


import inspect
import os
import re

from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
snake_case    :   Tuple	    =					'''src/transformers'''


# This is to make sure the transformers module imported is the one in the repo.
snake_case    :   Tuple	    =					direct_transformers_import(PATH_TO_TRANSFORMERS)

snake_case    :   Dict	    =					transformers.models.auto.configuration_auto.CONFIG_MAPPING

snake_case    :   Dict	    =					{
    # used to compute the property `self.chunk_length`
    '''EncodecConfig''': ['''overlap'''],
    # used as `self.bert_model = BertModel(config, ...)`
    '''DPRConfig''': True,
    # not used in modeling files, but it's an important information
    '''FSMTConfig''': ['''langs'''],
    # used internally in the configuration class file
    '''GPTNeoConfig''': ['''attention_types'''],
    # used internally in the configuration class file
    '''EsmConfig''': ['''is_folding_model'''],
    # used during training (despite we don't have training script for these models yet)
    '''Mask2FormerConfig''': ['''ignore_value'''],
    # `ignore_value` used during training (despite we don't have training script for these models yet)
    # `norm` used in conversion script (despite not using in the modeling file)
    '''OneFormerConfig''': ['''ignore_value''', '''norm'''],
    # used during preprocessing and collation, see `collating_graphormer.py`
    '''GraphormerConfig''': ['''spatial_pos_max'''],
    # used internally in the configuration class file
    '''T5Config''': ['''feed_forward_proj'''],
    # used internally in the configuration class file
    # `tokenizer_class` get default value `T5Tokenizer` intentionally
    '''MT5Config''': ['''feed_forward_proj''', '''tokenizer_class'''],
    '''UMT5Config''': ['''feed_forward_proj''', '''tokenizer_class'''],
    # used internally in the configuration class file
    '''LongT5Config''': ['''feed_forward_proj'''],
    # used internally in the configuration class file
    '''SwitchTransformersConfig''': ['''feed_forward_proj'''],
    # having default values other than `1e-5` - we can't fix them without breaking
    '''BioGptConfig''': ['''layer_norm_eps'''],
    # having default values other than `1e-5` - we can't fix them without breaking
    '''GLPNConfig''': ['''layer_norm_eps'''],
    # having default values other than `1e-5` - we can't fix them without breaking
    '''SegformerConfig''': ['''layer_norm_eps'''],
    # having default values other than `1e-5` - we can't fix them without breaking
    '''CvtConfig''': ['''layer_norm_eps'''],
    # having default values other than `1e-5` - we can't fix them without breaking
    '''PerceiverConfig''': ['''layer_norm_eps'''],
    # used internally to calculate the feature size
    '''InformerConfig''': ['''num_static_real_features''', '''num_time_features'''],
    # used internally to calculate the feature size
    '''TimeSeriesTransformerConfig''': ['''num_static_real_features''', '''num_time_features'''],
    # used internally to calculate the feature size
    '''AutoformerConfig''': ['''num_static_real_features''', '''num_time_features'''],
    # used internally to calculate `mlp_dim`
    '''SamVisionConfig''': ['''mlp_ratio'''],
    # For (head) training, but so far not implemented
    '''ClapAudioConfig''': ['''num_classes'''],
    # Not used, but providing useful information to users
    '''SpeechT5HifiGanConfig''': ['''sampling_rate'''],
}


# TODO (ydshieh): Check the failing cases, try to fix them or move some cases to the above block once we are sure
SPECIAL_CASES_TO_ALLOW.update(
    {
        '''CLIPSegConfig''': True,
        '''DeformableDetrConfig''': True,
        '''DetaConfig''': True,
        '''DinatConfig''': True,
        '''DonutSwinConfig''': True,
        '''EfficientFormerConfig''': True,
        '''FSMTConfig''': True,
        '''JukeboxConfig''': True,
        '''LayoutLMv2Config''': True,
        '''MaskFormerSwinConfig''': True,
        '''MT5Config''': True,
        '''NatConfig''': True,
        '''OneFormerConfig''': True,
        '''PerceiverConfig''': True,
        '''RagConfig''': True,
        '''SpeechT5Config''': True,
        '''SwinConfig''': True,
        '''Swin2SRConfig''': True,
        '''Swinv2Config''': True,
        '''SwitchTransformersConfig''': True,
        '''TableTransformerConfig''': True,
        '''TapasConfig''': True,
        '''TransfoXLConfig''': True,
        '''UniSpeechConfig''': True,
        '''UniSpeechSatConfig''': True,
        '''WavLMConfig''': True,
        '''WhisperConfig''': True,
        # TODO: @Arthur (for `alignment_head` and `alignment_layer`)
        '''JukeboxPriorConfig''': True,
        # TODO: @Younes (for `is_decoder`)
        '''Pix2StructTextConfig''': True,
    }
)
def     __lowerCamelCase						(			UpperCAmelCase_						:		List[str]			,  UpperCAmelCase_						:		int			,  UpperCAmelCase_						:		Optional[int]			,  UpperCAmelCase_						:		List[Any]						):




