






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

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


lowerCamelCase	:							List[Any]				=logging.get_logger(__name__)


lowerCamelCase	:							Union[str, Any]				={
    '''vocab_file''': '''vocab.json''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
    '''merges_file''': '''merges.txt''',
}

lowerCamelCase	:							Union[str, 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	:							List[Any]				='''</w>'''
lowerCamelCase	:							Any				='''@@ '''







def 		SCREAMING_SNAKE_CASE							(					__lowerCAmelCase			) ->	Optional[int]:
     UpperCamelCase__			:   List[str]       				=  set()
     UpperCamelCase__			:   Any       				=  word[0]
     for char in word[1:]:
          pairs.add((prev_char, char)			)
          UpperCamelCase__			:   int       				=  char
     return pairs


# Speech2Text2 has no max input length
lowerCamelCase	:							List[Any]				={'''facebook/s2t-wav2vec2-large-en-de''': 1024}





class 			__a  (    A__       ):
 _lowerCAmelCase       :       Union[str, Any]        = VOCAB_FILES_NAMES
 _lowerCAmelCase       :       List[str]        = PRETRAINED_VOCAB_FILES_MAP
 _lowerCAmelCase       :       Dict        = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCAmelCase       :       Optional[Any]        = ['''input_ids''', '''attention_mask''']







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


      '''simple docstring'''






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

      UpperCamelCase__			:   Tuple       				=  do_lower_case

      with open(SCREAMING_SNAKE_CASE							,   encoding="utf-8"						) as vocab_handle:
           UpperCamelCase__			:   int       				=  json.load(SCREAMING_SNAKE_CASE						)
      UpperCamelCase__			:   Union[str, Any]       				=  {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__			:   List[str]       				=  None
           UpperCamelCase__			:   Union[str, Any]       				=  None
      else:
           with open(SCREAMING_SNAKE_CASE							,   encoding="utf-8"						) as merges_handle:
                UpperCamelCase__			:   str       				=  merges_handle.read().split("\n"						)[:-1]

           UpperCamelCase__			:   Any       				=  [tuple(merge.split()[:2]						) for merge in merges]
           UpperCamelCase__			:   Dict       				=  dict(zip(SCREAMING_SNAKE_CASE							,   range(len(SCREAMING_SNAKE_CASE						)						)						)						)
           UpperCamelCase__			:   Optional[int]       				=  {}







 @property
 def 					__lowercase					(		self					:   str						):


      '''simple docstring'''






      return len(self.decoder						)







 def 					__lowercase					(		self					:   Dict						):


      '''simple docstring'''






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







 def 					__lowercase					(		self					:   str							,   SCREAMING_SNAKE_CASE					:   str						):


      '''simple docstring'''






      UpperCamelCase__			:   Any       				=  tuple(token[:-1]						) + (token[-1] + BPE_TOKEN_MERGES,)
      if token in self.cache:
           return self.cache[token]
      UpperCamelCase__			:   Union[str, Any]       				=  get_pairs(SCREAMING_SNAKE_CASE						)

      if not pairs:
           return token

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

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

      if word.endswith(SCREAMING_SNAKE_CASE						):
           UpperCamelCase__			:   Union[str, Any]       				=  word.replace(SCREAMING_SNAKE_CASE							,   ""						)

      UpperCamelCase__			:   Optional[int]       				=  word.replace(" "							,   SCREAMING_SNAKE_CASE						)
      UpperCamelCase__			:   Tuple       				=  word
      return word







 def 					__lowercase					(		self					:   Any							,   SCREAMING_SNAKE_CASE					:   Dict						):


      '''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:
           UpperCamelCase__			:   Union[str, Any]       				=  text.lower()

      UpperCamelCase__			:   List[Any]       				=  text.split()

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

      return split_tokens







 def 					__lowercase					(		self					:   Tuple							,   SCREAMING_SNAKE_CASE					:   str						):


      '''simple docstring'''






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







 def 					__lowercase					(		self					:   Optional[int]							,   SCREAMING_SNAKE_CASE					:   int						):


      '''simple docstring'''






      UpperCamelCase__			:   List[Any]       				=  self.decoder.get(SCREAMING_SNAKE_CASE							,   self.unk_token						)
      return result







 def 					__lowercase					(		self					:   Dict							,   SCREAMING_SNAKE_CASE					:   List[str]						):


      '''simple docstring'''






      UpperCamelCase__			:   Tuple       				=  " ".join(SCREAMING_SNAKE_CASE						)

      # make sure @@ tokens are concatenated
      UpperCamelCase__			:   str       				=  "".join(string.split(SCREAMING_SNAKE_CASE						)						)

      return string







 def 					__lowercase					(		self					:   Optional[Any]							,   SCREAMING_SNAKE_CASE					:   str							,   SCREAMING_SNAKE_CASE					:   Optional[str] = None						):


      '''simple docstring'''






      if not os.path.isdir(SCREAMING_SNAKE_CASE						):
           logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
           return
      UpperCamelCase__			:   Tuple       				=  os.path.join(
          SCREAMING_SNAKE_CASE							,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
      UpperCamelCase__			:   Optional[int]       				=  os.path.join(
          SCREAMING_SNAKE_CASE							,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]						)

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

      UpperCamelCase__			:   List[str]       				=  0
      if self.bpe_ranks is None:
           return (vocab_file,)

      with open(SCREAMING_SNAKE_CASE							,   "w"							,   encoding="utf-8"						) as writer:
           for bpe_tokens, token_index in sorted(self.bpe_ranks.items()							,   key=lambda SCREAMING_SNAKE_CASE						: 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__			:   int       				=  token_index
                writer.write(" ".join(SCREAMING_SNAKE_CASE						) + "\n"						)
                index += 1

      return (vocab_file, merges_file)







from typing import TYPE_CHECKING

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


lowerCamelCase	:							int				={
    '''configuration_audio_spectrogram_transformer''': [
        '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ASTConfig''',
    ]
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase	:							Union[str, Any]				=[
     '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''ASTForAudioClassification''',
     '''ASTModel''',
     '''ASTPreTrainedModel''',
 ]

try:
 if not is_speech_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase	:							Optional[int]				=['''ASTFeatureExtractor''']

if TYPE_CHECKING:
 from .configuration_audio_spectrogram_transformer import (
     AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
     ASTConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_audio_spectrogram_transformer import (
      AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      ASTForAudioClassification,
      ASTModel,
      ASTPreTrainedModel,
  )

 try:
  if not is_speech_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
 import sys

 lowerCamelCase	:							Optional[int]				=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)