



'''simple docstring'''





import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / '''utils'''))

from test_module.custom_configuration import CustomConfig  # noqa E402


_lowerCAmelCase      						=	get_tests_dir('''fixtures/dummy-config.json''')






class        lowerCAmelCase_(				unittest.TestCase     ):
  '''simple docstring'''




  def 							UpperCAmelCase_	(    self      )    ->		Optional[int]:
      lowerCAmelCase__ :  Any							      =					0




  def 							UpperCAmelCase_	(    self      )    ->		List[Any]:
      self.assertIsNotNone(transformers.models.auto.__spec__      )
      self.assertIsNotNone(importlib.util.find_spec("""transformers.models.auto"""      )      )




  def 							UpperCAmelCase_	(    self      )    ->		List[str]:
      lowerCAmelCase__ :  Dict							      =					AutoConfig.from_pretrained("""bert-base-uncased"""      )
      self.assertIsInstance(__UpperCAmelCase  ,__UpperCAmelCase      )




  def 							UpperCAmelCase_	(    self      )    ->		Optional[int]:
      lowerCAmelCase__ :  Optional[Any]							      =					AutoConfig.from_pretrained(__UpperCAmelCase      )
      self.assertIsInstance(__UpperCAmelCase  ,__UpperCAmelCase      )




  def 							UpperCAmelCase_	(    self      )    ->		Optional[Any]:
      lowerCAmelCase__ :  Tuple							      =					AutoConfig.from_pretrained(__UpperCAmelCase      )
      self.assertIsInstance(__UpperCAmelCase  ,__UpperCAmelCase      )




  def 							UpperCAmelCase_	(    self      )    ->		Union[str, Any]:
      lowerCAmelCase__ :  Optional[Any]							      =					AutoConfig.for_model("""roberta"""      )
      self.assertIsInstance(__UpperCAmelCase  ,__UpperCAmelCase      )




  def 							UpperCAmelCase_	(    self      )    ->		List[Any]:
      with tempfile.TemporaryDirectory() as tmp_dir:
          # This model name contains bert and roberta, but roberta ends up being picked.
          lowerCAmelCase__ :  List[str]							      =					os.path.join(__UpperCAmelCase  ,"""fake-roberta"""      )
          os.makedirs(__UpperCAmelCase  ,exist_ok=__UpperCAmelCase      )
          with open(os.path.join(__UpperCAmelCase  ,"""config.json"""      )  ,"""w"""      ) as f:
              f.write(json.dumps({}      )      )
          lowerCAmelCase__ :  int							      =					AutoConfig.from_pretrained(__UpperCAmelCase      )
          self.assertEqual(type(__UpperCAmelCase      )  ,__UpperCAmelCase      )




  def 							UpperCAmelCase_	(    self      )    ->		Optional[Any]:
      try:
          AutoConfig.register("""custom"""  ,__UpperCAmelCase      )
          # Wrong model type will raise an error
          with self.assertRaises(__UpperCAmelCase      ):
              AutoConfig.register("""model"""  ,__UpperCAmelCase      )
          # Trying to register something existing in the Transformers library will raise an error
          with self.assertRaises(__UpperCAmelCase      ):
              AutoConfig.register("""bert"""  ,__UpperCAmelCase      )

          # Now that the config is registered, it can be used as any other config with the auto-API
          lowerCAmelCase__ :  Any							      =					CustomConfig()
          with tempfile.TemporaryDirectory() as tmp_dir:
              config.save_pretrained(__UpperCAmelCase      )
              lowerCAmelCase__ :  int							      =					AutoConfig.from_pretrained(__UpperCAmelCase      )
              self.assertIsInstance(__UpperCAmelCase  ,__UpperCAmelCase      )

      finally:
          if "custom" in CONFIG_MAPPING._extra_content:
              del CONFIG_MAPPING._extra_content["custom"]




  def 							UpperCAmelCase_	(    self      )    ->		List[Any]:
      with self.assertRaisesRegex(
          __UpperCAmelCase  ,"""bert-base is not a local folder and is not a valid model identifier"""      ):
          lowerCAmelCase__ :  List[Any]							      =					AutoConfig.from_pretrained("""bert-base"""      )




  def 							UpperCAmelCase_	(    self      )    ->		List[str]:
      with self.assertRaisesRegex(
          __UpperCAmelCase  ,R"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""      ):
          lowerCAmelCase__ :  str							      =					AutoConfig.from_pretrained(__UpperCAmelCase  ,revision="""aaaaaa"""      )