      """simple docstring"""





      a						:Optional[int]										=	False
      for attribute in attributes:
            for modeling_source in source_strings:
                  # check if we can find `config.xxx`, `getattr(config, "xxx", ...)` or `getattr(self.config, "xxx", ...)`
                  if (
                      F'''config.{attribute}''' in modeling_source
                      or F'''getattr(config, "{attribute}"''' in modeling_source
                      or F'''getattr(self.config, "{attribute}"''' in modeling_source
                  ):
                        a						:List[Any]										=	True
                  # Deal with multi-line cases
                  elif (
                      re.search(
                          RF'''getattr[ \t\v\n\r\f]*\([ \t\v\n\r\f]*(self\.)?config,[ \t\v\n\r\f]*"{attribute}"'''			,  UpperCAmelCase_			,  )
                      is not None
                  ):
                        a						:Dict										=	True
                  # `SequenceSummary` is called with `SequenceSummary(config)`
                  elif attribute in [
                      "summary_type",
                      "summary_use_proj",
                      "summary_activation",
                      "summary_last_dropout",
                      "summary_proj_to_labels",
                      "summary_first_dropout",
                  ]:
                        if "SequenceSummary" in modeling_source:
                              a						:str										=	True
                  if attribute_used:
                        break
            if attribute_used:
                  break

            # common and important attributes, even if they do not always appear in the modeling files
      a						:Union[str, Any]										=	[
          '''bos_index''',
          '''eos_index''',
          '''pad_index''',
          '''unk_index''',
          '''mask_index''',
          '''image_size''',
          '''use_cache''',
          '''out_features''',
          '''out_indices''',
      ]
      a						:Union[str, Any]										=	['''encoder_no_repeat_ngram_size''']

      # Special cases to be allowed
      a						:Any										=	True
      if not attribute_used:
            a						:Union[str, Any]										=	False
            for attribute in attributes:
                  # Allow if the default value in the configuration class is different from the one in `PretrainedConfig`
                  if attribute in ["is_encoder_decoder"] and default_value is True:
                        a						:Optional[int]										=	True
                  elif attribute in ["tie_word_embeddings"] and default_value is False:
                        a						:int										=	True

                  # Allow cases without checking the default value in the configuration class
                  elif attribute in attributes_to_allow + attributes_used_in_generation:
                        a						:Any										=	True
                  elif attribute.endswith('''_token_id'''						):
                        a						:Dict										=	True

                  # configuration class specific cases
                  if not case_allowed:
                        a						:str										=	SPECIAL_CASES_TO_ALLOW.get(config_class.__name__			,  []						)
                        a						:Tuple										=	allowed_cases is True or attribute in allowed_cases

      return attribute_used or case_allowed
def     __lowerCamelCase						(			UpperCAmelCase_						:		int						):




      """simple docstring"""





      a						:Any										=	dict(inspect.signature(config_class.__init__						).parameters						)
      a						:List[Any]										=	[x for x in list(signature.keys()						) if x not in ['''self''', '''kwargs''']]
      a						:Dict										=	[signature[param].default for param in parameter_names]

      # If `attribute_map` exists, an attribute can have different names to be used in the modeling files, and as long
      # as one variant is used, the test should pass
      a						:List[str]										=	{}
      if len(config_class.attribute_map						) > 0:
            a						:str										=	{v: k for k, v in config_class.attribute_map.items()}

      # Get the path to modeling source files
      a						:List[str]										=	inspect.getsourcefile(UpperCAmelCase_						)
      a						:Dict										=	os.path.dirname(UpperCAmelCase_						)
      # Let's check against all frameworks: as long as one framework uses an attribute, we are good.
      a						:Tuple										=	[os.path.join(UpperCAmelCase_			,  UpperCAmelCase_						) for fn in os.listdir(UpperCAmelCase_						) if fn.startswith('''modeling_'''						)]

      # Get the source code strings
      a						:List[str]										=	[]
      for path in modeling_paths:
            if os.path.isfile(UpperCAmelCase_						):
                  with open(UpperCAmelCase_						) as fp:
                        modeling_sources.append(fp.read()						)

      a						:Optional[Any]										=	[]
      for config_param, default_value in zip(UpperCAmelCase_			,  UpperCAmelCase_						):
            # `attributes` here is all the variant names for `config_param`
            a						:List[str]										=	[config_param]
            # some configuration classes have non-empty `attribute_map`, and both names could be used in the
            # corresponding modeling files. As long as one of them appears, it is fine.
            if config_param in reversed_attribute_map:
                  attributes.append(reversed_attribute_map[config_param]						)

            if not check_attribute_being_used(UpperCAmelCase_			,  UpperCAmelCase_			,  UpperCAmelCase_			,  UpperCAmelCase_						):
                  unused_attributes.append(attributes[0]						)

      return sorted(UpperCAmelCase_						)
def     __lowerCamelCase						(			):




