

import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple

import numpy as np

from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
    from transformers.pipelines.conversational import Conversation


_snake_case         =  logging.get_logger(__name__)

_snake_case         =  {'vocab_file': 'vocab.txt', 'emoji_file': 'emoji.json'}

_snake_case         =  {
    'vocab_file': {
        'abeja/gpt-neox-japanese-2.7b': 'https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/vocab.txt',
    },
    'emoji_file': {
        'abeja/gpt-neox-japanese-2.7b': 'https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/emoji.json',
    },
}

_snake_case         =  {
    'abeja/gpt-neox-japanese-2.7b': 2_048,
}







def  _A		(     snake_case		,							snake_case					)      ->     List[str]:
   with open(snake_case		,							"r"		,							encoding="utf-8"					) as f:
      _lowercase      :				Optional[int]      					=       json.loads(f.read()					)

   _lowercase      :				Union[str, Any]      					=       collections.OrderedDict()
   _lowercase      :				Optional[Any]      					=       collections.OrderedDict()
   _lowercase      :				List[str]      					=       collections.OrderedDict()
   with open(snake_case		,							"r"		,							encoding="utf-8"					) as f:
      _lowercase      :				Union[str, Any]      					=       f.readlines()
   _lowercase      :				Tuple      					=       [[t.rstrip("\n"					)] if (t == "," or "," not in t) else t.rstrip("\n"					).split(","					) for t in token]
   for idx, b in enumerate(snake_case					):
      _lowercase      :				Dict      					=       b
      _lowercase      :				Dict      					=       idx
      for wd in b:
         _lowercase      :				str      					=       idx

   return vocab, raw_vocab, ids_to_tokens, emoji


class        a__  (							lowerCamelCase_  ):
   _SCREAMING_SNAKE_CASE   :					str     	=							VOCAB_FILES_NAMES
   _SCREAMING_SNAKE_CASE   :					List[Any]     	=							PRETRAINED_VOCAB_FILES_MAP
   _SCREAMING_SNAKE_CASE   :					Optional[int]     	=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _SCREAMING_SNAKE_CASE   :					str     	=							['input_ids', 'attention_mask']


   def __init__(			self      ,    _UpperCamelCase      ,    _UpperCamelCase      ,    _UpperCamelCase="<|endoftext|>"      ,    _UpperCamelCase="<|endoftext|>"      ,    _UpperCamelCase="<|startoftext|>"      ,    _UpperCamelCase="<|endoftext|>"      ,    _UpperCamelCase=False      ,    **_UpperCamelCase      ,    ):





      """simple docstring"""





      super().__init__(
          unk_token=_UpperCamelCase      ,    pad_token=_UpperCamelCase      ,    bos_token=_UpperCamelCase      ,    eos_token=_UpperCamelCase      ,    do_clean_text=_UpperCamelCase      ,    **_UpperCamelCase      ,    )
      if not os.path.isfile(_UpperCamelCase  ):
         raise ValueError(
             f'''Can\'t find a vocabulary file at path \'{vocab_file}\'. To load the vocabulary from a Google pretrained'''
             " model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`"  )
      if not os.path.isfile(_UpperCamelCase  ):
         raise ValueError(
             f'''Can\'t find a emoji file at path \'{emoji_file}\'. To load the emoji information from a Google'''
             " pretrained model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`"  )
      _lowercase      :				Tuple      					=       do_clean_text
      _lowercase      :				List[Any]      					=       load_vocab_and_emoji(_UpperCamelCase      ,    _UpperCamelCase  )
      _lowercase      :				str      					=       SubWordJapaneseTokenizer(
          vocab=self.vocab      ,    ids_to_tokens=self.ids_to_tokens      ,    emoji=self.emoji  )


   @property
   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      return len(self.raw_vocab  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





