


import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class       __magic_name__	(     __lowerCAmelCase					,				unittest.TestCase):
     A:		Optional[int]			=      BarthezTokenizer
     A:		Optional[int]			=      BarthezTokenizerFast
     A:		str			=      True
     A:		Optional[int]			=      True


     def      UpperCAmelCase__	(      self							:     List[Any]			)  ->      str:





      '''simple docstring'''






      super().setUp()

      UpperCamelCase__					:    Optional[Any]          =   BarthezTokenizerFast.from_pretrained('''moussaKam/mbarthez'''			)
      tokenizer.save_pretrained(self.tmpdirname			)
      tokenizer.save_pretrained(self.tmpdirname							,	legacy_format=lowerCamelCase__			)
      UpperCamelCase__					:    int          =   tokenizer


     def      UpperCAmelCase__	(      self							:     Union[str, Any]			)  ->      str:





      '''simple docstring'''






      UpperCamelCase__					:    Optional[int]          =   '''<pad>'''
      UpperCamelCase__					:    List[str]          =   1

      self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase__			)							,	lowerCamelCase__			)
      self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase__			)							,	lowerCamelCase__			)


     def      UpperCAmelCase__	(      self							:     int			)  ->      Tuple:





      '''simple docstring'''






      UpperCamelCase__					:    int          =   list(self.get_tokenizer().get_vocab().keys()			)

      self.assertEqual(vocab_keys[0]							,	'''<s>'''			)
      self.assertEqual(vocab_keys[1]							,	'''<pad>'''			)
      self.assertEqual(vocab_keys[-1]							,	'''<mask>'''			)
      self.assertEqual(len(lowerCamelCase__			)							,	101122			)


     def      UpperCAmelCase__	(      self							:     Optional[Any]			)  ->      str:





      '''simple docstring'''






      self.assertEqual(self.get_tokenizer().vocab_size							,	101122			)


     @require_torch
     def      UpperCAmelCase__	(      self							:     Dict			)  ->      Tuple:





      '''simple docstring'''






      UpperCamelCase__					:    Dict          =   ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
      UpperCamelCase__					:    Any          =   [0, 57, 3018, 70307, 91, 2]

      UpperCamelCase__					:    Optional[int]          =   self.tokenizer(
          lowerCamelCase__							,	max_length=len(lowerCamelCase__			)							,	padding=lowerCamelCase__							,	truncation=lowerCamelCase__							,	return_tensors='''pt'''			)
      self.assertIsInstance(lowerCamelCase__							,	lowerCamelCase__			)

      self.assertEqual((2, 6)							,	batch.input_ids.shape			)
      self.assertEqual((2, 6)							,	batch.attention_mask.shape			)
      UpperCamelCase__					:    List[Any]          =   batch.input_ids.tolist()[0]
      self.assertListEqual(lowerCamelCase__							,	lowerCamelCase__			)


     def      UpperCAmelCase__	(      self							:     str			)  ->      List[Any]:





      '''simple docstring'''






      if not self.test_rust_tokenizer:
       return

      UpperCamelCase__					:    List[Any]          =   self.get_tokenizer()
      UpperCamelCase__					:    Optional[int]          =   self.get_rust_tokenizer()

      UpperCamelCase__					:    Any          =   '''I was born in 92000, and this is falsé.'''

      UpperCamelCase__					:    List[str]          =   tokenizer.tokenize(lowerCamelCase__			)
      UpperCamelCase__					:    Tuple          =   rust_tokenizer.tokenize(lowerCamelCase__			)
      self.assertListEqual(lowerCamelCase__							,	lowerCamelCase__			)

      UpperCamelCase__					:    Tuple          =   tokenizer.encode(lowerCamelCase__							,	add_special_tokens=lowerCamelCase__			)
      UpperCamelCase__					:    str          =   rust_tokenizer.encode(lowerCamelCase__							,	add_special_tokens=lowerCamelCase__			)
      self.assertListEqual(lowerCamelCase__							,	lowerCamelCase__			)

      UpperCamelCase__					:    Tuple          =   self.get_rust_tokenizer()
      UpperCamelCase__					:    Optional[int]          =   tokenizer.encode(lowerCamelCase__			)
      UpperCamelCase__					:    str          =   rust_tokenizer.encode(lowerCamelCase__			)
      self.assertListEqual(lowerCamelCase__							,	lowerCamelCase__			)


     @slow
     def      UpperCAmelCase__	(      self							:     List[str]			)  ->      Dict:





      '''simple docstring'''






