


'''simple docstring'''



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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


A__						:   int				=    logging.get_logger(__name__)

A__						:   str				=    {"""vocab_file""": """sentencepiece.bpe.model"""}

A__						:   int				=    {
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    }
}

A__						:   Tuple				=    {
    """camembert-base""": 512,
}

A__						:   Any				=    """▁"""





class   UpperCAmelCase_    (A__    ):





    """simple docstring"""






    lowerCamelCase    :   Tuple					=     VOCAB_FILES_NAMES
    lowerCamelCase    :   List[Any]					=     PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase    :   Tuple					=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase    :   List[Any]					=     ['input_ids', 'attention_mask']







    def __init__(				self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_="<s>"     ,	SCREAMING_SNAKE_CASE_="</s>"     ,	SCREAMING_SNAKE_CASE_="</s>"     ,	SCREAMING_SNAKE_CASE_="<s>"     ,	SCREAMING_SNAKE_CASE_="<unk>"     ,	SCREAMING_SNAKE_CASE_="<pad>"     ,	SCREAMING_SNAKE_CASE_="<mask>"     ,	SCREAMING_SNAKE_CASE_=["<s>NOTUSED", "</s>NOTUSED"]     ,	SCREAMING_SNAKE_CASE_ = None     ,	**SCREAMING_SNAKE_CASE_     ,	)							->	Any:
         __lowerCamelCase  :      Optional[Any]														=						AddedToken(_lowerCamelCase     ,	lstrip=_lowerCamelCase     ,	rstrip=_lowerCamelCase      ) if isinstance(_lowerCamelCase     ,	_lowerCamelCase      ) else mask_token

         __lowerCamelCase  :      List[str]														=						{} if sp_model_kwargs is None else sp_model_kwargs

         super().__init__(
             bos_token=_lowerCamelCase     ,	eos_token=_lowerCamelCase     ,	unk_token=_lowerCamelCase     ,	sep_token=_lowerCamelCase     ,	cls_token=_lowerCamelCase     ,	pad_token=_lowerCamelCase     ,	mask_token=_lowerCamelCase     ,	additional_special_tokens=_lowerCamelCase     ,	sp_model_kwargs=self.sp_model_kwargs     ,	**_lowerCamelCase     ,	)
         __lowerCamelCase  :      Optional[int]														=						spm.SentencePieceProcessor(**self.sp_model_kwargs      )
         self.sp_model.Load(str(_lowerCamelCase      )      )
         __lowerCamelCase  :      str														=						vocab_file
         # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
         # sentencepiece vocabulary (this is the case for <s> and </s>
         __lowerCamelCase  :      Tuple														=						{'<s>NOTUSED': 0, '<pad>': 1, '</s>NOTUSED': 2, '<unk>': 3}
         __lowerCamelCase  :      List[str]														=						len(self.fairseq_tokens_to_ids      )
         __lowerCamelCase  :      List[str]														=						len(self.sp_model      ) + len(self.fairseq_tokens_to_ids      )
         __lowerCamelCase  :      Any														=						{v: k for k, v in self.fairseq_tokens_to_ids.items()}







    def  lowercase_							(				self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_ = None      )							->	List[Any]:



         if token_ids_a is None:
              return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         __lowerCamelCase  :      Any														=						[self.cls_token_id]
         __lowerCamelCase  :      str														=						[self.sep_token_id]
         return cls + token_ids_a + sep + sep + token_ids_a + sep







    def  lowercase_							(				self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_ = None     ,	SCREAMING_SNAKE_CASE_ = False      )							->	Optional[Any]:



         if already_has_special_tokens:
              return super().get_special_tokens_mask(
                  token_ids_a=_lowerCamelCase     ,	token_ids_a=_lowerCamelCase     ,	already_has_special_tokens=_lowerCamelCase      )

         if token_ids_a is None:
              return [1] + ([0] * len(_lowerCamelCase      )) + [1]
         return [1] + ([0] * len(_lowerCamelCase      )) + [1, 1] + ([0] * len(_lowerCamelCase      )) + [1]







    def  lowercase_							(				self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_ = None      )							->	Union[str, Any]:
         __lowerCamelCase  :      Union[str, Any]														=						[self.sep_token_id]
         __lowerCamelCase  :      Dict														=						[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]