      """simple docstring"""





      a						:Optional[Any]										=	{}
      for _config_class in list(CONFIG_MAPPING.values()						):
            # Skip deprecated models
            if "models.deprecated" in _config_class.__module__:
                  continue
            # Some config classes are not in `CONFIG_MAPPING` (e.g. `CLIPVisionConfig`, `Blip2VisionConfig`, etc.)
            a						:Optional[int]										=	[
                cls
                for name, cls in inspect.getmembers(
                    inspect.getmodule(_config_class						)			,  lambda UpperCAmelCase_						: inspect.isclass(UpperCAmelCase_						)
                    and issubclass(UpperCAmelCase_			,  UpperCAmelCase_						)
                    and inspect.getmodule(UpperCAmelCase_						) == inspect.getmodule(_config_class						)			,  )
            ]
            for config_class in config_classes_in_module:
                  a						:Union[str, Any]										=	check_config_attributes_being_used(UpperCAmelCase_						)
                  if len(UpperCAmelCase_						) > 0:
                        a						:Tuple										=	unused_attributes

      if len(UpperCAmelCase_						) > 0:
            a						:Dict										=	'''The following configuration classes contain unused attributes in the corresponding modeling files:\n'''
            for name, attributes in configs_with_unused_attributes.items():
                  error += F'''{name}: {attributes}\n'''

            raise ValueError(UpperCAmelCase_						)


if __name__ == "__main__":
     check_config_attributes()









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

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


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

snake_case    :   Optional[Any]	    =					{
    '''vocab_file''': '''vocab.txt''',
    '''merges_file''': '''bpe.codes''',
}

snake_case    :   str	    =					{
    '''vocab_file''': {
        '''vinai/phobert-base''': '''https://huggingface.co/vinai/phobert-base/resolve/main/vocab.txt''',
        '''vinai/phobert-large''': '''https://huggingface.co/vinai/phobert-large/resolve/main/vocab.txt''',
    },
    '''merges_file''': {
        '''vinai/phobert-base''': '''https://huggingface.co/vinai/phobert-base/resolve/main/bpe.codes''',
        '''vinai/phobert-large''': '''https://huggingface.co/vinai/phobert-large/resolve/main/bpe.codes''',
    },
}

snake_case    :   List[Any]	    =					{
    '''vinai/phobert-base''': 2_56,
    '''vinai/phobert-large''': 2_56,
}
def     __lowerCamelCase						(			UpperCAmelCase_						:		List[str]						):




      """simple docstring"""





      a						:Union[str, Any]										=	set()
      a						:str										=	word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)						)
            a						:Optional[int]										=	char

      a						:Optional[int]										=	set(UpperCAmelCase_						)
      return pairs







class 		_snake_case  (				_snake_case							):
 SCREAMING_SNAKE_CASE__				=	VOCAB_FILES_NAMES
 SCREAMING_SNAKE_CASE__				=	PRETRAINED_VOCAB_FILES_MAP
 SCREAMING_SNAKE_CASE__				=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




 def __init__(		self ,  _lowerCamelCase ,  _lowerCamelCase ,  _lowerCamelCase="<s>" ,  _lowerCamelCase="</s>" ,  _lowerCamelCase="</s>" ,  _lowerCamelCase="<s>" ,  _lowerCamelCase="<unk>" ,  _lowerCamelCase="<pad>" ,  _lowerCamelCase="<mask>" ,  **_lowerCamelCase ,  ):
       super().__init__(
           bos_token=_lowerCamelCase ,  eos_token=_lowerCamelCase ,  unk_token=_lowerCamelCase ,  sep_token=_lowerCamelCase ,  cls_token=_lowerCamelCase ,  pad_token=_lowerCamelCase ,  mask_token=_lowerCamelCase ,  **_lowerCamelCase ,  )

       a						:Optional[Any]										=	vocab_file
       a						:Optional[Any]										=	merges_file

       a						:Any										=	{}
       a						:Any										=	0
       a						:int										=	1
       a						:Union[str, Any]										=	2
       a						:List[Any]										=	3

       self.add_from_file(_lowerCamelCase   )

       a						:List[str]										=	{v: k for k, v in self.encoder.items()}

       with open(_lowerCamelCase ,  encoding='''utf-8'''   ) as merges_handle:
             a						:List[str]										=	merges_handle.read().split('''\n'''   )[:-1]
       a						:Any										=	[tuple(merge.split()[:-1]   ) for merge in merges]
       a						:str										=	dict(zip(_lowerCamelCase ,  range(len(_lowerCamelCase   )   )   )   )
       a						:str										=	{}




