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			:							Dict     =logging.get_logger(__name__)

lowerCAmelCase			:							List[str]     ={"vocab_file": "vocab.txt", "emoji_file": "emoji.json"}

lowerCAmelCase			:							Optional[Any]     ={
    "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			:							str     ={
    "abeja/gpt-neox-japanese-2.7b": 2048,
}







def 						A__  (					__A   , __A	):







    '''simple docstring'''





    with open(SCREAMING_SNAKE_CASE__   , """r"""   , encoding="""utf-8"""	) as f:
        _lowerCamelCase     :		int 						=						json.loads(f.read()	)

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

    return vocab, raw_vocab, ids_to_tokens, emoji




class 	__snake_case	( _UpperCAmelCase		):





      '''simple docstring'''






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



      def __init__(					self     :				List[Any]    ,  _UpperCamelCase     :				List[str]    ,  _UpperCamelCase     :				List[Any]    ,  _UpperCamelCase     :				List[str]="<|endoftext|>"    ,  _UpperCamelCase     :				Optional[int]="<|endoftext|>"    ,  _UpperCamelCase     :				List[str]="<|startoftext|>"    ,  _UpperCamelCase     :				Optional[int]="<|endoftext|>"    ,  _UpperCamelCase     :				Tuple=False    ,  **_UpperCamelCase     :				Dict    ,  )				->Any:


          """simple docstring"""


          super().__init__(
              unk_token=lowercase__    ,  pad_token=lowercase__    ,  bos_token=lowercase__    ,  eos_token=lowercase__    ,  do_clean_text=lowercase__    ,  **lowercase__    ,  )
          if not os.path.isfile(lowercase__):
              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(lowercase__):
              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     :		Optional[int] 						=						do_clean_text
          _lowerCamelCase     :		Union[str, Any] 						=						load_vocab_and_emoji(lowercase__    ,  lowercase__)
          _lowerCamelCase     :		Tuple 						=						SubWordJapaneseTokenizer(
              vocab=self.vocab    ,  ids_to_tokens=self.ids_to_tokens    ,  emoji=self.emoji)



      @property
      def 	_SCREAMING_SNAKE_CASE    (					self     :				List[Any])				->Dict:


          """simple docstring"""


          return len(self.raw_vocab)



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Union[str, Any])				->List[Any]:


          """simple docstring"""


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



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[int]    ,  _UpperCamelCase     :				Any)				->Union[str, Any]:


          """simple docstring"""


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



      def 	_SCREAMING_SNAKE_CASE    (					self     :				int    ,  _UpperCamelCase     :				Union[str, Any])				->Optional[int]:


          """simple docstring"""


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



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[Any]    ,  _UpperCamelCase     :				List[str])				->Optional[int]:


          """simple docstring"""


          return self.subword_tokenizer.convert_id_to_token(lowercase__)



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[Any]    ,  _UpperCamelCase     :				List[Any])				->int:


          """simple docstring"""


          _lowerCamelCase     :		Union[str, Any] 						=						"""""".join(lowercase__).strip()
          return out_string



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Dict    ,  _UpperCamelCase     :				Optional[Any])				->List[Any]:


          """simple docstring"""


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

          if len(lowercase__) > self.model_max_length:
              _lowerCamelCase     :		Dict 						=						input_ids[-self.model_max_length :]
          return input_ids




      def 	_SCREAMING_SNAKE_CASE    (					self     :				List[Any]    ,  _UpperCamelCase     :				Any    ,  _UpperCamelCase     :				Dict = None)				->Optional[Any]:


          """simple docstring"""


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





class 	__snake_case	( _UpperCAmelCase		):





      '''simple docstring'''






      def __init__(					self     :				Optional[int]    ,  _UpperCamelCase     :				Optional[Any]    ,  _UpperCamelCase     :				int    ,  _UpperCamelCase     :				int)				->str:


          """simple docstring"""


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



      def __len__(					self     :				Any)				->Optional[Any]:


          """simple docstring"""


          return len(self.ids_to_tokens)



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Union[str, Any]    ,  _UpperCamelCase     :				List[str])				->Dict:


          """simple docstring"""


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



      def 	_SCREAMING_SNAKE_CASE    (					self     :				List[Any]    ,  _UpperCamelCase     :				List[Any]    ,  _UpperCamelCase     :				Any=False)				->Union[str, Any]:


          """simple docstring"""


