
"""simple docstring"""




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


_A			:       List[Any]   		=       logging.get_logger(__name__)

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

_A			:       int   		=       {
    """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""",
    },
}

_A			:       Union[str, Any]   		=       {
    """abeja/gpt-neox-japanese-2.7b""": 20_48,
}


def   __magic_name__	(      __snake_case				:       int     , __snake_case				:       List[str]  ) ->				Optional[Any]:
       with open(__snake_case     , "r"     , encoding="utf-8"  ) as f:
              lowercase    :				Optional[Any]       		=							json.loads(f.read()  )

       lowercase    :				List[Any]       		=							collections.OrderedDict()
       lowercase    :				Optional[int]       		=							collections.OrderedDict()
       lowercase    :				Any       		=							collections.OrderedDict()
       with open(__snake_case     , "r"     , encoding="utf-8"  ) as f:
              lowercase    :				Optional[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    :				int       		=							b
              lowercase    :				Optional[int]       		=							idx
              for wd in b:
                     lowercase    :				int       		=							idx

       return vocab, raw_vocab, ids_to_tokens, emoji

class 		a__						(      a_						):
   __lowerCAmelCase            =				VOCAB_FILES_NAMES
   __lowerCAmelCase            =				PRETRAINED_VOCAB_FILES_MAP
   __lowerCAmelCase            =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __lowerCAmelCase            =				["""input_ids""", """attention_mask"""]
   def __init__(			self	,    _a	,    _a	,    _a="<|endoftext|>"	,    _a="<|endoftext|>"	,    _a="<|startoftext|>"	,    _a="<|endoftext|>"	,    _a=False	,    **_a	,    ):
          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)`"				)
          lowercase    :				Optional[Any]       		=							do_clean_text
          lowercase		,    lowercase		,    lowercase		,    lowercase    :				Tuple       		=							load_vocab_and_emoji(_a	,    _a				)
          lowercase    :				Any       		=							SubWordJapaneseTokenizer(
              vocab=self.vocab	,    ids_to_tokens=self.ids_to_tokens	,    emoji=self.emoji				)
   @property
   def 			__magic_name__			(			self				):
          # self.vocab contains support for character fluctuation unique to Japanese, and has a large number of vocab
          return len(self.raw_vocab				)
   def 			__magic_name__			(			self				):
          return dict(self.raw_vocab	,    **self.added_tokens_encoder				)
   def 			__magic_name__			(			self	,    _a				):
          return self.subword_tokenizer.tokenize(_a	,    clean=self.do_clean_text				)
   def 			__magic_name__			(			self	,    _a				):
          return self.vocab.get(_a	,    self.vocab.get(self.unk_token				)				)
   def 			__magic_name__			(			self	,    _a				):
          return self.subword_tokenizer.convert_id_to_token(_a				)
   def 			__magic_name__			(			self	,    _a				):
          lowercase    :				Union[str, Any]       		=							"".join(_a				).strip()
          return out_string
   def 			__magic_name__			(			self	,    _a				):
          lowercase    :				Union[str, Any]       		=							[]
          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:
                 lowercase    :				Optional[Any]       		=							input_ids[-self.model_max_length :]
          return input_ids

