )
              self.assertEqual(after_tokenizer.model_max_length    ,42      )

              _lowerCAmelCase       :   str  =    tokenizer.__class__.from_pretrained(_A    ,model_max_length=43      )
              self.assertEqual(tokenizer.model_max_length    ,43      )

              shutil.rmtree(_A      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Union[str, Any]  =    self.get_tokenizers(do_lower_case=_A      )
      for tokenizer in tokenizers:
          with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
              _lowerCAmelCase,					_lowerCAmelCase       :   Dict  =    self.get_clean_sequence(_A      )

              # a special token for Canine can be defined as follows:
              _lowerCAmelCase       :   List[Any]  =    0xE005
              _lowerCAmelCase       :   Dict  =    chr(_A      )

              tokenizer.add_special_tokens({'cls_token': special_token}      )
              _lowerCAmelCase       :   Any  =    tokenizer.encode(_A    ,add_special_tokens=_A      )
              self.assertEqual(len(_A      )    ,1      )

              _lowerCAmelCase       :   Tuple  =    tokenizer.decode(ids + encoded_special_token    ,clean_up_tokenization_spaces=_A      )
              _lowerCAmelCase       :   Union[str, Any]  =    tokenizer.encode(_A    ,add_special_tokens=_A      )

              _lowerCAmelCase       :   List[Any]  =    tokenizer.encode(_A    ,add_special_tokens=_A      )
              _lowerCAmelCase       :   Optional[Any]  =    tokenizer.encode(_A    ,add_special_tokens=_A      )
              self.assertEqual(_A    ,input_encoded + special_token_id      )

              _lowerCAmelCase       :   List[Any]  =    tokenizer.decode(_A    ,skip_special_tokens=_A      )
              self.assertTrue(special_token not in decoded      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   str  =    self.get_tokenizers(do_lower_case=_A      )
      for tokenizer in tokenizers:
          with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
              _lowerCAmelCase       :   Union[str, Any]  =    chr(0xE005      )
              _lowerCAmelCase       :   Tuple  =    chr(0xE006      )

              # `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
              tokenizer.add_tokens([SPECIAL_TOKEN_1]    ,special_tokens=_A      )
              # `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
              # which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
              tokenizer.add_special_tokens({'additional_special_tokens': [SPECIAL_TOKEN_2]}      )

              _lowerCAmelCase       :   str  =    tokenizer.tokenize(_A      )
              _lowerCAmelCase       :   Tuple  =    tokenizer.tokenize(_A      )

              self.assertEqual(len(_A      )    ,1      )
              self.assertEqual(len(_A      )    ,1      )
              self.assertEqual(token_a[0]    ,_A      )
              self.assertEqual(token_a[0]    ,_A      )

  @require_tokenizers
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Any  =    self.get_tokenizers(do_lower_case=_A      )
      for tokenizer in tokenizers:
          with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
              # a special token for Canine can be defined as follows:
              _lowerCAmelCase       :   Optional[int]  =    0xE006
              _lowerCAmelCase       :   List[Any]  =    chr(_A      )

              _lowerCAmelCase       :   Union[str, Any]  =    AddedToken(_A    ,lstrip=_A      )
              tokenizer.add_special_tokens({'additional_special_tokens': [new_token]}      )

              with tempfile.TemporaryDirectory() as tmp_dir_name:
                  tokenizer.save_pretrained(_A      )
                  tokenizer.from_pretrained(_A      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   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(_A      )

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

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

              # a special token for Canine can be defined as follows:
              _lowerCAmelCase       :   str  =    0xE006
              _lowerCAmelCase       :   List[str]  =    chr(_A      )

              _lowerCAmelCase       :   Dict  =    [new_token_a]
              _lowerCAmelCase       :   Optional[Any]  =    [new_token_a]

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

              # 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
              _lowerCAmelCase       :   Union[str, Any]  =    tokenizer_class.from_pretrained(_A    ,extra_ids=0      )
              self.assertIn(_A    ,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(
                  [new_token_a]    ,tokenizer_without_change_in_init.convert_ids_to_tokens(
                      tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]      )      )    ,)

              _lowerCAmelCase       :   List[Any]  =    0xE007
              _lowerCAmelCase       :   List[str]  =    chr(_A      )
              # Now we test that we can change the value of additional_special_tokens in the from_pretrained
              _lowerCAmelCase       :   Optional[Any]  =    [AddedToken(_A    ,lstrip=_A      )]
              _lowerCAmelCase       :   str  =    tokenizer_class.from_pretrained(
                  _A    ,additional_special_tokens=_A    ,extra_ids=0      )

              self.assertIn(_A    ,tokenizer.additional_special_tokens      )
              # self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
              self.assertEqual(
                  [new_token_a]    ,tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]      )      )      )

  @require_tokenizers
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Tuple  =    self.get_tokenizers(do_lower_case=_A      )
      for tokenizer in tokenizers:
          with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
              _lowerCAmelCase       :   str  =    'hello world'
              if self.space_between_special_tokens:
                  _lowerCAmelCase       :   Optional[Any]  =    '[CLS] hello world [SEP]'
              else:
                  _lowerCAmelCase       :   Optional[Any]  =    input
              _lowerCAmelCase       :   Union[str, Any]  =    tokenizer.encode(_A    ,add_special_tokens=_A      )
              _lowerCAmelCase       :   Tuple  =    tokenizer.decode(_A    ,spaces_between_special_tokens=self.space_between_special_tokens      )
              self.assertIn(_A    ,[output, output.lower()]      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

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

      _lowerCAmelCase       :   Union[str, Any]  =    'a'
      _lowerCAmelCase       :   List[str]  =    ord(_A      )

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

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

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

      _lowerCAmelCase       :   List[Any]  =    0xE006
      _lowerCAmelCase       :   Any  =    chr(_A      )
      setattr(_A    ,'additional_special_tokens_ids'    ,[additional_special_token_id]      )
      self.assertListEqual(getattr(_A    ,'additional_special_tokens'      )    ,[additional_special_token]      )
      self.assertListEqual(getattr(_A    ,'additional_special_tokens_ids'      )    ,[additional_special_token_id]      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      pass

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      pass

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      pass

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      pass

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      pass

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      pass

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      pass







  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      pass








"""simple docstring"""






import baseaa

def 		lowerCamelCase__		(					_lowerCamelCase   ):

    '''simple docstring'''



    return baseaa.aaaencode(string.encode('utf-8'   )   )

def 		lowerCamelCase__		(					_lowerCamelCase   ):

    '''simple docstring'''



    return baseaa.aaadecode(_lowerCamelCase   ).decode('utf-8'   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()