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


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      return self.subword_tokenizer.tokenize(_UpperCamelCase      ,    clean=self.do_clean_text  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      return self.vocab.get(_UpperCamelCase      ,    self.vocab.get(self.unk_token  )  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      return self.subword_tokenizer.convert_id_to_token(_UpperCamelCase  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				int      					=       "".join(_UpperCamelCase  ).strip()
      return out_string


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				Any      					=       []
      for is_user, text in conversation.iter_texts():
         input_ids.extend(self.encode(_UpperCamelCase      ,    add_special_tokens=_UpperCamelCase  ) + [self.eos_token_id]  )

      if len(_UpperCamelCase  ) > self.model_max_length:
         _lowercase      :				str      					=       input_ids[-self.model_max_length :]
      return input_ids






   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None  ):





      """simple docstring"""





      _lowercase      :				Optional[int]      					=       0
      if os.path.isdir(_UpperCamelCase  ):
         _lowercase      :				Tuple      					=       os.path.join(
             _UpperCamelCase      ,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]  )
         _lowercase      :				List[str]      					=       os.path.join(
             _UpperCamelCase      ,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["emoji_file"]  )
      else:
         _lowercase      :				int      					=       (
             (filename_prefix + "-" if filename_prefix else "") + save_directory + VOCAB_FILES_NAMES["vocab_file"]
         )
         _lowercase      :				Tuple      					=       (
             (filename_prefix + "-" if filename_prefix else "") + save_directory + VOCAB_FILES_NAMES["emoji_file"]
         )
      with open(_UpperCamelCase      ,    "w"      ,    encoding="utf-8"  ) as writer:
         for token_index, token in self.ids_to_tokens.items():
            if index != token_index:
               logger.warning(
                   f'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
                   " Please check that the vocabulary is not corrupted!"  )
               _lowercase      :				List[Any]      					=       token_index
            writer.write(",".join(_UpperCamelCase  ) + "\n"  )
            index += 1
      with open(_UpperCamelCase      ,    "w"      ,    encoding="utf-8"  ) as writer:
         json.dump(self.emoji      ,    _UpperCamelCase  )
      return vocab_file, emoji_file




class        a__  (							lowerCamelCase_  ):


   def __init__(			self      ,    _UpperCamelCase      ,    _UpperCamelCase      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				Tuple      					=       vocab  # same as swe
      _lowercase      :				int      					=       ids_to_tokens  # same as bpe
      _lowercase      :				Dict      					=       emoji
      _lowercase      :				List[str]      					=       np.max([len(_UpperCamelCase  ) for w in self.vocab.keys()]  )
      _lowercase      :				Dict      					=       re.compile(R"(https?|ftp)(:\/\/[-_\.!~*\'()a-zA-Z0-9;\/?:\@&=\+$,%#]+)"  )
      _lowercase      :				Optional[Any]      					=       re.compile(R"[A-Za-z0-9\._+]*@[\-_0-9A-Za-z]+(\.[A-Za-z]+)*"  )
      _lowercase      :				str      					=       re.compile(R"[\(]{0,1}[0-9]{2,4}[\)\-\(]{0,1}[0-9]{2,4}[\)\-]{0,1}[0-9]{3,4}"  )
      _lowercase      :				List[str]      					=       re.compile(
          R"([12]\d{3}[/\-年])*(0?[1-9]|1[0-2])[/\-月]((0?[1-9]|[12][0-9]|3[01])日?)*(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*"  )
      _lowercase      :				Any      					=       re.compile(
          R"(明治|大正|昭和|平成|令和|㍾|㍽|㍼|㍻|\u32ff)\d{1,2}年(0?[1-9]|1[0-2])月(0?[1-9]|[12][0-9]|3[01])日(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*"  )
      _lowercase      :				Dict      					=       re.compile(
          R"((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*億)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*万)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*千)*(0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*(千円|万円|千万円|円|千ドル|万ドル|千万ドル|ドル|千ユーロ|万ユーロ|千万ユーロ|ユーロ)+(\(税込\)|\(税抜\)|\+tax)*"  )
      _lowercase      :				str      					=       "─━│┃┄┅┆┇┈┉┊┋┌┍┎┏┐┑┒┓└┕┖┗┘┙┚┛├┝┞┟┠┡┢┣┤┥┦┧┨┩┪┫┬┭┮┯┰┱┲┳┴┵┶┷┸┹┺┻┼┽┾┿╀╁╂╃╄╅╆╇╈╉╊╋╌╍╎╏═║╒╓╔╕╖╗╘╙╚╛╜╝╞╟╠╡╢╣╤╥╦╧╨╩╪╫╬╭╮╯╰╱╲╳╴╵╶╷╸╹╺╻╼╽╾╿"
      _lowercase      :				Optional[int]      					=       "▀▁▂▃▄▅▆▇█▉▊▋▌▍▎▏▐░▒▓▔▕▖▗▘▙▚▛▜▝▞▟"
      _lowercase      :				List[str]      					=       str.maketrans({k: "<BLOCK>" for k in keisen + blocks}  )