   def 			__magic_name__			(			self	,    _a	,    _a = None				):
          lowercase    :				Tuple       		=							0
          if os.path.isdir(_a				):
                 lowercase    :				Optional[int]       		=							os.path.join(
                     _a	,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]				)
                 lowercase    :				Optional[Any]       		=							os.path.join(
                     _a	,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["emoji_file"]				)
          else:
                 lowercase    :				str       		=							(
                     (filename_prefix + "-" if filename_prefix else "") + save_directory + VOCAB_FILES_NAMES["vocab_file"]
                 )
                 lowercase    :				List[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!"				)
                               lowercase    :				Dict       		=							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__						(      a_						):
   def __init__(			self	,    _a	,    _a	,    _a				):
          lowercase    :				Union[str, Any]       		=							vocab  # same as swe
          lowercase    :				Dict       		=							ids_to_tokens  # same as bpe
          lowercase    :				Any       		=							emoji
          lowercase    :				str       		=							np.max([len(_a				) for w in self.vocab.keys()]				)
          lowercase    :				int       		=							re.compile(R"(https?|ftp)(:\/\/[-_\.!~*\'()a-zA-Z0-9;\/?:\@&=\+$,%#]+)"				)
          lowercase    :				Union[str, Any]       		=							re.compile(R"[A-Za-z0-9\._+]*@[\-_0-9A-Za-z]+(\.[A-Za-z]+)*"				)
          lowercase    :				List[str]       		=							re.compile(R"[\(]{0,1}[0-9]{2,4}[\)\-\(]{0,1}[0-9]{2,4}[\)\-]{0,1}[0-9]{3,4}"				)
          lowercase    :				Optional[int]       		=							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    :				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|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*"				)
          lowercase    :				Optional[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)*"				)
          lowercase    :				List[Any]       		=							"─━│┃┄┅┆┇┈┉┊┋┌┍┎┏┐┑┒┓└┕┖┗┘┙┚┛├┝┞┟┠┡┢┣┤┥┦┧┨┩┪┫┬┭┮┯┰┱┲┳┴┵┶┷┸┹┺┻┼┽┾┿╀╁╂╃╄╅╆╇╈╉╊╋╌╍╎╏═║╒╓╔╕╖╗╘╙╚╛╜╝╞╟╠╡╢╣╤╥╦╧╨╩╪╫╬╭╮╯╰╱╲╳╴╵╶╷╸╹╺╻╼╽╾╿"
          lowercase    :				int       		=							"▀▁▂▃▄▅▆▇█▉▊▋▌▍▎▏▐░▒▓▔▕▖▗▘▙▚▛▜▝▞▟"
          lowercase    :				Union[str, Any]       		=							str.maketrans({k: "<BLOCK>" for k in keisen + blocks}				)
   def __len__(			self				):
          return len(self.ids_to_tokens				)
   def 			__magic_name__			(			self	,    _a				):
          lowercase    :				List[Any]       		=							self.content_repattera.sub("<URL>"	,    _a				)
          lowercase    :				List[Any]       		=							self.content_repattera.sub("<EMAIL>"	,    _a				)
          lowercase    :				List[Any]       		=							self.content_repattera.sub("<TEL>"	,    _a				)
          lowercase    :				List[Any]       		=							self.content_repattera.sub("<DATE>"	,    _a				)
          lowercase    :				int       		=							self.content_repattera.sub("<DATE>"	,    _a				)
          lowercase    :				Tuple       		=							self.content_repattera.sub("<PRICE>"	,    _a				)
          lowercase    :				Optional[Any]       		=							content.translate(self.content_transa				)
          while "<BLOCK><BLOCK>" in content:
                 lowercase    :				List[Any]       		=							content.replace("<BLOCK><BLOCK>"	,    "<BLOCK>"				)
          return content
   def 			__magic_name__			(			self	,    _a	,    _a=False				):
          lowercase    :				str       		=							text.replace(" "	,    "<SP>"				)
          lowercase    :				str       		=							text.replace("　"	,    "<SP>"				)
          lowercase    :				int       		=							text.replace("\r\n"	,    "<BR>"				)
          lowercase    :				Dict       		=							text.replace("\n"	,    "<BR>"				)
          lowercase    :				int       		=							text.replace("\r"	,    "<BR>"				)
          lowercase    :				Dict       		=							text.replace("\t"	,    "<TAB>"				)
          lowercase    :				List[str]       		=							text.replace("—"	,    "ー"				)
          lowercase    :				Any       		=							text.replace("−"	,    "ー"				)
          for k, v in self.emoji["emoji"].items():
                 if k in text:
                        lowercase    :				Optional[int]       		=							text.replace(_a	,    _a				)
          if clean:
                 lowercase    :				Optional[int]       		=							self.clean_text(_a				)

          def check_simbol(_a				):
                 lowercase    :				List[Any]       		=							x.encode()
                 if len(_a				) == 1 and len(_a				) == 2:
                        lowercase    :				Optional[Any]       		=							(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(_a				):
                 lowercase    :				int       		=							x.encode()
                 if len(_a				) == 1 and len(_a				) == 3:
                        lowercase    :				Any       		=							(int(e[0]				) << 16) + (int(e[1]				) << 8) + int(e[2]				)
                        if c >= 0XE2_8080 and c <= 0XE2_B07F:
                               return True
                 return False

          lowercase    :				Tuple       		=							0
          lowercase    :				Optional[Any]       		=							[]
          while pos < len(_a				):
                 lowercase    :				Dict       		=							min(len(_a				)	,    pos + self.maxlen + 1				) if text[pos] == "<" else pos + 3
                 lowercase    :				List[str]       		=							[]  # (token_id, token, pos)
                 for e in range(_a	,    _a	,    -1				):
                        lowercase    :				Optional[int]       		=							text[pos:e]
                        if wd in self.vocab:
                               if wd[0] == "<" and len(_a				) > 2:
                                      lowercase    :				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
                        lowercase		,    lowercase		,    lowercase    :				Tuple       		=							sorted(_a	,    key=lambda _a				: x[0]				)[0]
                        result.append(_a				)
                        lowercase    :				Tuple       		=							e
                 else:
                        lowercase    :				Union[str, Any]       		=							pos + 1
                        lowercase    :				Optional[int]       		=							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				)
                        lowercase    :				Any       		=							end
          return result

   def 			__magic_name__			(			self	,    _a	,    _a="\n"				):
          lowercase    :				Any       		=							[]
          lowercase    :				Union[str, Any]       		=							[]
          lowercase    :				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"				)				)
                        lowercase    :				Any       		=							[]
                 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"				)				)
          lowercase    :				Any       		=							"".join(_a				)
          return text




