





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


_lowerCamelCase      							=   logging.get_logger(__name__)

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

_lowerCamelCase      							=   {
    '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',
    },
}

_lowerCamelCase      							=   {
    'abeja/gpt-neox-japanese-2.7b': 2048,
}




def  __UpperCAmelCase(   lowercase_			,     lowercase_   ):
       with open(lowercase_			,     '''r'''			,     encoding='''utf-8'''   ) as f:
              _lowerCamelCase				:  Union[str, Any]						=		json.loads(f.read()   )

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

       return vocab, raw_vocab, ids_to_tokens, emoji







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__   ,				a__="<|endoftext|>"   ,				a__="<|endoftext|>"   ,				a__="<|startoftext|>"   ,				a__="<|endoftext|>"   ,				a__=False   ,				**a__   ,				):



             """simple docstring"""





             super().__init__(
                 unk_token=a__   ,				pad_token=a__   ,				bos_token=a__   ,				eos_token=a__   ,				do_clean_text=a__   ,				**a__   ,				)
             if not os.path.isfile(a__):
                    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(a__):
                    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)`''')
             _lowerCamelCase				:  Dict						=		do_clean_text
             _lowerCamelCase,	_lowerCamelCase,	_lowerCamelCase,	_lowerCamelCase				:  Union[str, Any]						=		load_vocab_and_emoji(a__   ,				a__)
             _lowerCamelCase				:  Union[str, Any]						=		SubWordJapaneseTokenizer(
                 vocab=self.vocab   ,				ids_to_tokens=self.ids_to_tokens   ,				emoji=self.emoji)


      @property
      def 					__snake_case      (		self):



             """simple docstring"""





             return len(self.raw_vocab)


      def 					__snake_case      (		self):



             """simple docstring"""





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


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





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


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





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


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





             return self.subword_tokenizer.convert_id_to_token(a__)


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





             _lowerCamelCase				:  int						=		''''''.join(a__).strip()
             return out_string


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





             _lowerCamelCase				:  List[str]						=		[]
             for is_user, text in conversation.iter_texts():
                    input_ids.extend(self.encode(a__   ,				add_special_tokens=a__) + [self.eos_token_id])

             if len(a__) > self.model_max_length:
                    _lowerCamelCase				:  Optional[Any]						=		input_ids[-self.model_max_length :]
             return input_ids



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



             """simple docstring"""





             _lowerCamelCase				:  Optional[Any]						=		0
             if os.path.isdir(a__):
                    _lowerCamelCase				:  Tuple						=		os.path.join(
                        a__   ,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])
                    _lowerCamelCase				:  List[Any]						=		os.path.join(
                        a__   ,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''emoji_file'''])
             else:
                    _lowerCamelCase				:  Optional[int]						=		(
                        (filename_prefix + '''-''' if filename_prefix else '''''') + save_directory + VOCAB_FILES_NAMES['''vocab_file''']
                    )
                    _lowerCamelCase				:  str						=		(
                        (filename_prefix + '''-''' if filename_prefix else '''''') + save_directory + VOCAB_FILES_NAMES['''emoji_file''']
                    )
             with open(a__   ,				'''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!''')
                                  _lowerCamelCase				:  Any						=		token_index
                           writer.write(''','''.join(a__) + '''\n''')
                           index += 1
             with open(a__   ,				'''w'''   ,				encoding='''utf-8''') as writer:
                    json.dump(self.emoji   ,				a__)
             return vocab_file, emoji_file







class       __A							(   lowerCamelCase__	):




      """simple docstring"""







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



             """simple docstring"""





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


      def __len__(		self):



             """simple docstring"""





             return len(self.ids_to_tokens)


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





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


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



             """simple docstring"""