   def __len__(			self  ):





      """simple docstring"""





      return len(self.ids_to_tokens  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				List[Any]      					=       self.content_repattera.sub("<URL>"      ,    _UpperCamelCase  )
      _lowercase      :				Dict      					=       self.content_repattera.sub("<EMAIL>"      ,    _UpperCamelCase  )
      _lowercase      :				Tuple      					=       self.content_repattera.sub("<TEL>"      ,    _UpperCamelCase  )
      _lowercase      :				List[Any]      					=       self.content_repattera.sub("<DATE>"      ,    _UpperCamelCase  )
      _lowercase      :				Tuple      					=       self.content_repattera.sub("<DATE>"      ,    _UpperCamelCase  )
      _lowercase      :				Optional[int]      					=       self.content_repattera.sub("<PRICE>"      ,    _UpperCamelCase  )
      _lowercase      :				List[str]      					=       content.translate(self.content_transa  )
      while "<BLOCK><BLOCK>" in content:
         _lowercase      :				str      					=       content.replace("<BLOCK><BLOCK>"      ,    "<BLOCK>"  )
      return content


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase=False  ):





      """simple docstring"""





      _lowercase      :				Union[str, Any]      					=       text.replace(" "      ,    "<SP>"  )
      _lowercase      :				int      					=       text.replace("　"      ,    "<SP>"  )
      _lowercase      :				int      					=       text.replace("\r\n"      ,    "<BR>"  )
      _lowercase      :				List[str]      					=       text.replace("\n"      ,    "<BR>"  )
      _lowercase      :				Optional[Any]      					=       text.replace("\r"      ,    "<BR>"  )
      _lowercase      :				Union[str, Any]      					=       text.replace("\t"      ,    "<TAB>"  )
      _lowercase      :				List[str]      					=       text.replace("—"      ,    "ー"  )
      _lowercase      :				int      					=       text.replace("−"      ,    "ー"  )
      for k, v in self.emoji["emoji"].items():
         if k in text:
            _lowercase      :				List[Any]      					=       text.replace(_UpperCamelCase      ,    _UpperCamelCase  )
      if clean:
         _lowercase      :				int      					=       self.clean_text(_UpperCamelCase  )

      def check_simbol(_UpperCamelCase  ):
         _lowercase      :				Optional[int]      					=       x.encode()
         if len(_UpperCamelCase  ) == 1 and len(_UpperCamelCase  ) == 2:
            _lowercase      :				List[Any]      					=       (int(e[0]  ) << 8) + int(e[1]  )
            if (
                (c >= 0XC2_A1 and c <= 0XC2_BF)
                or (c >= 0XC7_80 and c <= 0XC7_83)
                or (c >= 0XCA_B9 and c <= 0XCB_BF)
                or (c >= 0XCC_80 and c <= 0XCD_A2)
            ):
               return True
         return False

      def checkuae(_UpperCamelCase  ):
         _lowercase      :				Any      					=       x.encode()
         if len(_UpperCamelCase  ) == 1 and len(_UpperCamelCase  ) == 3:
            _lowercase      :				Dict      					=       (int(e[0]  ) << 16) + (int(e[1]  ) << 8) + int(e[2]  )
            if c >= 0XE2_80_80 and c <= 0XE2_B0_7F:
               return True
         return False

