

'''simple docstring'''


import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


snake_case  : Union[str, Any]					    =	logging.get_logger(__name__)


snake_case  : Optional[Any]					    =	{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

# See all BART models at https://huggingface.co/models?filter=bart
snake_case  : Dict					    =	{
    '''vocab_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/vocab.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/vocab.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/merges.txt''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/merges.txt''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json''',
    },
}

snake_case  : Tuple					    =	{
    '''facebook/bart-base''': 1_024,
    '''facebook/bart-large''': 1_024,
    '''facebook/bart-large-mnli''': 1_024,
    '''facebook/bart-large-cnn''': 1_024,
    '''facebook/bart-large-xsum''': 1_024,
    '''yjernite/bart_eli5''': 1_024,
}




class 					lowerCamelCase__(    __lowerCAmelCase		):
 UpperCamelCase			:						Union[str, Any]   							=       VOCAB_FILES_NAMES
 UpperCamelCase			:						int   							=       PRETRAINED_VOCAB_FILES_MAP
 UpperCamelCase			:						Optional[Any]   							=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCamelCase			:						Any   							=       ["""input_ids""", """attention_mask"""]
 UpperCamelCase			:						str   							=       BartTokenizer

 def __init__(      self			,							__UpperCAmelCase=None			,							__UpperCAmelCase=None			,							__UpperCAmelCase=None			,							__UpperCAmelCase="replace"			,							__UpperCAmelCase="<s>"			,							__UpperCAmelCase="</s>"			,							__UpperCAmelCase="</s>"			,							__UpperCAmelCase="<s>"			,							__UpperCAmelCase="<unk>"			,							__UpperCAmelCase="<pad>"			,							__UpperCAmelCase="<mask>"			,							__UpperCAmelCase=False			,							__UpperCAmelCase=True			,							**__UpperCAmelCase			,							):



    """simple docstring"""







    super().__init__(
        _SCREAMING_SNAKE_CASE			,							_SCREAMING_SNAKE_CASE			,							tokenizer_file=_SCREAMING_SNAKE_CASE			,							errors=_SCREAMING_SNAKE_CASE			,							bos_token=_SCREAMING_SNAKE_CASE			,							eos_token=_SCREAMING_SNAKE_CASE			,							sep_token=_SCREAMING_SNAKE_CASE			,							cls_token=_SCREAMING_SNAKE_CASE			,							unk_token=_SCREAMING_SNAKE_CASE			,							pad_token=_SCREAMING_SNAKE_CASE			,							mask_token=_SCREAMING_SNAKE_CASE			,							add_prefix_space=_SCREAMING_SNAKE_CASE			,							trim_offsets=_SCREAMING_SNAKE_CASE			,							**_SCREAMING_SNAKE_CASE			,							)

    __lowercase							      =				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
    if pre_tok_state.get("""add_prefix_space"""			,							_SCREAMING_SNAKE_CASE	) != add_prefix_space:
       __lowercase							      =				getattr(_SCREAMING_SNAKE_CASE			,							pre_tok_state.pop("""type"""	)	)
       __lowercase							      =				add_prefix_space
       __lowercase							      =				pre_tok_class(**_SCREAMING_SNAKE_CASE	)

    __lowercase							      =				add_prefix_space

    # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
    __lowercase							      =				"""post_processor"""
    __lowercase							      =				getattr(self.backend_tokenizer			,							_SCREAMING_SNAKE_CASE			,							_SCREAMING_SNAKE_CASE	)
    if tokenizer_component_instance:
       __lowercase							      =				json.loads(tokenizer_component_instance.__getstate__()	)

       # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
       if "sep" in state:
          __lowercase							      =				tuple(state["""sep"""]	)
       if "cls" in state:
          __lowercase							      =				tuple(state["""cls"""]	)

       __lowercase							      =				False

       if state.get("""add_prefix_space"""			,							_SCREAMING_SNAKE_CASE	) != add_prefix_space:
          __lowercase							      =				add_prefix_space
          __lowercase							      =				True

       if state.get("""trim_offsets"""			,							_SCREAMING_SNAKE_CASE	) != trim_offsets:
          __lowercase							      =				trim_offsets
          __lowercase							      =				True

       if changes_to_apply:
          __lowercase							      =				getattr(_SCREAMING_SNAKE_CASE			,							state.pop("""type"""	)	)
          __lowercase							      =				component_class(**_SCREAMING_SNAKE_CASE	)
          setattr(self.backend_tokenizer			,							_SCREAMING_SNAKE_CASE			,							_SCREAMING_SNAKE_CASE	)

 @property
 def   __magic_name__						(      self	):



    """simple docstring"""







    if self._mask_token is None:
       if self.verbose:
          logger.error("""Using mask_token, but it is not set yet."""	)
       return None
    return str(self._mask_token	)

 @mask_token.setter
 def   __magic_name__						(      self			,							__UpperCAmelCase	):



    """simple docstring"""