  def 							UpperCAmelCase_	(    self      )    ->		Dict:
      with self.assertRaisesRegex(
          __UpperCAmelCase  ,"""hf-internal-testing/no-config-test-repo does not appear to have a file named config.json."""  ,):
          lowerCAmelCase__ :  List[Any]							      =					AutoConfig.from_pretrained("""hf-internal-testing/no-config-test-repo"""      )




  def 							UpperCAmelCase_	(    self      )    ->		List[str]:
      # If remote code is not set, we will time out when asking whether to load the model.
      with self.assertRaises(__UpperCAmelCase      ):
          lowerCAmelCase__ :  Optional[int]							      =					AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""      )
      # If remote code is disabled, we can't load this config.
      with self.assertRaises(__UpperCAmelCase      ):
          lowerCAmelCase__ :  List[str]							      =					AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""  ,trust_remote_code=__UpperCAmelCase      )

      lowerCAmelCase__ :  Union[str, Any]							      =					AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""  ,trust_remote_code=__UpperCAmelCase      )
      self.assertEqual(config.__class__.__name__  ,"""NewModelConfig"""      )

      # Test config can be reloaded.
      with tempfile.TemporaryDirectory() as tmp_dir:
          config.save_pretrained(__UpperCAmelCase      )
          lowerCAmelCase__ :  Optional[int]							      =					AutoConfig.from_pretrained(__UpperCAmelCase  ,trust_remote_code=__UpperCAmelCase      )
      self.assertEqual(reloaded_config.__class__.__name__  ,"""NewModelConfig"""      )






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






      class        lowerCAmelCase_(				SCREAMING_SNAKE_CASE_     ):
        '''simple docstring'''




        __lowercase							:      Union[str, Any]				=      '''new-model'''

      try:
          AutoConfig.register("""new-model"""  ,__UpperCAmelCase      )
          # If remote code is not set, the default is to use local
          lowerCAmelCase__ :  Union[str, Any]							      =					AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""      )
          self.assertEqual(config.__class__.__name__  ,"""NewModelConfigLocal"""      )

          # If remote code is disabled, we load the local one.
          lowerCAmelCase__ :  List[str]							      =					AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""  ,trust_remote_code=__UpperCAmelCase      )
          self.assertEqual(config.__class__.__name__  ,"""NewModelConfigLocal"""      )

          # If remote is enabled, we load from the Hub
          lowerCAmelCase__ :  str							      =					AutoConfig.from_pretrained("""hf-internal-testing/test_dynamic_model"""  ,trust_remote_code=__UpperCAmelCase      )
          self.assertEqual(config.__class__.__name__  ,"""NewModelConfig"""      )

      finally:
          if "new-model" in CONFIG_MAPPING._extra_content:
              del CONFIG_MAPPING._extra_content["new-model"]




'''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


__lowerCAmelCase         =    logging.get_logger(__name__)

__lowerCAmelCase         =    """▁"""

__lowerCAmelCase         =    {"""vocab_file""": """sentencepiece.bpe.model""", """monolingual_vocab_file""": """dict.txt"""}

__lowerCAmelCase         =    {
    """vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model""",
    },
    """monolingual_vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt""",
    },
}

__lowerCAmelCase         =    {"""vinai/bartpho-syllable""": 1_0_2_4}







class UpperCAmelCase__	( lowercase__	):





  """simple docstring"""

  __UpperCAmelCase				:				Optional[Any]   =					VOCAB_FILES_NAMES
  __UpperCAmelCase				:				Dict   =					PRETRAINED_VOCAB_FILES_MAP
  __UpperCAmelCase				:				Optional[int]   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __UpperCAmelCase				:				Dict   =					['''input_ids''', '''attention_mask''']


  def __init__(		self      :     str							,_a      :     str							,_a      :     Any							,_a      :     Any="<s>"							,_a      :     Dict="</s>"							,_a      :     int="</s>"							,_a      :     Union[str, Any]="<s>"							,_a      :     List[Any]="<unk>"							,_a      :     Optional[Any]="<pad>"							,_a      :     List[str]="<mask>"							,_a      :     Optional[Dict[str, Any]] = None							,**_a      :     int							,):


     '''simple docstring'''






     _a				:	Any			=   AddedToken(_a							,lstrip=_a							,rstrip=_a       ) if isinstance(_a							,_a       ) else mask_token

     _a				:	Optional[Any]			=   {} if sp_model_kwargs is None else sp_model_kwargs

     super().__init__(
         bos_token=_a							,eos_token=_a							,unk_token=_a							,sep_token=_a							,cls_token=_a							,pad_token=_a							,mask_token=_a							,sp_model_kwargs=self.sp_model_kwargs							,**_a							,)

