






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

import regex as re

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


UpperCamelCase    							=      logging.get_logger(__name__)


UpperCamelCase    							=      {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

UpperCamelCase    							=      {
    'vocab_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'
    },
    'merges_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'
    },
    'tokenizer_config_file': {
        'facebook/blenderbot_small-90M': (
            'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'
        )
    },
}

UpperCamelCase    							=      {'facebook/blenderbot_small-90M': 512}


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

   __UpperCamelCase	:			Optional[Any]					=					set(__lowerCAmelCase							)
   return pairs







class 		_A						( UpperCAmelCase_ ):
  lowercase_						:			Any						=					VOCAB_FILES_NAMES
  lowercase_						:			Dict						=					PRETRAINED_VOCAB_FILES_MAP
  lowercase_						:			List[Any]						=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowercase_						:			Optional[int]						=					['''input_ids''', '''attention_mask''']

  def __init__(    self						:	Dict   ,				lowerCamelCase__						:	str   ,				lowerCamelCase__						:	List[Any]   ,				lowerCamelCase__						:	Optional[int]="__start__"   ,				lowerCamelCase__						:	List[str]="__end__"   ,				lowerCamelCase__						:	List[Any]="__unk__"   ,				lowerCamelCase__						:	int="__null__"   ,				**lowerCamelCase__						:	Union[str, Any]   ,				):
     """simple docstring"""

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

     with open(lowerCamelCase__   ,				encoding="""utf-8"""			) as vocab_handle:
        __UpperCamelCase	:			int					=					json.load(lowerCamelCase__			)
     __UpperCamelCase	:			Optional[Any]					=					{v: k for k, v in self.encoder.items()}
     with open(lowerCamelCase__   ,				encoding="""utf-8"""			) as merges_handle:
        __UpperCamelCase	:			List[Any]					=					merges_handle.read().split("""\n"""			)[1:-1]
     __UpperCamelCase	:			Optional[Any]					=					[tuple(merge.split()			) for merge in merges]
     __UpperCamelCase	:			Tuple					=					dict(zip(lowerCamelCase__   ,				range(len(lowerCamelCase__			)			)			)			)
     __UpperCamelCase	:			Dict					=					{}

  @property
  def    a					(    self						:	Optional[Any]			):
     """simple docstring"""

     return len(self.encoder			)

  def    a					(    self						:	List[str]			):
     """simple docstring"""

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

  def    a					(    self						:	int   ,				lowerCamelCase__						:	str			):
     """simple docstring"""

     if token in self.cache:
        return self.cache[token]
     __UpperCamelCase	:			Optional[Any]					=					re.sub("""([.,!?()])"""   ,				R""" \1"""   ,				lowerCamelCase__			)
     __UpperCamelCase	:			str					=					re.sub("""(')"""   ,				R""" \1 """   ,				lowerCamelCase__			)
     __UpperCamelCase	:			Union[str, Any]					=					re.sub(R"""\s{2,}"""   ,				""" """   ,				lowerCamelCase__			)
     if "\n" in token:
        __UpperCamelCase	:			Union[str, Any]					=					token.replace("""\n"""   ,				""" __newln__"""			)

     __UpperCamelCase	:			Optional[int]					=					token.split(""" """			)
     __UpperCamelCase	:			Any					=					[]
     for token in tokens:
        if not len(lowerCamelCase__			):
           continue

        __UpperCamelCase	:			Optional[int]					=					token.lower()
        __UpperCamelCase	:			Optional[int]					=					tuple(lowerCamelCase__			)
        __UpperCamelCase	:			str					=					tuple(list(word[:-1]			) + [word[-1] + """</w>"""]			)
        __UpperCamelCase	:			Dict					=					get_pairs(lowerCamelCase__			)

        if not pairs:
           words.append(lowerCamelCase__			)
           continue

        while True:
           __UpperCamelCase	:			Tuple					=					min(lowerCamelCase__   ,				key=lambda lowerCamelCase__			: self.bpe_ranks.get(lowerCamelCase__   ,				float("""inf"""			)			)			)
           if bigram not in self.bpe_ranks:
              break
           __UpperCamelCase	,     __UpperCamelCase	:			Dict					=					bigram
           __UpperCamelCase	:			Optional[Any]					=					[]
           __UpperCamelCase	:			Optional[int]					=					0

           while i < len(lowerCamelCase__			):
              try:
                 __UpperCamelCase	:			Any					=					word.index(lowerCamelCase__   ,				lowerCamelCase__			)
                 new_word.extend(word[i:j]			)
                 __UpperCamelCase	:			Optional[int]					=					j
              except ValueError:
                 new_word.extend(word[i:]			)
                 break

              if word[i] == first and i < len(lowerCamelCase__			) - 1 and word[i + 1] == second:
                 new_word.append(first + second			)
                 i += 2
              else:
                 new_word.append(word[i]			)
                 i += 1
           __UpperCamelCase	:			str					=					tuple(lowerCamelCase__			)
           __UpperCamelCase	:			Tuple					=					new_word
           if len(lowerCamelCase__			) == 1:
              break
           else:
              __UpperCamelCase	:			List[Any]					=					get_pairs(lowerCamelCase__			)
        __UpperCamelCase	:			Tuple					=					"""@@ """.join(lowerCamelCase__			)
        __UpperCamelCase	:			Tuple					=					word[:-4]

        __UpperCamelCase	:			Tuple					=					word
        words.append(lowerCamelCase__			)
     return " ".join(lowerCamelCase__			)

  def    a					(    self						:	Tuple   ,				lowerCamelCase__						:	str			):
     """simple docstring"""

     __UpperCamelCase	:			Any					=					[]

     __UpperCamelCase	:			Any					=					re.findall(R"""\S+\n?"""   ,				lowerCamelCase__			)

     for token in words:
        split_tokens.extend(list(self.bpe(lowerCamelCase__			).split(""" """			)			)			)
     return split_tokens

  def    a					(    self						:	Union[str, Any]   ,				lowerCamelCase__						:	str			):
     """simple docstring"""

     __UpperCamelCase	:			Union[str, Any]					=					token.lower()
     return self.encoder.get(lowerCamelCase__   ,				self.encoder.get(self.unk_token			)			)

  def    a					(    self						:	Optional[int]   ,				lowerCamelCase__						:	int			):
     """simple docstring"""

     return self.decoder.get(lowerCamelCase__   ,				self.unk_token			)

  def    a					(    self						:	int   ,				lowerCamelCase__						:	List[str]			):
     """simple docstring"""

     __UpperCamelCase	:			Tuple					=					""" """.join(lowerCamelCase__			).replace("""@@ """   ,				""""""			).strip()
     return out_string

  def    a					(    self						:	List[str]   ,				lowerCamelCase__						:	str   ,				lowerCamelCase__						:	Optional[str] = None			):
     """simple docstring"""

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

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

     __UpperCamelCase	:			int					=					0
     with open(lowerCamelCase__   ,				"""w"""   ,				encoding="""utf-8"""			) as writer:
        writer.write("""#version: 0.2\n"""			)
        for bpe_tokens, token_index in sorted(self.bpe_ranks.items()   ,				key=lambda lowerCamelCase__			: kv[1]			):
           if index != token_index:
              logger.warning(
                  f'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
                  """ Please check that the tokenizer is not corrupted!"""			)
              __UpperCamelCase	:			Dict					=					token_index
           writer.write(""" """.join(lowerCamelCase__			) + """\n"""			)
           index += 1

     return vocab_file, merge_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,
)