    @property
    def  lowercase_							(				self      )							->	Union[str, Any]:
         return len(self.fairseq_tokens_to_ids      ) + len(self.sp_model      )







    def  lowercase_							(				self      )							->	Union[str, Any]:
         __lowerCamelCase  :      Optional[Any]														=						{self.convert_ids_to_tokens(_lowerCamelCase      ): i for i in range(self.vocab_size      )}
         vocab.update(self.added_tokens_encoder      )
         return vocab







    def  lowercase_							(				self     ,	SCREAMING_SNAKE_CASE_      )							->	int:
         return self.sp_model.encode(_lowerCamelCase     ,	out_type=_lowerCamelCase      )







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



         if token in self.fairseq_tokens_to_ids:
              return self.fairseq_tokens_to_ids[token]
         elif self.sp_model.PieceToId(_lowerCamelCase      ) == 0:
              # Convert sentence piece unk token to fairseq unk token index
              return self.unk_token_id
         return self.fairseq_offset + self.sp_model.PieceToId(_lowerCamelCase      )







    def  lowercase_							(				self     ,	SCREAMING_SNAKE_CASE_      )							->	Optional[int]:



         if index in self.fairseq_ids_to_tokens:
              return self.fairseq_ids_to_tokens[index]
         return self.sp_model.IdToPiece(index - self.fairseq_offset      )







    def  lowercase_							(				self     ,	SCREAMING_SNAKE_CASE_      )							->	Optional[Any]:
         __lowerCamelCase  :      int														=						[]
         __lowerCamelCase  :      Optional[Any]														=						''
         __lowerCamelCase  :      Optional[Any]														=						False
         for token in tokens:
              # make sure that special tokens are not decoded using sentencepiece model
              if token in self.all_special_tokens:
                   if not prev_is_special:
                        out_string += " "
                   out_string += self.sp_model.decode(_lowerCamelCase      ) + token
                   __lowerCamelCase  :      Union[str, Any]														=						True
                   __lowerCamelCase  :      Optional[Any]														=						[]
              else:
                   current_sub_tokens.append(_lowerCamelCase      )
                   __lowerCamelCase  :      Any														=						False
         out_string += self.sp_model.decode(_lowerCamelCase      )
         return out_string.strip()







    def __getstate__(				self      )							->	Tuple:
         __lowerCamelCase  :      List[Any]														=						self.__dict__.copy()
         __lowerCamelCase  :      str														=						None
         return state







    def __setstate__(				self     ,	SCREAMING_SNAKE_CASE_      )							->	Union[str, Any]:
         __lowerCamelCase  :      str														=						d

         # for backward compatibility
         if not hasattr(self     ,	'sp_model_kwargs'      ):
              __lowerCamelCase  :      Any														=						{}

         __lowerCamelCase  :      List[Any]														=						spm.SentencePieceProcessor(**self.sp_model_kwargs      )
         self.sp_model.Load(self.vocab_file      )







    def  lowercase_							(				self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_ = None      )							->	str:



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

         if os.path.abspath(self.vocab_file      ) != os.path.abspath(_lowerCamelCase      ) and os.path.isfile(self.vocab_file      ):
              copyfile(self.vocab_file     ,	_lowerCamelCase      )
         elif not os.path.isfile(self.vocab_file      ):
              with open(_lowerCamelCase     ,	'wb'      ) as fi:
                   __lowerCamelCase  :      int														=						self.sp_model.serialized_model_proto()
                   fi.write(_lowerCamelCase      )

         return (out_vocab_file,)








"""simple docstring"""






import copy
import tempfile
import unittest

from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError

from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test





class 				a__					(						unittest.TestCase       ):



     @parameterized.expand([(None,), ('foo.json',)]   )
     def  lowerCamelCase_						(							self :Union[str, Any]      ,  _lowerCamelCase :Any   ):