     _a				:	Optional[int]			=   vocab_file
     _a				:	Union[str, Any]			=   monolingual_vocab_file
     _a				:	List[Any]			=   spm.SentencePieceProcessor(**self.sp_model_kwargs       )
     self.sp_model.Load(str(_a       )       )

     # Load the reduced vocab

     # Keep order of special tokens for backward compatibility
     _a				:	Union[str, Any]			=   {}
     _a				:	int			=   0
     for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
        if str(_a       ) not in self.fairseq_tokens_to_ids:
           _a				:	int			=   cnt
           cnt += 1
     with open(_a							,'r'							,encoding='utf-8'       ) as f:
        for line in f.readlines():
           _a				:	str			=   line.strip().split()[0]
           _a				:	Tuple			=   len(self.fairseq_tokens_to_ids       )
     if str(_a       ) not in self.fairseq_tokens_to_ids:
        _a				:	List[str]			=   len(self.fairseq_tokens_to_ids       )

     _a				:	Tuple			=   {v: k for k, v in self.fairseq_tokens_to_ids.items()}


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


     '''simple docstring'''






     _a				:	int			=   self.__dict__.copy()
     _a				:	str			=   None
     _a				:	Optional[Any]			=   self.sp_model.serialized_model_proto()
     return state


  def __setstate__(		self      :     Tuple							,_a      :     Tuple       ):


     '''simple docstring'''






     _a				:	Tuple			=   d

     # for backward compatibility
     if not hasattr(self							,'sp_model_kwargs'       ):
        _a				:	List[str]			=   {}

     _a				:	List[Any]			=   spm.SentencePieceProcessor(**self.sp_model_kwargs       )
     self.sp_model.LoadFromSerializedProto(self.sp_model_proto       )


  def   __lowercase		(		self      :     Dict							,_a      :     List[int]							,_a      :     Optional[List[int]] = None       ):


     '''simple docstring'''






     if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
     _a				:	Dict			=   [self.cls_token_id]
     _a				:	int			=   [self.sep_token_id]
     return cls + token_ids_a + sep + sep + token_ids_a + sep


  def   __lowercase		(		self      :     int							,_a      :     List[int]							,_a      :     Optional[List[int]] = None							,_a      :     bool = False       ):


     '''simple docstring'''






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

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


  def   __lowercase		(		self      :     Tuple							,_a      :     List[int]							,_a      :     Optional[List[int]] = None       ):


     '''simple docstring'''






     _a				:	List[str]			=   [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]


  @property
  def   __lowercase		(		self      :     Dict       ):


     '''simple docstring'''






     return len(self.fairseq_ids_to_tokens       )


  def   __lowercase		(		self      :     Dict       ):


     '''simple docstring'''






     _a				:	List[str]			=   {self.convert_ids_to_tokens(_a       ): i for i in range(self.vocab_size       )}
     vocab.update(self.added_tokens_encoder       )
     return vocab


  def   __lowercase		(		self      :     Tuple							,_a      :     str       ):


     '''simple docstring'''






     return self.sp_model.encode(_a							,out_type=_a       )


  def   __lowercase		(		self      :     Union[str, Any]							,_a      :     Union[str, Any]       ):


     '''simple docstring'''






     if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
     else:
        return self.unk_token_id


  def   __lowercase		(		self      :     Any							,_a      :     int       ):


     '''simple docstring'''






     return self.fairseq_ids_to_tokens[index]


  def   __lowercase		(		self      :     Tuple							,_a      :     Union[str, Any]       ):


     '''simple docstring'''






     _a				:	str			=   ''.join(_a       ).replace(_a							,' '       ).strip()
     return out_string


  def   __lowercase		(		self      :     Union[str, Any]							,_a      :     str							,_a      :     Optional[str] = None       ):


     '''simple docstring'''






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

     if os.path.abspath(self.vocab_file       ) != os.path.abspath(_a       ) and os.path.isfile(self.vocab_file       ):
        copyfile(self.vocab_file							,_a       )
     elif not os.path.isfile(self.vocab_file       ):
        with open(_a							,'wb'       ) as fi:
           _a				:	List[Any]			=   self.sp_model.serialized_model_proto()
           fi.write(_a       )

     if os.path.abspath(self.monolingual_vocab_file       ) != os.path.abspath(
         _a       ) and os.path.isfile(self.monolingual_vocab_file       ):
        copyfile(self.monolingual_vocab_file							,_a       )
     elif not os.path.isfile(self.monolingual_vocab_file       ):
        with open(_a							,'w'							,encoding='utf-8'       ) as fp:
           for token in self.fairseq_tokens_to_ids:
              if token not in self.all_special_tokens:
                 fp.write(F"""{str(_a       )} \n"""       )

     return out_vocab_file, out_monolingual_vocab_file