      UpperCamelCase__					:    Optional[int]          =   {'''input_ids''': [[0, 490, 14328, 4507, 354, 47, 43669, 95, 25, 78117, 20215, 19779, 190, 22, 400, 4, 35343, 80310, 603, 86, 24937, 105, 33438, 94762, 196, 39642, 7, 15, 15933, 173, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 10534, 87, 25, 66, 3358, 196, 55289, 8, 82961, 81, 2204, 75203, 7, 15, 763, 12956, 216, 178, 14328, 9595, 1377, 69693, 7, 448, 71021, 196, 18106, 1437, 13974, 108, 9083, 4, 49315, 7, 39, 86, 1326, 2793, 46333, 4, 448, 196, 74588, 7, 49315, 7, 39, 21, 822, 38470, 74, 21, 66723, 62480, 8, 22050, 5, 2]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
      # fmt: on

      # moussaKam/mbarthez is a french model. So we also use french texts.
      UpperCamelCase__					:    int          =   [
          '''Le transformeur est un modèle d\'apprentissage profond introduit en 2017, '''
          '''utilisé principalement dans le domaine du traitement automatique des langues (TAL).''',
          '''À l\'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus '''
          '''pour gérer des données séquentielles, telles que le langage naturel, pour des tâches '''
          '''telles que la traduction et la synthèse de texte.''',
      ]

      self.tokenizer_integration_test_util(
          expected_encoding=lowerCamelCase__							,	model_name='''moussaKam/mbarthez'''							,	revision='''c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'''							,	sequences=lowerCamelCase__							,	)






import logging
import os
import threading
import time


try:
       import warnings
except ImportError:
       __UpperCamelCase       :       Any						       =				None

try:
       import msvcrt
except ImportError:
       __UpperCamelCase       :       Optional[Any]						       =				None

try:
       import fcntl
except ImportError:
       __UpperCamelCase       :       Union[str, Any]						       =				None


# Backward compatibility
# ------------------------------------------------
try:
       TimeoutError
except NameError:
       __UpperCamelCase       :       Any						       =				OSError


# Data
# ------------------------------------------------
__UpperCamelCase       :       Optional[int]						       =				[
    "Timeout",
    "BaseFileLock",
    "WindowsFileLock",
    "UnixFileLock",
    "SoftFileLock",
    "FileLock",
]

__UpperCamelCase       :       Dict						       =				"3.0.12"


__UpperCamelCase       :       str						       =				None

def 			_a  (				):







 """simple docstring"""



 global _logger
 UpperCamelCase__					:    Tuple          =   _logger or logging.getLogger(__name__     )
 return _logger

class       __magic_name__	(     __lowerCAmelCase):


     def __init__(      self							:     Any							,	lowerCamelCase__							:     List[Any]			)  ->      int:





      '''simple docstring'''






      UpperCamelCase__					:    List[str]          =   lock_file
      return None


     def __str__(      self							:     Optional[int]			)  ->      Union[str, Any]:





      '''simple docstring'''






      UpperCamelCase__					:    Tuple          =   F"The file lock '{self.lock_file}' could not be acquired."
      return temp



class       __magic_name__	:


     def __init__(      self							:     List[str]							,	lowerCamelCase__							:     Dict			)  ->      Optional[int]:





      '''simple docstring'''






      UpperCamelCase__					:    Optional[int]          =   lock
      return None


     def __enter__(      self							:     Tuple			)  ->      str:





      '''simple docstring'''






      return self.lock


     def __exit__(      self							:     Any							,	lowerCamelCase__							:     List[Any]							,	lowerCamelCase__							:     Dict							,	lowerCamelCase__							:     str			)  ->      Any:





      '''simple docstring'''






      self.lock.release()
      return None



class       __magic_name__	:


     def __init__(      self							:     List[Any]							,	lowerCamelCase__							:     int							,	lowerCamelCase__							:     List[str]=-1							,	lowerCamelCase__							:     Any=None			)  ->      Optional[Any]:





      '''simple docstring'''






      UpperCamelCase__					:    int          =   max_filename_length if max_filename_length is not None else 255
      # Hash the filename if it's too long
      UpperCamelCase__					:    List[Any]          =   self.hash_filename_if_too_long(lowerCamelCase__							,	lowerCamelCase__			)
      # The path to the lock file.
      UpperCamelCase__					:    Tuple          =   lock_file

      # The file descriptor for the *_lock_file* as it is returned by the
      # os.open() function.
      # This file lock is only NOT None, if the object currently holds the
      # lock.
      UpperCamelCase__					:    int          =   None

      # The default timeout value.
      UpperCamelCase__					:    Optional[Any]          =   timeout

      # We use this lock primarily for the lock counter.
      UpperCamelCase__					:    List[Any]          =   threading.Lock()

      # The lock counter is used for implementing the nested locking
      # mechanism. Whenever the lock is acquired, the counter is increased and
      # the lock is only released, when this value is 0 again.
      UpperCamelCase__					:    Any          =   0
      return None