             _lowerCamelCase				:  Optional[int]						=		text.replace(''' '''   ,				'''<SP>''')
             _lowerCamelCase				:  Union[str, Any]						=		text.replace('''　'''   ,				'''<SP>''')
             _lowerCamelCase				:  Dict						=		text.replace('''\r\n'''   ,				'''<BR>''')
             _lowerCamelCase				:  Tuple						=		text.replace('''\n'''   ,				'''<BR>''')
             _lowerCamelCase				:  Optional[Any]						=		text.replace('''\r'''   ,				'''<BR>''')
             _lowerCamelCase				:  Optional[Any]						=		text.replace('''\t'''   ,				'''<TAB>''')
             _lowerCamelCase				:  List[Any]						=		text.replace('''—'''   ,				'''ー''')
             _lowerCamelCase				:  List[str]						=		text.replace('''−'''   ,				'''ー''')
             for k, v in self.emoji["emoji"].items():
                    if k in text:
                           _lowerCamelCase				:  Optional[int]						=		text.replace(a__   ,				a__)
             if clean:
                    _lowerCamelCase				:  str						=		self.clean_text(a__)

             def check_simbol(a__):
                    _lowerCamelCase				:  List[Any]						=		x.encode()
                    if len(a__) == 1 and len(a__) == 2:
                           _lowerCamelCase				:  Optional[int]						=		(int(e[0]) << 8) + int(e[1])
                           if (
                               (c >= 0Xc_2_a_1 and c <= 0Xc_2_b_f)
                               or (c >= 0Xc_7_8_0 and c <= 0Xc_7_8_3)
                               or (c >= 0Xc_a_b_9 and c <= 0Xc_b_b_f)
                               or (c >= 0Xc_c_8_0 and c <= 0Xc_d_a_2)
                           ):
                                  return True
                    return False

             def checkuae(a__):
                    _lowerCamelCase				:  Optional[Any]						=		x.encode()
                    if len(a__) == 1 and len(a__) == 3:
                           _lowerCamelCase				:  List[Any]						=		(int(e[0]) << 16) + (int(e[1]) << 8) + int(e[2])
                           if c >= 0Xe_2_8_0_8_0 and c <= 0Xe_2_b_0_7_f:
                                  return True
                    return False

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



      def 					__snake_case      (		self   ,				a__   ,				a__="\n"):



             """simple docstring"""





             _lowerCamelCase				:  Union[str, Any]						=		[]
             _lowerCamelCase				:  str						=		[]
             _lowerCamelCase				:  List[Any]						=		self.ids_to_tokens[index][0]
             if word[:6] == "<|byte" and word[-2:] == "|>":
                    byte_tokens.append(int(word[6:-2]))
             else:
                    if len(a__) > 0:
                           words.append(bytearray(a__).decode('''utf-8'''   ,				errors='''replace'''))
                           _lowerCamelCase				:  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(a__)
                    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(a__)
             if len(a__) > 0:
                    words.append(bytearray(a__).decode('''utf-8'''   ,				errors='''replace'''))
             _lowerCamelCase				:  Any						=		''''''.join(a__)
             return text








from __future__ import annotations




def  __UpperCAmelCase(   lowercase_			,     lowercase_ = None			,     lowercase_ = None			,     lowercase_ = False			,     ):
       _lowerCamelCase				:  Tuple						=		cipher_alphabet or [chr(lowercase_   ) for i in range(97			,     1_23   )]

       # If the argument is None or the user provided an empty dictionary
       if not frequencies_dict:
              # Frequencies of letters in the english language (how much they show up)
              _lowerCamelCase				:  Dict						=		{
                  '''a''': 0.0_8_4_9_7,
                  '''b''': 0.0_1_4_9_2,
                  '''c''': 0.0_2_2_0_2,
                  '''d''': 0.0_4_2_5_3,
                  '''e''': 0.1_1_1_6_2,
                  '''f''': 0.0_2_2_2_8,
                  '''g''': 0.0_2_0_1_5,
                  '''h''': 0.0_6_0_9_4,
                  '''i''': 0.0_7_5_4_6,
                  '''j''': 0.0_0_1_5_3,
                  '''k''': 0.0_1_2_9_2,
                  '''l''': 0.0_4_0_2_5,
                  '''m''': 0.0_2_4_0_6,
                  '''n''': 0.0_6_7_4_9,
                  '''o''': 0.0_7_5_0_7,
                  '''p''': 0.0_1_9_2_9,
                  '''q''': 0.0_0_0_9_5,
                  '''r''': 0.0_7_5_8_7,
                  '''s''': 0.0_6_3_2_7,
                  '''t''': 0.0_9_3_5_6,
                  '''u''': 0.0_2_7_5_8,
                  '''v''': 0.0_0_9_7_8,
                  '''w''': 0.0_2_5_6_0,
                  '''x''': 0.0_0_1_5_0,
                  '''y''': 0.0_1_9_9_4,
                  '''z''': 0.0_0_0_7_7,
              }
       else:
              # Custom frequencies dictionary
              _lowerCamelCase				:  Tuple						=		frequencies_dict