    __lowercase							      =				AddedToken(_SCREAMING_SNAKE_CASE			,							lstrip=_SCREAMING_SNAKE_CASE			,							rstrip=_SCREAMING_SNAKE_CASE	) if isinstance(_SCREAMING_SNAKE_CASE			,							_SCREAMING_SNAKE_CASE	) else value
    __lowercase							      =				value

 def   __magic_name__						(      self			,							*__UpperCAmelCase			,							**__UpperCAmelCase	):



    """simple docstring"""







    __lowercase							      =				kwargs.get("""is_split_into_words"""			,							_SCREAMING_SNAKE_CASE	)

    if is_split_into_words and not self.add_prefix_space:
       raise ValueError(
           F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
           """to use it with pretokenized inputs."""	)

    return super()._batch_encode_plus(*_SCREAMING_SNAKE_CASE			,							**_SCREAMING_SNAKE_CASE	)

 def   __magic_name__						(      self			,							*__UpperCAmelCase			,							**__UpperCAmelCase	):



    """simple docstring"""







    __lowercase							      =				kwargs.get("""is_split_into_words"""			,							_SCREAMING_SNAKE_CASE	)

    if is_split_into_words and not self.add_prefix_space:
       raise ValueError(
           F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
           """to use it with pretokenized inputs."""	)

    return super()._encode_plus(*_SCREAMING_SNAKE_CASE			,							**_SCREAMING_SNAKE_CASE	)

 def   __magic_name__						(      self			,							__UpperCAmelCase			,							__UpperCAmelCase = None	):



    """simple docstring"""







    __lowercase							      =				self._tokenizer.model.save(_SCREAMING_SNAKE_CASE			,							name=_SCREAMING_SNAKE_CASE	)
    return tuple(_SCREAMING_SNAKE_CASE	)

 def   __magic_name__						(      self			,							__UpperCAmelCase			,							__UpperCAmelCase=None	):



    """simple docstring"""







    __lowercase							      =				[self.bos_token_id] + token_ids_a + [self.eos_token_id]
    if token_ids_a is None:
       return output

    return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




 def   __magic_name__						(      self			,							__UpperCAmelCase			,							__UpperCAmelCase = None	):



    """simple docstring"""







    __lowercase							      =				[self.sep_token_id]
    __lowercase							      =				[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]









'''simple docstring'''





import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
UpperCamelCase_		:     Optional[int]          =		object()

# For specifying empty leaf dict `{}`
UpperCamelCase_		:     Optional[int]          =		object()





def       __a      (  _UpperCamelCase:       Union[str, Any]   ,		_UpperCamelCase:       Optional[Any]       )		->					Optional[Any]:

     """simple docstring"""




     _snake_case				= tuple((re.compile(x + "$"       ) for x in qs)       )
     for i in range(len(_UpperCamelCase       ) - len(_UpperCamelCase       ) + 1       ):
          _snake_case				= [x.match(_UpperCamelCase       ) for x, y in zip(_UpperCamelCase   ,		ks[i:]       )]
          if matches and all(_UpperCamelCase       ):
               return True
     return False





def       __a      (  _UpperCamelCase:       Optional[Any]       )		->					Union[str, Any]:

     """simple docstring"""




     def replace(_UpperCamelCase:       Tuple   ,		_UpperCamelCase:       List[str]       ):
          for rule, replacement in rules:
               if _match(_UpperCamelCase   ,		_UpperCamelCase       ):
                    return replacement
          return val

     return replace





def       __a      (  )		->					Any:

     """simple docstring"""




     return [
         # embeddings
         (("transformer", "wpe", "embedding"), P("mp"   ,		_UpperCamelCase       )),
         (("transformer", "wte", "embedding"), P("mp"   ,		_UpperCamelCase       )),
         # atention
         (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(_UpperCamelCase   ,		"mp"       )),
         (("attention", "out_proj", "kernel"), P("mp"   ,		_UpperCamelCase       )),
         (("attention", "out_proj", "bias"), None),
         # mlp
         (("mlp", "c_fc", "kernel"), P(_UpperCamelCase   ,		"mp"       )),
         (("mlp", "c_fc", "bias"), P("mp"       )),
         (("mlp", "c_proj", "kernel"), P("mp"   ,		_UpperCamelCase       )),
         (("mlp", "c_proj", "bias"), None),
         # layer norms
         ((r"ln_\d+", "bias"), None),
         ((r"\d+", r"ln_\d+", "scale"), None),
         (("ln_f", "bias"), None),
         (("ln_f", "scale"), None),
     ]





def       __a      (  _UpperCamelCase:       Union[str, Any]       )		->					Any:

     """simple docstring"""




     _snake_case				= _get_partition_rules()
     _snake_case				= _replacement_rules(_UpperCamelCase       )
     _snake_case				= {k: _unmatched for k in flatten_dict(_UpperCamelCase       )}
     _snake_case				= {k: replace(_UpperCamelCase   ,		_UpperCamelCase       ) for k, v in initd.items()}
     assert _unmatched not in result.values(), "Incomplete partition spec."
     return freeze(unflatten_dict(_UpperCamelCase       )       )


