





"""simple docstring"""






import json
import os
from typing import Dict, List, Optional, Tuple

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


lowerCAmelCase_			=							logging.get_logger(__name__)


lowerCAmelCase_			=							{
    '''vocab_file''': '''vocab.json''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
    '''merges_file''': '''merges.txt''',
}

lowerCAmelCase_			=							{
    '''vocab_file''': {
        '''facebook/s2t-wav2vec2-large-en-de''': (
            '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json'''
        ),
    },
    '''tokenizer_config_file''': {
        '''facebook/s2t-wav2vec2-large-en-de''': (
            '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json'''
        ),
    },
    '''merges_file''': {
        '''facebook/s2t-wav2vec2-large-en-de''': (
            '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt'''
        ),
    },
}

lowerCAmelCase_			=							'''</w>'''
lowerCAmelCase_			=							'''@@ '''

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Any:






       """simple docstring"""




       _UpperCAmelCase     =     set()
       _UpperCAmelCase     =     word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)							)
              _UpperCAmelCase     =     char
       return pairs


# Speech2Text2 has no max input length
lowerCAmelCase_			=							{'''facebook/s2t-wav2vec2-large-en-de''': 1_024}



class 	lowerCAmelCase					(      snake_case							):
       lowerCAmelCase__						 =  VOCAB_FILES_NAMES
       lowerCAmelCase__						 =  PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__						 =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__						 =  ["""input_ids""", """attention_mask"""]






       def __init__(   self    ,  a__    ,  a__="<s>"    ,  a__="<pad>"    ,  a__="</s>"    ,  a__="<unk>"    ,  a__=False    ,  a__=None    ,  **a__    ,  ):
              super().__init__(
                  unk_token=a__    ,  bos_token=a__    ,  eos_token=a__    ,  pad_token=a__    ,  do_lower_case=a__    ,  **a__    ,  )

              _UpperCAmelCase     =     do_lower_case

              with open(a__    ,  encoding='utf-8'     ) as vocab_handle:
                     _UpperCAmelCase     =     json.load(a__     )
              _UpperCAmelCase     =     {v: k for k, v in self.encoder.items()}

              if merges_file is None:
                     logger.info(f"""No merges files provided. {self.__class__.__name__} can only be used for decoding."""     )

                     _UpperCAmelCase     =     None
                     _UpperCAmelCase     =     None
              else:
                     with open(a__    ,  encoding='utf-8'     ) as merges_handle:
                            _UpperCAmelCase     =     merges_handle.read().split('\n'     )[:-1]

                     _UpperCAmelCase     =     [tuple(merge.split()[:2]     ) for merge in merges]
                     _UpperCAmelCase     =     dict(zip(a__    ,  range(len(a__     )     )     )     )
                     _UpperCAmelCase     =     {}






       @property
       def 							__A (   self     ):
              return len(self.decoder     )






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






       def 							__A (   self    ,  a__     ):
              _UpperCAmelCase     =     tuple(token[:-1]     ) + (token[-1] + BPE_TOKEN_MERGES,)
              if token in self.cache:
                     return self.cache[token]
              _UpperCAmelCase     =     get_pairs(a__     )

              if not pairs:
                     return token

              while True:
                     _UpperCAmelCase     =     min(a__    ,  key=lambda a__     : self.bpe_ranks.get(a__    ,  float('inf'     )     )     )
                     if bigram not in self.bpe_ranks:
                            break
                     _UpperCAmelCase    ,							_UpperCAmelCase     =     bigram
                     _UpperCAmelCase     =     []
                     _UpperCAmelCase     =     0
                     while i < len(a__     ):
                            try:
                                   _UpperCAmelCase     =     word.index(a__    ,  a__     )
                            except ValueError:
                                   new_word.extend(word[i:]     )
                                   break
                            else:
                                   new_word.extend(word[i:j]     )
                                   _UpperCAmelCase     =     j

                            if word[i] == first and i < len(a__     ) - 1 and word[i + 1] == second:
                                   new_word.append(first + second     )
                                   i += 2
                            else:
                                   new_word.append(word[i]     )
                                   i += 1
                     _UpperCAmelCase     =     tuple(a__     )
                     _UpperCAmelCase     =     new_word
                     if len(a__     ) == 1:
                            break
                     else:
                            _UpperCAmelCase     =     get_pairs(a__     )
              _UpperCAmelCase     =     ' '.join(a__     )
              if word == "\n  " + BPE_TOKEN_MERGES:
                     _UpperCAmelCase     =     '\n' + BPE_TOKEN_MERGES

              if word.endswith(a__     ):
                     _UpperCAmelCase     =     word.replace(a__    ,  ''     )

              _UpperCAmelCase     =     word.replace(' '    ,  a__     )
              _UpperCAmelCase     =     word
              return word






       def 							__A (   self    ,  a__     ):

              if self.bpe_ranks is None:
                     raise ValueError(
                         'This tokenizer was instantiated without a `merges.txt` file, so'
                         ' that it can only be used for decoding, not for encoding.'
                         'Make sure to provide `merges.txt` file at instantiation to enable '
                         'encoding.'     )

              if self.do_lower_case:
                     _UpperCAmelCase     =     text.lower()