      _lowercase      :				Optional[int]      					=       0
      _lowercase      :				Optional[int]      					=       []
      while pos < len(_UpperCamelCase  ):
         _lowercase      :				Dict      					=       min(len(_UpperCamelCase  )      ,    pos + self.maxlen + 1  ) if text[pos] == "<" else pos + 3
         _lowercase      :				List[str]      					=       []  # (token_id, token, pos)
         for e in range(_UpperCamelCase      ,    _UpperCamelCase      ,    -1  ):
            _lowercase      :				Optional[int]      					=       text[pos:e]
            if wd in self.vocab:
               if wd[0] == "<" and len(_UpperCamelCase  ) > 2:
                  _lowercase      :				Optional[int]      					=       [(self.vocab[wd], wd, e)]
                  break
               else:
                  candidates.append((self.vocab[wd], wd, e)  )
         if len(_UpperCamelCase  ) > 0:
            # the smallest token_id is adopted
            _lowercase      :				Union[str, Any]      					=       sorted(_UpperCamelCase      ,    key=lambda _UpperCamelCase  : x[0]  )[0]
            result.append(_UpperCamelCase  )
            _lowercase      :				List[Any]      					=       e
         else:
            _lowercase      :				Optional[Any]      					=       pos + 1
            _lowercase      :				Any      					=       text[pos:end]
            if check_simbol(_UpperCamelCase  ):
               result.append("<KIGOU>"  )
            elif checkuae(_UpperCamelCase  ):
               result.append("<U2000U2BFF>"  )
            else:
               for i in wd.encode("utf-8"  ):
                  result.append("<|byte%d|>" % i  )
            _lowercase      :				int      					=       end
      return result






   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase="\n"  ):





      """simple docstring"""





      _lowercase      :				Dict      					=       []
      _lowercase      :				List[str]      					=       []
      _lowercase      :				int      					=       self.ids_to_tokens[index][0]
      if word[:6] == "<|byte" and word[-2:] == "|>":
         byte_tokens.append(int(word[6:-2]  )  )
      else:
         if len(_UpperCamelCase  ) > 0:
            words.append(bytearray(_UpperCamelCase  ).decode("utf-8"      ,    errors="replace"  )  )
            _lowercase      :				int      					=       []
         if word[:7] == "<|emoji" and word[-2:] == "|>":
            words.append(self.emoji["emoji_inv"][word]  )
         elif word == "<SP>":
            words.append(" "  )
         elif word == "<BR>":
            words.append(_UpperCamelCase  )
         elif word == "<TAB>":
            words.append("\t"  )
         elif word == "<BLOCK>":
            words.append("▀"  )
         elif word == "<KIGOU>":
            words.append("ǀ"  )
         elif word == "<U2000U2BFF>":
            words.append("‖"  )
         else:
            words.append(_UpperCamelCase  )
      if len(_UpperCamelCase  ) > 0:
         words.append(bytearray(_UpperCamelCase  ).decode("utf-8"      ,    errors="replace"  )  )
      _lowercase      :				Optional[Any]      					=       "".join(_UpperCamelCase  )
      return text









'''simple docstring'''
import warnings

from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor


_snake_case         =  logging.get_logger(__name__)


class        a__  (							lowerCamelCase_  ):


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





      """simple docstring"""





      warnings.warn(
          "The class ChineseCLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
          " Please use ChineseCLIPImageProcessor instead."      ,    _UpperCamelCase      ,    )
      super().__init__(*_UpperCamelCase      ,    **_UpperCamelCase  )