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

          def check_simbol(_UpperCamelCase     :				Any):
              _lowerCamelCase     :		int 						=						x.encode()
              if len(lowercase__) == 1 and len(lowercase__) == 2:
                  _lowerCamelCase     :		Tuple 						=						(int(e[0]) << 8) + int(e[1])
                  if (
                      (c >= 0xc2a1 and c <= 0xc2bf)
                      or (c >= 0xc780 and c <= 0xc783)
                      or (c >= 0xcab9 and c <= 0xcbbf)
                      or (c >= 0xcc80 and c <= 0xcda2)
                  ):
                      return True
              return False

          def checkuae(_UpperCamelCase     :				List[str]):
              _lowerCamelCase     :		int 						=						x.encode()
              if len(lowercase__) == 1 and len(lowercase__) == 3:
                  _lowerCamelCase     :		Union[str, Any] 						=						(int(e[0]) << 16) + (int(e[1]) << 8) + int(e[2])
                  if c >= 0xe2_8080 and c <= 0xe2_b07f:
                      return True
              return False

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




      def 	_SCREAMING_SNAKE_CASE    (					self     :				Tuple    ,  _UpperCamelCase     :				Optional[int]    ,  _UpperCamelCase     :				Any="\n")				->Dict:


          """simple docstring"""


          _lowerCamelCase     :		Optional[Any] 						=						[]
          _lowerCamelCase     :		Optional[Any] 						=						[]
          _lowerCamelCase     :		Dict 						=						self.ids_to_tokens[index][0]
          if word[:6] == "<|byte" and word[-2:] == "|>":
              byte_tokens.append(int(word[6:-2]))
          else:
              if len(lowercase__) > 0:
                  words.append(bytearray(lowercase__).decode("""utf-8"""    ,  errors="""replace"""))
                  _lowerCamelCase     :		Tuple 						=						[]
              if word[:7] == "<|emoji" and word[-2:] == "|>":
                  words.append(self.emoji["""emoji_inv"""][word])
              elif word == "<SP>":
                  words.append(""" """)
              elif word == "<BR>":
                  words.append(lowercase__)
              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(lowercase__)
          if len(lowercase__) > 0:
              words.append(bytearray(lowercase__).decode("""utf-8"""    ,  errors="""replace"""))
          _lowerCamelCase     :		str 						=						"""""".join(lowercase__)
          return text





from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader




class 	__snake_case	( __lowerCAmelCase		):





      '''simple docstring'''






      def __init__(					self     :				Dict    ,  _UpperCamelCase     :				NestedDataStructureLike[PathLike]    ,  _UpperCamelCase     :				Optional[NamedSplit] = None    ,  _UpperCamelCase     :				Optional[Features] = None    ,  _UpperCamelCase     :				str = None    ,  _UpperCamelCase     :				bool = False    ,  _UpperCamelCase     :				bool = False    ,  _UpperCamelCase     :				Optional[int] = None    ,  **_UpperCamelCase     :				Tuple    ,  )				->Union[str, Any]:


          """simple docstring"""


          super().__init__(
              _UpperCamelCase    ,  split=_UpperCamelCase    ,  features=_UpperCamelCase    ,  cache_dir=_UpperCamelCase    ,  keep_in_memory=_UpperCamelCase    ,  streaming=_UpperCamelCase    ,  num_proc=_UpperCamelCase    ,  **_UpperCamelCase    ,  )
          _lowerCamelCase     :		List[Any] 						=						path_or_paths if isinstance(_UpperCamelCase    ,  _UpperCamelCase) else {self.split: path_or_paths}
          _lowerCamelCase     :		Any 						=						Text(
              cache_dir=_UpperCamelCase    ,  data_files=_UpperCamelCase    ,  features=_UpperCamelCase    ,  **_UpperCamelCase    ,  )




      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[Any])				->Optional[Any]:


          """simple docstring"""


          if self.streaming:
              _lowerCamelCase     :		Tuple 						=						self.builder.as_streaming_dataset(split=self.split)
          # Build regular (map-style) dataset
          else:
              _lowerCamelCase     :		List[Any] 						=						None
              _lowerCamelCase     :		Any 						=						None
              _lowerCamelCase     :		List[str] 						=						None
              _lowerCamelCase     :		Dict 						=						None

              self.builder.download_and_prepare(
                  download_config=_UpperCamelCase    ,  download_mode=_UpperCamelCase    ,  verification_mode=_UpperCamelCase    ,  base_path=_UpperCamelCase    ,  num_proc=self.num_proc    ,  )
              _lowerCamelCase     :		Optional[int] 						=						self.builder.as_dataset(
                  split=self.split    ,  verification_mode=_UpperCamelCase    ,  in_memory=self.keep_in_memory)
          return dataset