              _UpperCAmelCase     =     text.split()

              _UpperCAmelCase     =     []
              for token in text:
                     if token:
                            split_tokens.extend(list(self.bpe(a__     ).split(' '     )     )     )

              return split_tokens






       def 							__A (   self    ,  a__     ):
              return self.encoder.get(a__    ,  self.encoder.get(self.unk_token     )     )






       def 							__A (   self    ,  a__     ):
              _UpperCAmelCase     =     self.decoder.get(a__    ,  self.unk_token     )
              return result






       def 							__A (   self    ,  a__     ):
              _UpperCAmelCase     =     ' '.join(a__     )

              # make sure @@ tokens are concatenated
              _UpperCAmelCase     =     ''.join(string.split(a__     )     )

              return string






       def 							__A (   self    ,  a__    ,  a__ = None     ):
              if not os.path.isdir(a__     ):
                     logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""     )
                     return
              _UpperCAmelCase     =     os.path.join(
                  a__    ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )
              _UpperCAmelCase     =     os.path.join(
                  a__    ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']     )

              with open(a__    ,  'w'    ,  encoding='utf-8'     ) as f:
                     f.write(json.dumps(self.encoder    ,  indent=2    ,  sort_keys=a__    ,  ensure_ascii=a__     ) + '\n'     )

              _UpperCAmelCase     =     0
              if self.bpe_ranks is None:
                     return (vocab_file,)

              with open(a__    ,  'w'    ,  encoding='utf-8'     ) as writer:
                     for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,  key=lambda a__     : kv[1]     ):
                            if index != token_index:
                                   logger.warning(
                                       f"""Saving vocabulary to {merges_file}: BPE merge indices are not consecutive."""
                                       ' Please check that the tokenizer is not corrupted!'     )
                                   _UpperCAmelCase     =     token_index
                            writer.write(' '.join(a__     ) + '\n'     )
                            index += 1

              return (vocab_file, merges_file)













"""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_024}



class 	lowerCAmelCase					(      snake_case							):
       lowerCAmelCase__						 =  VOCAB_FILES_NAMES
       lowerCAmelCase__						 =  PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__						 =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__						 =  ["""input_ids""", """attention_mask"""]






       def __init__(   self    ,  a__    ,  a__    ,  a__="<s>"    ,  a__="</s>"    ,  a__="</s>"    ,  a__="<s>"    ,  a__="<unk>"    ,  a__="<pad>"    ,  a__="<mask>"    ,  a__ = None    ,  **a__    ,  ):
              # Mask token behave like a normal word, i.e. include the space before it
              _UpperCAmelCase     =     AddedToken(a__    ,  lstrip=a__    ,  rstrip=a__     ) if isinstance(a__    ,  a__     ) else mask_token

              _UpperCAmelCase     =     {} 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__    ,  )

              _UpperCAmelCase     =     vocab_file
              _UpperCAmelCase     =     monolingual_vocab_file
              _UpperCAmelCase     =     spm.SentencePieceProcessor(**self.sp_model_kwargs     )
              self.sp_model.Load(str(a__     )     )

              # 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(a__     ) not in self.fairseq_tokens_to_ids:
                            _UpperCAmelCase     =     cnt
                            cnt += 1
              with open(a__    ,  '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(a__     ) 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     ):
              _UpperCAmelCase     =     self.__dict__.copy()
              _UpperCAmelCase     =     None
              _UpperCAmelCase     =     self.sp_model.serialized_model_proto()
              return state






       def __setstate__(   self    ,  a__     ):
              _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 							__A (   self    ,  a__    ,  a__ = None     ):

              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 							__A (   self    ,  a__    ,  a__ = None    ,  a__ = False     ):

              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 							__A (   self    ,  a__    ,  a__ = None     ):
              _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 							__A (   self     ):
              return len(self.fairseq_ids_to_tokens     )






       def 							__A (   self     ):
              _UpperCAmelCase     =     {self.convert_ids_to_tokens(a__     ): i for i in range(self.vocab_size     )}
              vocab.update(self.added_tokens_encoder     )
              return vocab






       def 							__A (   self    ,  a__     ):
              return self.sp_model.encode(a__    ,  out_type=a__     )






       def 							__A (   self    ,  a__     ):
              if token in self.fairseq_tokens_to_ids:
                     return self.fairseq_tokens_to_ids[token]
              else:
                     return self.unk_token_id






       def 							__A (   self    ,  a__     ):
              return self.fairseq_ids_to_tokens[index]






       def 							__A (   self    ,  a__     ):
              _UpperCAmelCase     =     ''.join(a__     ).replace(a__    ,  ' '     ).strip()
              return out_string






       def 							__A (   self    ,  a__    ,  a__ = None     ):
              if not os.path.isdir(a__     ):
                     logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""     )
                     return
              _UpperCAmelCase     =     os.path.join(
                  a__    ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )
              _UpperCAmelCase     =     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:
                            _UpperCAmelCase     =     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