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase ,  _lowerCamelCase = None   ):

       if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       a						:Union[str, Any]										=	[self.cls_token_id]
       a						:Tuple										=	[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase ,  _lowerCamelCase = None ,  _lowerCamelCase = False   ):

       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 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase ,  _lowerCamelCase = None   ):
       a						:Optional[int]										=	[self.sep_token_id]
       a						:Optional[Any]										=	[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 	SCREAMING_SNAKE_CASE__    (		self   ):
       return len(self.encoder   )




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       return dict(self.encoder ,  **self.added_tokens_encoder   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       if token in self.cache:
             return self.cache[token]
       a						:Optional[int]										=	tuple(_lowerCamelCase   )
       a						:List[str]										=	tuple(list(word[:-1]   ) + [word[-1] + '''</w>''']   )
       a						:Union[str, Any]										=	get_pairs(_lowerCamelCase   )

       if not pairs:
             return token

       while True:
             a						:Optional[Any]										=	min(_lowerCamelCase ,  key=lambda _lowerCamelCase   : self.bpe_ranks.get(_lowerCamelCase ,  float('''inf'''   )   )   )
             if bigram not in self.bpe_ranks:
                   break
             a							,    a						:Dict										=	bigram
             a						:Union[str, Any]										=	[]
             a						:int										=	0
             while i < len(_lowerCamelCase   ):
                   try:
                         a						:Optional[Any]										=	word.index(_lowerCamelCase ,  _lowerCamelCase   )
                   except ValueError:
                         new_word.extend(word[i:]   )
                         break
                   else:
                         new_word.extend(word[i:j]   )
                         a						:Union[str, Any]										=	j

                   if word[i] == first and i < len(_lowerCamelCase   ) - 1 and word[i + 1] == second:
                         new_word.append(first + second   )
                         i += 2
                   else:
                         new_word.append(word[i]   )
                         i += 1
             a						:Union[str, Any]										=	tuple(_lowerCamelCase   )
             a						:int										=	new_word
             if len(_lowerCamelCase   ) == 1:
                   break
             else:
                   a						:List[str]										=	get_pairs(_lowerCamelCase   )
       a						:Union[str, Any]										=	'''@@ '''.join(_lowerCamelCase   )
       a						:Dict										=	word[:-4]
       a						:Any										=	word
       return word




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       a						:Union[str, Any]										=	[]

       a						:str										=	re.findall(R'''\S+\n?''' ,  _lowerCamelCase   )

       for token in words:
             split_tokens.extend(list(self.bpe(_lowerCamelCase   ).split(''' '''   )   )   )
       return split_tokens




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       return self.encoder.get(_lowerCamelCase ,  self.encoder.get(self.unk_token   )   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       return self.decoder.get(_lowerCamelCase ,  self.unk_token   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       a						:Optional[int]										=	''' '''.join(_lowerCamelCase   ).replace('''@@ ''' ,  ''''''   ).strip()
       return out_string




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase ,  _lowerCamelCase = None   ):
       if not os.path.isdir(_lowerCamelCase   ):
             logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''   )
             return
       a						:Tuple										=	os.path.join(
           _lowerCamelCase ,  (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )
       a						:Optional[int]										=	os.path.join(
           _lowerCamelCase ,  (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']   )

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

       if os.path.abspath(self.merges_file   ) != os.path.abspath(_lowerCamelCase   ):
             copyfile(self.merges_file ,  _lowerCamelCase   )

       return out_vocab_file, out_merge_file




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       if isinstance(_lowerCamelCase ,  _lowerCamelCase   ):
             try:
                   with open(_lowerCamelCase ,  '''r''' ,  encoding='''utf-8'''   ) as fd:
                         self.add_from_file(_lowerCamelCase   )
             except FileNotFoundError as fnfe:
                   raise fnfe
             except UnicodeError:
                   raise Exception(F'''Incorrect encoding detected in {f}, please rebuild the dataset'''   )
             return

       a						:str										=	f.readlines()
       for lineTmp in lines:
             a						:Tuple										=	lineTmp.strip()
             a						:int										=	line.rfind(''' '''   )
             if idx == -1:
                   raise ValueError('''Incorrect dictionary format, expected \'<token> <cnt>\''''   )
             a						:Tuple										=	line[:idx]
             a						:Tuple										=	len(self.encoder   )





