





'''simple docstring'''


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

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


lowerCAmelCase					:     str												=logging.get_logger(__name__)


lowerCAmelCase					:     List[str]												={
    '''vocab_file''': '''vocab.json''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
    '''merges_file''': '''merges.txt''',
}

lowerCAmelCase					:     List[Any]												={
    '''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					:     int												='''</w>'''
lowerCAmelCase					:     Union[str, Any]												='''@@ '''
def 							UpperCAmelCase_  (						__lowerCamelCase					:					Optional[int] ):
   lowercase_			:List[str]    			= set()
   lowercase_			:List[Any]    			= word[0]
   for char in word[1:]:
      pairs.add((prev_char, char) )
      lowercase_			:int    			= char
   return pairs


# Speech2Text2 has no max input length
lowerCAmelCase					:     List[str]												={'''facebook/s2t-wav2vec2-large-en-de''': 1_024}


class       a_   (				_lowerCAmelCase							):
     __A      =			VOCAB_FILES_NAMES
     __A      =			PRETRAINED_VOCAB_FILES_MAP
     __A      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __A      =			["input_ids", "attention_mask"]





     def __init__( self		:					Dict	,      lowercase		:					List[Any]	,      lowercase		:					Tuple="<s>"	,      lowercase		:					Union[str, Any]="<pad>"	,      lowercase		:					Optional[int]="</s>"	,      lowercase		:					Tuple="<unk>"	,      lowercase		:					int=False	,      lowercase		:					Tuple=None	,      **lowercase		:					Dict	,      ):





        """simple docstring"""




        super().__init__(
            unk_token=lowercase	,      bos_token=lowercase	,      eos_token=lowercase	,      pad_token=lowercase	,      do_lower_case=lowercase	,      **lowercase	,      )

        lowercase_			:Any    			= do_lower_case

        with open(lowercase	,      encoding="utf-8"						) as vocab_handle:
           lowercase_			:Dict    			= json.load(lowercase						)
        lowercase_			:Tuple    			= {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.'						)

           lowercase_			:Any    			= None
           lowercase_			:int    			= None
        else:
           with open(lowercase	,      encoding="utf-8"						) as merges_handle:
              lowercase_			:List[str]    			= merges_handle.read().split("\n"						)[:-1]

           lowercase_			:Optional[int]    			= [tuple(merge.split()[:2]						) for merge in merges]
           lowercase_			:List[str]    			= dict(zip(lowercase	,      range(len(lowercase						)						)						)						)
           lowercase_			:str    			= {}





     @property
     def 							lowercase__      ( self		:					List[Any]						):





        """simple docstring"""




        return len(self.decoder						)





     def 							lowercase__      ( self		:					int						):





        """simple docstring"""




        return dict(self.encoder	,      **self.added_tokens_encoder						)





     def 							lowercase__      ( self		:					Union[str, Any]	,      lowercase		:					Tuple						):





        """simple docstring"""




        lowercase_			:List[str]    			= tuple(token[:-1]						) + (token[-1] + BPE_TOKEN_MERGES,)
        if token in self.cache:
           return self.cache[token]
        lowercase_			:Dict    			= get_pairs(lowercase						)

        if not pairs:
           return token

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

              if word[i] == first and i < len(lowercase						) - 1 and word[i + 1] == second:
                 new_word.append(first + second						)
                 i += 2
              else:
                 new_word.append(word[i]						)
                 i += 1
           lowercase_			:Optional[Any]    			= tuple(lowercase						)
           lowercase_			:Tuple    			= new_word
           if len(lowercase						) == 1:
              break
           else:
              lowercase_			:Tuple    			= get_pairs(lowercase						)
        lowercase_			:Any    			= " ".join(lowercase						)
        if word == "\n  " + BPE_TOKEN_MERGES:
           lowercase_			:int    			= "\n" + BPE_TOKEN_MERGES

        if word.endswith(lowercase						):
           lowercase_			:int    			= word.replace(lowercase	,      ""						)

        lowercase_			:Dict    			= word.replace(" "	,      lowercase						)
        lowercase_			:int    			= word
        return word





     def 							lowercase__      ( self		:					Optional[int]	,      lowercase		:					List[str]						):





        """simple docstring"""




        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:
           lowercase_			:List[Any]    			= text.lower()

        lowercase_			:Tuple    			= text.split()

        lowercase_			:int    			= []
        for token in text:
           if token:
              split_tokens.extend(list(self.bpe(lowercase						).split(" "						)						)						)

        return split_tokens





     def 							lowercase__      ( self		:					Any	,      lowercase		:					str						):





        """simple docstring"""




        return self.encoder.get(lowercase	,      self.encoder.get(self.unk_token						)						)





     def 							lowercase__      ( self		:					Tuple	,      lowercase		:					int						):





        """simple docstring"""




        lowercase_			:Any    			= self.decoder.get(lowercase	,      self.unk_token						)
        return result





     def 							lowercase__      ( self		:					int	,      lowercase		:					List[str]						):





        """simple docstring"""




        lowercase_			:Optional[Any]    			= " ".join(lowercase						)

        # make sure @@ tokens are concatenated
        lowercase_			:int    			= "".join(string.split(lowercase						)						)

        return string







     def 							lowercase__      ( self		:					Tuple	,      lowercase		:					str	,      lowercase		:					Optional[str] = None						):





        """simple docstring"""




        if not os.path.isdir(lowercase						):
           logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
           return
        lowercase_			:str    			= os.path.join(
            lowercase	,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
        lowercase_			:List[Any]    			= os.path.join(
            lowercase	,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]						)

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

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

        with open(lowercase	,      "w"	,      encoding="utf-8"						) as writer:
           for bpe_tokens, token_index in sorted(self.bpe_ranks.items()	,      key=lambda lowercase						: 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!"						)
                 lowercase_			:Optional[Any]    			= token_index
              writer.write(" ".join(lowercase						) + "\n"						)
              index += 1

        return (vocab_file, merges_file)









'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase					:     Optional[Any]												={
    '''configuration_nllb_moe''': [
        '''NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''NllbMoeConfig''',
    ]
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase					:     Tuple												=[
     '''NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''NllbMoeForConditionalGeneration''',
     '''NllbMoeModel''',
     '''NllbMoePreTrainedModel''',
     '''NllbMoeTop2Router''',
     '''NllbMoeSparseMLP''',
 ]


if TYPE_CHECKING:
 from .configuration_nllb_moe import (
     NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
     NllbMoeConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_nllb_moe import (
      NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
      NllbMoeForConditionalGeneration,
      NllbMoeModel,
      NllbMoePreTrainedModel,
      NllbMoeSparseMLP,
      NllbMoeTopaRouter,
  )


else:
 import sys

 lowerCAmelCase					:     Tuple												=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


