





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  __UpperCAmelCase(   lowercase_   ):
       _lowerCamelCase				:  Tuple						=		set()
       _lowerCamelCase				:  Any						=		word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)   )
              _lowerCamelCase				:  Tuple						=		char
       return pairs


# Speech2Text2 has no max input length
_lowerCamelCase      							=   {'facebook/s2t-wav2vec2-large-en-de': 1024}







class       __A							(   lowerCamelCase__	):




      """simple docstring"""







      UpperCAmelCase__							=   VOCAB_FILES_NAMES
      UpperCAmelCase__							=   PRETRAINED_VOCAB_FILES_MAP
      UpperCAmelCase__							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCAmelCase__							=   ["""input_ids""", """attention_mask"""]


      def __init__(		self   ,				a__   ,				a__="<s>"   ,				a__="<pad>"   ,				a__="</s>"   ,				a__="<unk>"   ,				a__=False   ,				a__=None   ,				**a__   ,				):



             """simple docstring"""





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

             _lowerCamelCase				:  List[str]						=		do_lower_case

             with open(a__   ,				encoding='''utf-8''') as vocab_handle:
                    _lowerCamelCase				:  Optional[Any]						=		json.load(a__)
             _lowerCamelCase				:  int						=		{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.""")

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

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


      @property
      def 					__snake_case      (		self):



             """simple docstring"""





             return len(self.decoder)


      def 					__snake_case      (		self):



             """simple docstring"""





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


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





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

             if not pairs:
                    return token

             while True:
                    _lowerCamelCase				:  List[str]						=		min(a__   ,				key=lambda a__: self.bpe_ranks.get(a__   ,				float('''inf''')))
                    if bigram not in self.bpe_ranks:
                           break
                    _lowerCamelCase,	_lowerCamelCase				:  List[str]						=		bigram
                    _lowerCamelCase				:  Tuple						=		[]
                    _lowerCamelCase				:  Union[str, Any]						=		0
                    while i < len(a__):
                           try:
                                  _lowerCamelCase				:  Any						=		word.index(a__   ,				a__)
                           except ValueError:
                                  new_word.extend(word[i:])
                                  break
                           else:
                                  new_word.extend(word[i:j])
                                  _lowerCamelCase				:  List[Any]						=		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
                    _lowerCamelCase				:  List[Any]						=		tuple(a__)
                    _lowerCamelCase				:  List[str]						=		new_word
                    if len(a__) == 1:
                           break
                    else:
                           _lowerCamelCase				:  str						=		get_pairs(a__)
             _lowerCamelCase				:  Tuple						=		''' '''.join(a__)
             if word == "\n  " + BPE_TOKEN_MERGES:
                    _lowerCamelCase				:  int						=		'''\n''' + BPE_TOKEN_MERGES

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

             _lowerCamelCase				:  Tuple						=		word.replace(''' '''   ,				a__)
             _lowerCamelCase				:  List[Any]						=		word
             return word


      def 					__snake_case      (		self   ,				a__):



             """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:
                    _lowerCamelCase				:  Any						=		text.lower()

             _lowerCamelCase				:  Union[str, Any]						=		text.split()

             _lowerCamelCase				:  Union[str, Any]						=		[]
             for token in text:
                    if token:
                           split_tokens.extend(list(self.bpe(a__).split(''' ''')))

             return split_tokens


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





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


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





             _lowerCamelCase				:  Any						=		self.decoder.get(a__   ,				self.unk_token)
             return result


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





             _lowerCamelCase				:  Any						=		''' '''.join(a__)

             # make sure @@ tokens are concatenated
             _lowerCamelCase				:  Union[str, Any]						=		''''''.join(string.split(a__))

             return string



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



             """simple docstring"""





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

             _lowerCamelCase				:  Union[str, Any]						=		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!''')
                                  _lowerCamelCase				:  Union[str, Any]						=		token_index
                           writer.write(''' '''.join(a__) + '''\n''')
                           index += 1

             return (vocab_file, merges_file)








import copy
import random

from transformers import CLIPTokenizer







class       __A							(   lowerCamelCase__	):




      """simple docstring"""







      def __init__(		self   ,				*a__   ,				**a__):



             """simple docstring"""





             super().__init__(*a__   ,				**a__)
             _lowerCamelCase				:  Optional[Any]						=		{}


      def 					__snake_case      (		self   ,				a__   ,				*a__   ,				**a__):



             """simple docstring"""





             _lowerCamelCase				:  Optional[int]						=		super().add_tokens(a__   ,				*a__   ,				**a__)
             if num_added_tokens == 0:
                    raise ValueError(
                        F"""The tokenizer already contains the token {placeholder_token}. Please pass a different"""
                        ''' `placeholder_token` that is not already in the tokenizer.''')


      def 					__snake_case      (		self   ,				a__   ,				*a__   ,				a__=1   ,				**a__):



             """simple docstring"""





             _lowerCamelCase				:  Tuple						=		[]
             if num_vec_per_token == 1:
                    self.try_adding_tokens(a__   ,				*a__   ,				**a__)
                    output.append(a__)
             else:
                    _lowerCamelCase				:  Dict						=		[]
                    for i in range(a__):
                           _lowerCamelCase				:  Optional[Any]						=		placeholder_token + F"""_{i}"""
                           self.try_adding_tokens(a__   ,				*a__   ,				**a__)
                           output.append(a__)
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
             for token in self.token_map:
                    if token in placeholder_token:
                           raise ValueError(
                               F"""The tokenizer already has placeholder token {token} that can get confused with"""
                               F""" {placeholder_token}keep placeholder tokens independent""")
             _lowerCamelCase				:  int						=		output


      def 					__snake_case      (		self   ,				a__   ,				a__=False   ,				a__=1.0):



             """simple docstring"""





             if isinstance(a__   ,				a__):
                    _lowerCamelCase				:  Tuple						=		[]
                    for i in range(len(a__)):
                           output.append(self.replace_placeholder_tokens_in_text(text[i]   ,				vector_shuffle=a__))
                    return output
             for placeholder_token in self.token_map:
                    if placeholder_token in text:
                           _lowerCamelCase				:  Union[str, Any]						=		self.token_map[placeholder_token]
                           _lowerCamelCase				:  Optional[Any]						=		tokens[: 1 + int(len(a__) * prop_tokens_to_load)]
                           if vector_shuffle:
                                  _lowerCamelCase				:  int						=		copy.copy(a__)
                                  random.shuffle(a__)
                           _lowerCamelCase				:  List[str]						=		text.replace(a__   ,				''' '''.join(a__))
             return text


      def __call__(		self   ,				a__   ,				*a__   ,				a__=False   ,				a__=1.0   ,				**a__):



             """simple docstring"""





             return super().__call__(
                 self.replace_placeholder_tokens_in_text(
                     a__   ,				vector_shuffle=a__   ,				prop_tokens_to_load=a__)   ,				*a__   ,				**a__   ,				)



      def 					__snake_case      (		self   ,				a__   ,				*a__   ,				a__=False   ,				a__=1.0   ,				**a__):



             """simple docstring"""





             return super().encode(
                 self.replace_placeholder_tokens_in_text(
                     a__   ,				vector_shuffle=a__   ,				prop_tokens_to_load=a__)   ,				*a__   ,				**a__   ,				)