       if not case_sensitive:
              _lowerCamelCase				:  Optional[int]						=		ciphertext.lower()

       # Chi squared statistic values
       _lowerCamelCase				:  dict[int, tuple[float, str]]						=		{}

       # cycle through all of the shifts
       for shift in range(len(lowercase_   )   ):
              _lowerCamelCase				:  Any						=		''''''

              # decrypt the message with the shift
              for letter in ciphertext:
                     try:
                            # Try to index the letter in the alphabet
                            _lowerCamelCase				:  int						=		(alphabet_letters.index(letter.lower()   ) - shift) % len(
                                lowercase_   )
                            decrypted_with_shift += (
                                alphabet_letters[new_key].upper()
                                if case_sensitive and letter.isupper()
                                else alphabet_letters[new_key]
                            )
                     except ValueError:
                            # Append the character if it isn't in the alphabet
                            decrypted_with_shift += letter

              _lowerCamelCase				:  Optional[Any]						=		0.0

              # Loop through each letter in the decoded message with the shift
              for letter in decrypted_with_shift:
                     if case_sensitive:
                            _lowerCamelCase				:  Any						=		letter.lower()
                            if letter in frequencies:
                                   # Get the amount of times the letter occurs in the message
                                   _lowerCamelCase				:  List[str]						=		decrypted_with_shift.lower().count(lowercase_   )

                                   # Get the excepcted amount of times the letter should appear based
                                   # on letter frequencies
                                   _lowerCamelCase				:  Optional[Any]						=		frequencies[letter] * occurrences

                                   # Complete the chi squared statistic formula
                                   _lowerCamelCase				:  int						=		((occurrences - expected) ** 2) / expected

                                   # Add the margin of error to the total chi squared statistic
                                   chi_squared_statistic += chi_letter_value
                     else:
                            if letter.lower() in frequencies:
                                   # Get the amount of times the letter occurs in the message
                                   _lowerCamelCase				:  Union[str, Any]						=		decrypted_with_shift.count(lowercase_   )

                                   # Get the excepcted amount of times the letter should appear based
                                   # on letter frequencies
                                   _lowerCamelCase				:  List[str]						=		frequencies[letter] * occurrences

                                   # Complete the chi squared statistic formula
                                   _lowerCamelCase				:  str						=		((occurrences - expected) ** 2) / expected

                                   # Add the margin of error to the total chi squared statistic
                                   chi_squared_statistic += chi_letter_value

        # Add the data to the chi_squared_statistic_values dictionary
              _lowerCamelCase				:  Tuple						=		(
                  chi_squared_statistic,
                  decrypted_with_shift,
              )

       # Get the most likely cipher by finding the cipher with the smallest chi squared
       # statistic
       def chi_squared_statistic_values_sorting_key(lowercase_   ) -> tuple[float, str]:
              return chi_squared_statistic_values[key]

       _lowerCamelCase				:  int						=		min(
           lowercase_			,     key=lowercase_			,     )

       # Get all the data from the most likely cipher (key, decoded message)
       (
           (
           _lowerCamelCase
       ),	(
           _lowerCamelCase
       ),	
       )				:  Optional[int]						=		chi_squared_statistic_values[most_likely_cipher]

       # Return the data on the most likely shift
       return (
           most_likely_cipher,
           most_likely_cipher_chi_squared_value,
           decoded_most_likely_cipher,
       )