      '''simple docstring'''



      UpperCamelCase_     :					str   	=GenerationConfig(
          do_sample=_lowerCamelCase      ,  temperature=0.7      ,  length_penalty=1.0      ,  bad_words_ids=[[1, 2, 3], [4, 5]]      ,  )
      with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(_lowerCamelCase      ,  config_name=_lowerCamelCase   )
       UpperCamelCase_     :					Union[str, Any]   	=GenerationConfig.from_pretrained(_lowerCamelCase      ,  config_name=_lowerCamelCase   )

      # Checks parameters that were specified
      self.assertEqual(loaded_config.do_sample      ,  _lowerCamelCase   )
      self.assertEqual(loaded_config.temperature      ,  0.7   )
      self.assertEqual(loaded_config.length_penalty      ,  1.0   )
      self.assertEqual(loaded_config.bad_words_ids      ,  [[1, 2, 3], [4, 5]]   )

      # Checks parameters that were not specified (defaults)
      self.assertEqual(loaded_config.top_k      ,  50   )
      self.assertEqual(loaded_config.max_length      ,  20   )
      self.assertEqual(loaded_config.max_time      ,  _lowerCamelCase   )



     def  lowerCamelCase_						(							self :Optional[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Optional[int]   	=AutoConfig.from_pretrained('gpt2'   )
      UpperCamelCase_     :					Tuple   	=GenerationConfig.from_model_config(_lowerCamelCase   )
      UpperCamelCase_     :					Optional[int]   	=GenerationConfig()

      # The generation config has loaded a few non-default parameters from the model config
      self.assertNotEqual(_lowerCamelCase      ,  _lowerCamelCase   )

      # One of those parameters is eos_token_id -- check if it matches
      self.assertNotEqual(generation_config_from_model.eos_token_id      ,  default_generation_config.eos_token_id   )
      self.assertEqual(generation_config_from_model.eos_token_id      ,  model_config.eos_token_id   )



     def  lowerCamelCase_						(							self :Tuple   ):







      '''simple docstring'''



      UpperCamelCase_     :					str   	=GenerationConfig()
      UpperCamelCase_     :					Optional[Any]   	={
          'max_new_tokens': 1_024,
          'foo': 'bar',
      }
      UpperCamelCase_     :					Optional[Any]   	=copy.deepcopy(_lowerCamelCase   )
      UpperCamelCase_     :					Optional[int]   	=generation_config.update(**_lowerCamelCase   )

      # update_kwargs was not modified (no side effects)
      self.assertEqual(_lowerCamelCase      ,  _lowerCamelCase   )

      # update_kwargs was used to update the config on valid attributes
      self.assertEqual(generation_config.max_new_tokens      ,  1_024   )

      # `.update()` returns a dictionary of unused kwargs
      self.assertEqual(_lowerCamelCase      ,  {'foo': 'bar'}   )



     def  lowerCamelCase_						(							self :Union[str, Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Union[str, Any]   	=GenerationConfig()
      UpperCamelCase_     :					Union[str, Any]   	='bar'

      with tempfile.TemporaryDirectory('test-generation-config'   ) as tmp_dir:
       generation_config.save_pretrained(_lowerCamelCase   )

       UpperCamelCase_     :					Dict   	=GenerationConfig.from_pretrained(_lowerCamelCase   )
      # update_kwargs was used to update the config on valid attributes
      self.assertEqual(new_config.foo      ,  'bar'   )

      UpperCamelCase_     :					List[str]   	=GenerationConfig.from_model_config(_lowerCamelCase   )
      assert not hasattr(_lowerCamelCase      ,  'foo'   )  # no new kwargs should be initialized if from config




     def  lowerCamelCase_						(							self :Optional[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[str]   	=GenerationConfig()
      self.assertEqual(default_config.temperature      ,  1.0   )
      self.assertEqual(default_config.do_sample      ,  _lowerCamelCase   )
      self.assertEqual(default_config.num_beams      ,  1   )