     @property
     def      UpperCAmelCase__	(      self							:     Any			)  ->      Optional[int]:





      '''simple docstring'''






      return self._lock_file


     @property
     def      UpperCAmelCase__	(      self							:     Optional[int]			)  ->      Optional[int]:





      '''simple docstring'''






      return self._timeout


     @timeout.setter
     def      UpperCAmelCase__	(      self							:     List[Any]							,	lowerCamelCase__							:     Any			)  ->      List[str]:





      '''simple docstring'''






      UpperCamelCase__					:    List[str]          =   float(lowerCamelCase__			)
      return None


     def      UpperCAmelCase__	(      self							:     Any			)  ->      Optional[Any]:





      '''simple docstring'''






      raise NotImplementedError()


     def      UpperCAmelCase__	(      self							:     List[str]			)  ->      Dict:





      '''simple docstring'''






      raise NotImplementedError()


     @property
     def      UpperCAmelCase__	(      self							:     Any			)  ->      Dict:





      '''simple docstring'''






      return self._lock_file_fd is not None


     def      UpperCAmelCase__	(      self							:     Tuple							,	lowerCamelCase__							:     Optional[Any]=None							,	lowerCamelCase__							:     List[str]=0.05			)  ->      int:





      '''simple docstring'''






      if timeout is None:
       UpperCamelCase__					:    int          =   self.timeout

      # Increment the number right at the beginning.
      # We can still undo it, if something fails.
      with self._thread_lock:
       self._lock_counter += 1

      UpperCamelCase__					:    int          =   id(self			)
      UpperCamelCase__					:    List[Any]          =   self._lock_file
      UpperCamelCase__					:    Dict          =   time.time()
      try:
       while True:
        with self._thread_lock:
         if not self.is_locked:
          logger().debug(F"Attempting to acquire lock {lock_id} on {lock_filename}"			)
          self._acquire()

        if self.is_locked:
         logger().debug(F"Lock {lock_id} acquired on {lock_filename}"			)
         break
        elif timeout >= 0 and time.time() - start_time > timeout:
         logger().debug(F"Timeout on acquiring lock {lock_id} on {lock_filename}"			)
         raise Timeout(self._lock_file			)
        else:
         logger().debug(
             F"Lock {lock_id} not acquired on {lock_filename}, waiting {poll_intervall} seconds ..."			)
         time.sleep(lowerCamelCase__			)
      except:  # noqa
       # Something did go wrong, so decrement the counter.
       with self._thread_lock:
        UpperCamelCase__					:    List[Any]          =   max(0							,	self._lock_counter - 1			)

       raise
      return _Acquire_ReturnProxy(lock=self			)


     def      UpperCAmelCase__	(      self							:     Optional[int]							,	lowerCamelCase__							:     Optional[int]=False			)  ->      Any:





      '''simple docstring'''






      with self._thread_lock:
       if self.is_locked:
        self._lock_counter -= 1

        if self._lock_counter == 0 or force:
         UpperCamelCase__					:    List[str]          =   id(self			)
         UpperCamelCase__					:    Union[str, Any]          =   self._lock_file

         logger().debug(F"Attempting to release lock {lock_id} on {lock_filename}"			)
         self._release()
         UpperCamelCase__					:    Optional[Any]          =   0
         logger().debug(F"Lock {lock_id} released on {lock_filename}"			)

      return None


     def __enter__(      self							:     Union[str, Any]			)  ->      Tuple:





      '''simple docstring'''






      self.acquire()
      return self


     def __exit__(      self							:     Optional[int]							,	lowerCamelCase__							:     List[str]							,	lowerCamelCase__							:     Any							,	lowerCamelCase__							:     Any			)  ->      Optional[Any]:





      '''simple docstring'''






      self.release()
      return None


     def __del__(      self							:     Optional[Any]			)  ->      List[str]:





      '''simple docstring'''






      self.release(force=lowerCamelCase__			)
      return None


     def      UpperCAmelCase__	(      self							:     Optional[int]							,	lowerCamelCase__							:     str							,	lowerCamelCase__							:     int			)  ->      str:





      '''simple docstring'''






      UpperCamelCase__					:    str          =   os.path.basename(lowerCamelCase__			)
      if len(lowerCamelCase__			) > max_length and max_length > 0:
       UpperCamelCase__					:    Optional[int]          =   os.path.dirname(lowerCamelCase__			)
       UpperCamelCase__					:    List[str]          =   str(hash(lowerCamelCase__			)			)
       UpperCamelCase__					:    Optional[int]          =   filename[: max_length - len(lowerCamelCase__			) - 8] + '''...''' + hashed_filename + '''.lock'''
       return os.path.join(lowerCamelCase__							,	lowerCamelCase__			)
      else:
       return path



class       __magic_name__	(     __lowerCAmelCase):


     def __init__(      self							:     int							,	lowerCamelCase__							:     Dict							,	lowerCamelCase__							:     str=-1							,	lowerCamelCase__							:     int=None			)  ->      Optional[int]:





      '''simple docstring'''






      from .file_utils import relative_to_absolute_path

      super().__init__(lowerCamelCase__							,	timeout=lowerCamelCase__							,	max_filename_length=lowerCamelCase__			)
      UpperCamelCase__					:    int          =   '''\\\\?\\''' + relative_to_absolute_path(self.lock_file			)


     def      UpperCAmelCase__	(      self							:     Optional[Any]			)  ->      Union[str, Any]:





      '''simple docstring'''






      UpperCamelCase__					:    List[Any]          =   os.O_RDWR | os.O_CREAT | os.O_TRUNC

      try:
       UpperCamelCase__					:    Union[str, Any]          =   os.open(self._lock_file							,	lowerCamelCase__			)
      except OSError:
       pass
      else:
       try:
        msvcrt.locking(lowerCamelCase__							,	msvcrt.LK_NBLCK							,	1			)
       except OSError:
        os.close(lowerCamelCase__			)
       else:
        UpperCamelCase__					:    Union[str, Any]          =   fd
      return None


     def      UpperCAmelCase__	(      self							:     Tuple			)  ->      Optional[Any]:





      '''simple docstring'''






      UpperCamelCase__					:    str          =   self._lock_file_fd
      UpperCamelCase__					:    List[str]          =   None
      msvcrt.locking(lowerCamelCase__							,	msvcrt.LK_UNLCK							,	1			)
      os.close(lowerCamelCase__			)

      try:
       os.remove(self._lock_file			)
      # Probably another instance of the application
      # that acquired the file lock.
      except OSError:
       pass
      return None



class       __magic_name__	(     __lowerCAmelCase):


     def __init__(      self							:     Any							,	lowerCamelCase__							:     int							,	lowerCamelCase__							:     str=-1							,	lowerCamelCase__							:     int=None			)  ->      Tuple:





      '''simple docstring'''






      UpperCamelCase__					:    Union[str, Any]          =   os.statvfs(os.path.dirname(lowerCamelCase__			)			).f_namemax
      super().__init__(lowerCamelCase__							,	timeout=lowerCamelCase__							,	max_filename_length=lowerCamelCase__			)


     def      UpperCAmelCase__	(      self							:     int			)  ->      Optional[int]:





      '''simple docstring'''






      UpperCamelCase__					:    List[str]          =   os.O_RDWR | os.O_CREAT | os.O_TRUNC
      UpperCamelCase__					:    int          =   os.open(self._lock_file							,	lowerCamelCase__			)

      try:
       fcntl.flock(lowerCamelCase__							,	fcntl.LOCK_EX | fcntl.LOCK_NB			)
      except OSError:
       os.close(lowerCamelCase__			)
      else:
       UpperCamelCase__					:    Any          =   fd
      return None


     def      UpperCAmelCase__	(      self							:     int			)  ->      Any:





      '''simple docstring'''






      UpperCamelCase__					:    Tuple          =   self._lock_file_fd
      UpperCamelCase__					:    int          =   None
      fcntl.flock(lowerCamelCase__							,	fcntl.LOCK_UN			)
      os.close(lowerCamelCase__			)
      return None



class       __magic_name__	(     __lowerCAmelCase):


     def      UpperCAmelCase__	(      self							:     Optional[Any]			)  ->      List[Any]:





      '''simple docstring'''






      UpperCamelCase__					:    str          =   os.O_WRONLY | os.O_CREAT | os.O_EXCL | os.O_TRUNC
      try:
       UpperCamelCase__					:    Any          =   os.open(self._lock_file							,	lowerCamelCase__			)
      except OSError:
       pass
      else:
       UpperCamelCase__					:    Optional[Any]          =   fd
      return None


     def      UpperCAmelCase__	(      self							:     Optional[Any]			)  ->      Optional[Any]:





      '''simple docstring'''






      os.close(self._lock_file_fd			)
      UpperCamelCase__					:    List[str]          =   None

      try:
       os.remove(self._lock_file			)
      # The file is already deleted and that's what we want.
      except OSError:
       pass
      return None



__UpperCamelCase       :       Tuple						       =				None

if msvcrt:
       __UpperCamelCase       :       str						       =				WindowsFileLock
elif fcntl:
       __UpperCamelCase       :       Optional[Any]						       =				UnixFileLock
else:
       __UpperCamelCase       :       Optional[Any]						       =				SoftFileLock

       if warnings is not None:
              warnings.warn("only soft file lock is available")


