



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_024}
class 				lowercase__       (   UpperCamelCase__				):







       '''simple docstring'''


       UpperCamelCase						=					VOCAB_FILES_NAMES
       UpperCamelCase						=					PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase						=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCamelCase						=					['''input_ids''', '''attention_mask''']



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


             '''simple docstring'''




             UpperCAmelCase_      			=							AddedToken(__lowerCamelCase		,    lstrip=__lowerCamelCase		,    rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase		,    __lowerCamelCase   ) else mask_token

             UpperCAmelCase_      			=							{} 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		,    sp_model_kwargs=self.sp_model_kwargs		,    **__lowerCamelCase		,    )

             UpperCAmelCase_      			=							vocab_file
             UpperCAmelCase_      			=							monolingual_vocab_file
             UpperCAmelCase_      			=							spm.SentencePieceProcessor(**self.sp_model_kwargs   )
             self.sp_model.Load(str(__lowerCamelCase   )   )

             # Load the reduced vocab

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

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



       def __getstate__(							self      :  str   )			->						int:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.__dict__.copy()
             UpperCAmelCase_      			=							None
             UpperCAmelCase_      			=							self.sp_model.serialized_model_proto()
             return state



       def __setstate__(							self      :  Dict		,    _UpperCAmelCase      :  List[str]   )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							d

             # for backward compatibility
             if not hasattr(self		,    "sp_model_kwargs"   ):
                   UpperCAmelCase_      			=							{}

             UpperCAmelCase_      			=							spm.SentencePieceProcessor(**self.sp_model_kwargs   )
             self.sp_model.LoadFromSerializedProto(self.sp_model_proto   )



       def 					lowercase__    (							self      :  List[Any]		,    _UpperCAmelCase      :  Union[str, Any]		,    _UpperCAmelCase      :  str = None   )			->						Optional[Any]:


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  Tuple		,    _UpperCAmelCase      :  Union[str, Any]		,    _UpperCAmelCase      :  Tuple = None		,    _UpperCAmelCase      :  Dict = False   )			->						Optional[int]:


             '''simple docstring'''




             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      :  Dict		,    _UpperCAmelCase      :  Dict		,    _UpperCAmelCase      :  int = None   )			->						Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_      			=							[self.sep_token_id]
             UpperCAmelCase_      			=							[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      :  Tuple   )			->						str:


             '''simple docstring'''




             return len(self.fairseq_ids_to_tokens   )



       def 					lowercase__    (							self      :  List[str]   )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							{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      :  Union[str, Any]		,    _UpperCAmelCase      :  List[Any]   )			->						List[str]:


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  Dict		,    _UpperCAmelCase      :  Optional[Any]   )			->						str:


             '''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      :  int		,    _UpperCAmelCase      :  List[str]   )			->						Union[str, Any]:


             '''simple docstring'''




             return self.fairseq_ids_to_tokens[index]



       def 					lowercase__    (							self      :  str		,    _UpperCAmelCase      :  Optional[Any]   )			->						Any:


             '''simple docstring'''




             UpperCAmelCase_      			=							"".join(__lowerCamelCase   ).replace(__lowerCamelCase		,    " "   ).strip()
             return out_string







       def 					lowercase__    (							self      :  List[str]		,    _UpperCAmelCase      :  Union[str, Any]		,    _UpperCAmelCase      :  Optional[int] = None   )			->						List[Any]:


             '''simple docstring'''




             if not os.path.isdir(__lowerCamelCase   ):
                   logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""   )
                   return
             UpperCAmelCase_      			=							os.path.join(
                 __lowerCamelCase		,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )
             UpperCAmelCase_      			=							os.path.join(
                 __lowerCamelCase		,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["monolingual_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:
                         UpperCAmelCase_      			=							self.sp_model.serialized_model_proto()
                         fi.write(__lowerCamelCase   )

             if os.path.abspath(self.monolingual_vocab_file   ) != os.path.abspath(
                 __lowerCamelCase   ) and os.path.isfile(self.monolingual_vocab_file   ):
                   copyfile(self.monolingual_vocab_file		,    __lowerCamelCase   )
             elif not os.path.isfile(self.monolingual_vocab_file   ):
                   with open(__lowerCamelCase		,    "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(__lowerCamelCase   )} \n"""   )

             return out_vocab_file, out_monolingual_vocab_file









"""simple docstring"""





from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class 				lowercase__       :







       '''simple docstring'''


       UpperCamelCase						=					42
       UpperCamelCase						=					None
       UpperCamelCase						=					None



lowerCamelCase       	=						namedtuple("""CoinsDistribResult""", """moves excess""")
def        a__     (				lowerCAmelCase__				):

      if root is None:
            return 0

      # Validation
      def count_nodes(lowerCAmelCase__				) -> int:
            if node is None:
                  return 0

            return count_nodes(node.left				) + count_nodes(node.right				) + 1

      def count_coins(lowerCAmelCase__				) -> int:
            if node is None:
                  return 0

            return count_coins(node.left				) + count_coins(node.right				) + node.data

      if count_nodes(lowerCAmelCase__				) != count_coins(lowerCAmelCase__				):
            raise ValueError("The nodes number should be same as the number of coins"				)

      # Main calculation
      def get_distrib(lowerCAmelCase__				) -> CoinsDistribResult:

            if node is None:
                  return CoinsDistribResult(0     ,      1				)

            UpperCAmelCase_			,   UpperCAmelCase_      			=							get_distrib(node.left				)
            UpperCAmelCase_			,   UpperCAmelCase_      			=							get_distrib(node.right				)

            UpperCAmelCase_      			=							1 - left_distrib_excess
            UpperCAmelCase_      			=							1 - right_distrib_excess

            UpperCAmelCase_      			=							(
                left_distrib_moves
                + right_distrib_moves
                + abs(lowerCAmelCase__				)
                + abs(lowerCAmelCase__				)
            )
            UpperCAmelCase_      			=							node.data - coins_to_left - coins_to_right

            return CoinsDistribResult(lowerCAmelCase__     ,      lowerCAmelCase__				)

      return get_distrib(lowerCAmelCase__				)[0]


if __name__ == "__main__":
  import doctest

  doctest.testmod()




