


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

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


snake_case__				:	Optional[int]					       =					logging.get_logger(__name__)


snake_case__				:	Optional[Any]					       =					{
    'vocab_file': 'vocab.json',
    'tokenizer_config_file': 'tokenizer_config.json',
    'merges_file': 'merges.txt',
}

snake_case__				:	Optional[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'
        ),
    },
}

snake_case__				:	Optional[Any]					       =					'</w>'
snake_case__				:	List[Any]					       =					'@@ '


def    __lowerCamelCase   (      A__						: Optional[int]					)     ->    Optional[Any]:
   lowerCamelCase_						:   List[Any]		= set()
   lowerCamelCase_						:   Tuple		= word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)					)
      lowerCamelCase_						:   Optional[Any]		= char
   return pairs


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





class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



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



       def __init__(						self				:				Union[str, Any]		,				__a				:				int		,				__a				:				Optional[Any]="<s>"		,				__a				:				Any="<pad>"		,				__a				:				List[Any]="</s>"		,				__a				:				List[Any]="<unk>"		,				__a				:				Tuple=False		,				__a				:				List[str]=None		,				**__a				:				Optional[int]		,				)					->int:
          super().__init__(
              unk_token=__a		,				bos_token=__a		,				eos_token=__a		,				pad_token=__a		,				do_lower_case=__a		,				**__a		,				)

          lowerCamelCase_						:   int		= do_lower_case

          with open(__a		,				encoding="""utf-8"""							) as vocab_handle:
             lowerCamelCase_						:   int		= 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_						:   Dict		= None
             lowerCamelCase_						:   List[Any]		= None
          else:
             with open(__a		,				encoding="""utf-8"""							) as merges_handle:
                lowerCamelCase_						:   Dict		= merges_handle.read().split("""\n"""							)[:-1]

             lowerCamelCase_						:   List[str]		= [tuple(merge.split()[:2]							) for merge in merges]
             lowerCamelCase_						:   Tuple		= dict(zip(__a		,				range(len(__a							)							)							)							)
             lowerCamelCase_						:   Tuple		= {}



       @property
       def 				_lowerCAmelCase							(						self				:				int							)					->int:
          return len(self.decoder							)



       def 				_lowerCAmelCase							(						self				:				List[str]							)					->Dict:
          return dict(self.encoder		,				**self.added_tokens_encoder							)



       def 				_lowerCAmelCase							(						self				:				int		,				__a				:				Any							)					->List[Any]:
          lowerCamelCase_						:   str		= tuple(token[:-1]							) + (token[-1] + BPE_TOKEN_MERGES,)
          if token in self.cache:
             return self.cache[token]
          lowerCamelCase_						:   Optional[int]		= get_pairs(__a							)

          if not pairs:
             return token

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

          if word.endswith(__a							):
             lowerCamelCase_						:   Any		= word.replace(__a		,				""""""							)

          lowerCamelCase_						:   Dict		= word.replace(""" """		,				__a							)
          lowerCamelCase_						:   List[Any]		= word
          return word



       def 				_lowerCAmelCase							(						self				:				Optional[int]		,				__a				:				str							)					->int:

          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_						:   Optional[Any]		= text.lower()

          lowerCamelCase_						:   Dict		= text.split()

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

          return split_tokens



       def 				_lowerCAmelCase							(						self				:				Tuple		,				__a				:				str							)					->int:
          return self.encoder.get(__a		,				self.encoder.get(self.unk_token							)							)



       def 				_lowerCAmelCase							(						self				:				int		,				__a				:				int							)					->str:
          lowerCamelCase_						:   Optional[int]		= self.decoder.get(__a		,				self.unk_token							)
          return result



       def 				_lowerCAmelCase							(						self				:				Optional[Any]		,				__a				:				List[str]							)					->str:
          lowerCamelCase_						:   Optional[Any]		= """ """.join(__a							)

