



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

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


_lowercase    	=		logging.get_logger(__name__)

_lowercase    	=		{
    "vocab_file": "vocab.txt",
    "merges_file": "bpe.codes",
}

_lowercase    	=		{
    "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",
    },
}

_lowercase    	=		{
    "vinai/phobert-base": 256,
    "vinai/phobert-large": 256,
}



def 		lowerCAmelCase__     (       UpperCamelCase_					:							Any						)->	Optional[int]:
    A__					=       set()
    A__					=       word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)						)
        A__					=       char

    A__					=       set(UpperCamelCase_						)
    return pairs



class      _UpperCAmelCase      (							A__  ):
     UpperCamelCase__		     =					VOCAB_FILES_NAMES
     UpperCamelCase__		     =					PRETRAINED_VOCAB_FILES_MAP
     UpperCamelCase__		     =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




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

         A__					=       vocab_file
         A__					=       merges_file

         A__					=       {}
         A__					=       0
         A__					=       1
         A__					=       2
         A__					=       3

         self.add_from_file(a__)

         A__					=       {v: k for k, v in self.encoder.items()}

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




     def 		snake_case_		(					self			,    a__			,    a__ = None):

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




     def 		snake_case_		(					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 		snake_case_		(					self			,    a__			,    a__ = None):
         A__					=       [self.sep_token_id]
         A__					=       [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 		snake_case_		(					self):
         return len(self.encoder)




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




     def 		snake_case_		(					self			,    a__):
         if token in self.cache:
             return self.cache[token]
         A__					=       tuple(a__)
         A__					=       tuple(list(word[:-1]) + [word[-1] + '''</w>'''])
         A__					=       get_pairs(a__)

         if not pairs:
             return token

         while True:
             A__					=       min(a__			,    key=lambda a__: self.bpe_ranks.get(a__			,    float('''inf''')))
             if bigram not in self.bpe_ranks:
                 break
             A__			,						A__					=       bigram
             A__					=       []
             A__					=       0
             while i < len(a__):
                 try:
                     A__					=       word.index(a__			,    a__)
                 except ValueError:
                     new_word.extend(word[i:])
                     break
                 else:
                     new_word.extend(word[i:j])
                     A__					=       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
             A__					=       tuple(a__)
             A__					=       new_word
             if len(a__) == 1:
                 break
             else:
                 A__					=       get_pairs(a__)
         A__					=       '''@@ '''.join(a__)
         A__					=       word[:-4]
         A__					=       word
         return word




     def 		snake_case_		(					self			,    a__):
         A__					=       []

         A__					=       re.findall(R'''\S+\n?'''			,    a__)

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




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




     def 		snake_case_		(					self			,    a__):
         return self.decoder.get(a__			,    self.unk_token)




     def 		snake_case_		(					self			,    a__):
         A__					=       ''' '''.join(a__).replace('''@@ '''			,    '''''').strip()
         return out_string




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

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

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

         return out_vocab_file, out_merge_file




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

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





from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase    	=		{
    "configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
    "feature_extraction_mctct": ["MCTCTFeatureExtractor"],
    "processing_mctct": ["MCTCTProcessor"],
}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowercase    	=		[
       "MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "MCTCTForCTC",
       "MCTCTModel",
       "MCTCTPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig
   from .feature_extraction_mctct import MCTCTFeatureExtractor
   from .processing_mctct import MCTCTProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mctct import MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST, MCTCTForCTC, MCTCTModel, MCTCTPreTrainedModel

else:
   import sys

   _lowercase    	=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