      UpperCamelCase_     :					Tuple   	=GenerationConfig(
          do_sample=_lowerCamelCase      ,  temperature=0.7      ,  length_penalty=1.0      ,  bad_words_ids=[[1, 2, 3], [4, 5]]      ,  )
      self.assertEqual(config.temperature      ,  0.7   )
      self.assertEqual(config.do_sample      ,  _lowerCamelCase   )
      self.assertEqual(config.num_beams      ,  1   )

      with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(_lowerCamelCase   )
       UpperCamelCase_     :					str   	=GenerationConfig.from_pretrained(_lowerCamelCase      ,  temperature=1.0   )

      self.assertEqual(loaded_config.temperature      ,  1.0   )
      self.assertEqual(loaded_config.do_sample      ,  _lowerCamelCase   )
      self.assertEqual(loaded_config.num_beams      ,  1   )  # default value





@is_staging_test
class 				a__					(						unittest.TestCase       ):



     @classmethod
     def  lowerCamelCase_						(							cls :Optional[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Dict   	=TOKEN
      HfFolder.save_token(_lowerCamelCase   )



     @classmethod
     def  lowerCamelCase_						(							cls :List[Any]   ):







      '''simple docstring'''



      try:
       delete_repo(token=cls._token      ,  repo_id='test-generation-config'   )
      except HTTPError:
       pass

      try:
       delete_repo(token=cls._token      ,  repo_id='valid_org/test-generation-config-org'   )
      except HTTPError:
       pass



     def  lowerCamelCase_						(							self :List[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[str]   	=GenerationConfig(
          do_sample=_lowerCamelCase      ,  temperature=0.7      ,  length_penalty=1.0      ,  )
      config.push_to_hub('test-generation-config'      ,  use_auth_token=self._token   )

      UpperCamelCase_     :					List[Any]   	=GenerationConfig.from_pretrained(f'''{USER}/test-generation-config'''   )
      for k, v in config.to_dict().items():
       if k != "transformers_version":
        self.assertEqual(_lowerCamelCase      ,  getattr(_lowerCamelCase      ,  _lowerCamelCase   )   )

        # Reset repo
      delete_repo(token=self._token      ,  repo_id='test-generation-config'   )

      # Push to hub via save_pretrained
      with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(
           _lowerCamelCase      ,  repo_id='test-generation-config'      ,  push_to_hub=_lowerCamelCase      ,  use_auth_token=self._token   )

      UpperCamelCase_     :					Any   	=GenerationConfig.from_pretrained(f'''{USER}/test-generation-config'''   )
      for k, v in config.to_dict().items():
       if k != "transformers_version":
        self.assertEqual(_lowerCamelCase      ,  getattr(_lowerCamelCase      ,  _lowerCamelCase   )   )




     def  lowerCamelCase_						(							self :Union[str, Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Union[str, Any]   	=GenerationConfig(
          do_sample=_lowerCamelCase      ,  temperature=0.7      ,  length_penalty=1.0      ,  )
      config.push_to_hub('valid_org/test-generation-config-org'      ,  use_auth_token=self._token   )

      UpperCamelCase_     :					int   	=GenerationConfig.from_pretrained('valid_org/test-generation-config-org'   )
      for k, v in config.to_dict().items():
       if k != "transformers_version":
        self.assertEqual(_lowerCamelCase      ,  getattr(_lowerCamelCase      ,  _lowerCamelCase   )   )

        # Reset repo
      delete_repo(token=self._token      ,  repo_id='valid_org/test-generation-config-org'   )

      # Push to hub via save_pretrained
      with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(
           _lowerCamelCase      ,  repo_id='valid_org/test-generation-config-org'      ,  push_to_hub=_lowerCamelCase      ,  use_auth_token=self._token   )

      UpperCamelCase_     :					Optional[Any]   	=GenerationConfig.from_pretrained('valid_org/test-generation-config-org'   )
      for k, v in config.to_dict().items():
       if k != "transformers_version":
        self.assertEqual(_lowerCamelCase      ,  getattr(_lowerCamelCase      ,  _lowerCamelCase   )   )