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

          return string




       def 				_lowerCAmelCase							(						self				:				str		,				__a				:				str		,				__a				:				Optional[str] = None							)					->Tuple[str]:
          if not os.path.isdir(__a							):
             logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''							)
             return
          lowerCamelCase_						:   List[Any]		= os.path.join(
              __a		,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)
          lowerCamelCase_						:   List[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_						:   List[str]		= 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_						:   str		= token_index
                writer.write(""" """.join(__a							) + """\n"""							)
                index += 1

          return (vocab_file, merges_file)









from . import (
    albert,
    align,
    altclip,
    audio_spectrogram_transformer,
    auto,
    autoformer,
    bark,
    bart,
    barthez,
    bartpho,
    beit,
    bert,
    bert_generation,
    bert_japanese,
    bertweet,
    big_bird,
    bigbird_pegasus,
    biogpt,
    bit,
    blenderbot,
    blenderbot_small,
    blip,
    blip_a,
    bloom,
    bridgetower,
    byta,
    camembert,
    canine,
    chinese_clip,
    clap,
    clip,
    clipseg,
    codegen,
    conditional_detr,
    convbert,
    convnext,
    convnextva,
    cpm,
    cpmant,
    ctrl,
    cvt,
    dataavec,
    deberta,
    deberta_va,
    decision_transformer,
    deformable_detr,
    deit,
    deprecated,
    deta,
    detr,
    dialogpt,
    dinat,
    distilbert,
    dit,
    donut,
    dpr,
    dpt,
    efficientformer,
    efficientnet,
    electra,
    encodec,
    encoder_decoder,
    ernie,
    ernie_m,
    esm,
    falcon,
    flaubert,
    flava,
    fnet,
    focalnet,
    fsmt,
    funnel,
    git,
    glpn,
    gpta,
    gpt_bigcode,
    gpt_neo,
    gpt_neox,
    gpt_neox_japanese,
    gpt_swa,
    gptj,
    gptsan_japanese,
    graphormer,
    groupvit,
    herbert,
    hubert,
    ibert,
    imagegpt,
    informer,
    instructblip,
    jukebox,
    layoutlm,
    layoutlmva,
    layoutlmva,
    layoutxlm,
    led,
    levit,
    lilt,
    llama,
    longformer,
    longta,
    luke,
    lxmert,
    mam_aaa,
    marian,
    markuplm,
    maskaformer,
    maskformer,
    mbart,
    mbartaa,
    mega,
    megatron_bert,
    megatron_gpta,
    mgp_str,
    mluke,
    mobilebert,
    mobilenet_va,
    mobilenet_va,
    mobilevit,
    mobilevitva,
    mpnet,
    mra,
    mta,
    musicgen,
    mvp,
    nat,
    nezha,
    nllb,
    nllb_moe,
    nystromformer,
    oneformer,
    open_llama,
    openai,
    opt,
    owlvit,
    pegasus,
    pegasus_x,
    perceiver,
    phobert,
    pixastruct,
    plbart,
    poolformer,
    prophetnet,
    qdqbert,
    rag,
    realm,
    reformer,
    regnet,
    rembert,
    resnet,
    roberta,
    roberta_prelayernorm,
    roc_bert,
    roformer,
    rwkv,
    sam,
    segformer,
    sew,
    sew_d,
    speech_encoder_decoder,
    speech_to_text,
    speech_to_text_a,
    speechta,
    splinter,
    squeezebert,
    swiftformer,
    swin,
    swinasr,
    swinva,
    switch_transformers,
    ta,
    table_transformer,
    tapas,
    time_series_transformer,
    timesformer,
    timm_backbone,
    transfo_xl,
    trocr,
    tvlt,
    umta,
    unispeech,
    unispeech_sat,
    upernet,
    videomae,
    vilt,
    vision_encoder_decoder,
    vision_text_dual_encoder,
    visual_bert,
    vit,
    vit_hybrid,
    vit_mae,
    vit_msn,
    vivit,
    wavaveca,
    wavaveca_conformer,
    wavaveca_phoneme,
    wavaveca_with_lm,
    wavlm,
    whisper,
    x_clip,
    xglm,
    xlm,
    xlm_prophetnet,
    xlm_roberta,
    xlm_roberta_xl,
    xlnet,
    xmod,
    yolos,
    yoso,
)