"""simple docstring"""




import logging
import os
from typing import List, TextIO, Union

from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask


_A			:       Optional[int]   		=       logging.getLogger(__name__)

class 		a__						(      a_						):
   def __init__(			self	,    _a=-1				):
          # in NER datasets, the last column is usually reserved for NER label
          lowercase    :				List[str]       		=							label_idx
   def 			__magic_name__			(			self	,    _a	,    _a				):
          if isinstance(_a	,    _a				):
                 lowercase    :				Optional[Any]       		=							mode.value
          lowercase    :				List[str]       		=							os.path.join(_a	,    f"""{mode}.txt"""				)
          lowercase    :				str       		=							1
          lowercase    :				Optional[int]       		=							[]
          with open(_a	,    encoding="utf-8"				) as f:
                 lowercase    :				List[Any]       		=							[]
                 lowercase    :				Optional[int]       		=							[]
                 for line in f:
                        if line.startswith("-DOCSTART-"				) or line == "" or line == "\n":
                               if words:
                                      examples.append(InputExample(guid=f"""{mode}-{guid_index}"""	,    words=_a	,    labels=_a				)				)
                                      guid_index += 1
                                      lowercase    :				int       		=							[]
                                      lowercase    :				int       		=							[]
                        else:
                               lowercase    :				Optional[Any]       		=							line.split(" "				)
                               words.append(splits[0]				)
                               if len(_a				) > 1:
                                      labels.append(splits[self.label_idx].replace("\n"	,    ""				)				)
                               else:
                                      # Examples could have no label for mode = "test"
                                      labels.append("O"				)
                 if words:
                        examples.append(InputExample(guid=f"""{mode}-{guid_index}"""	,    words=_a	,    labels=_a				)				)
          return examples
   def 			__magic_name__			(			self	,    _a	,    _a	,    _a				):
          lowercase    :				List[str]       		=							0
          for line in test_input_reader:
                 if line.startswith("-DOCSTART-"				) or line == "" or line == "\n":
                        writer.write(_a				)
                        if not preds_list[example_id]:
                               example_id += 1
                 elif preds_list[example_id]:
                        lowercase    :				Any       		=							line.split()[0] + " " + preds_list[example_id].pop(0				) + "\n"
                        writer.write(_a				)
                 else:
                        logger.warning("Maximum sequence length exceeded: No prediction for '%s'."	,    line.split()[0]				)

   def 			__magic_name__			(			self	,    _a				):
          if path:
                 with open(_a	,    "r"				) as f:
                        lowercase    :				Optional[Any]       		=							f.read().splitlines()
                 if "O" not in labels:
                        lowercase    :				List[Any]       		=							["O"] + labels
                 return labels
          else:
                 return ["O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"]


class 		a__						(      a_						):
   def __init__(			self				):
          # in CONLL2003 dataset chunk column is second-to-last
          super().__init__(label_idx=-2				)

   def 			__magic_name__			(			self	,    _a				):
          if path:
                 with open(_a	,    "r"				) as f:
                        lowercase    :				Tuple       		=							f.read().splitlines()
                 if "O" not in labels:
                        lowercase    :				Optional[int]       		=							["O"] + labels
                 return labels
          else:
                 return [
                     "O",
                     "B-ADVP",
                     "B-INTJ",
                     "B-LST",
                     "B-PRT",
                     "B-NP",
                     "B-SBAR",
                     "B-VP",
                     "B-ADJP",
                     "B-CONJP",
                     "B-PP",
                     "I-ADVP",
                     "I-INTJ",
                     "I-LST",
                     "I-PRT",
                     "I-NP",
                     "I-SBAR",
                     "I-VP",
                     "I-ADJP",
                     "I-CONJP",
                     "I-PP",
                 ]


class 		a__						(      a_						):
   def 			__magic_name__			(			self	,    _a	,    _a				):
          if isinstance(_a	,    _a				):
                 lowercase    :				List[Any]       		=							mode.value
          lowercase    :				Optional[int]       		=							os.path.join(_a	,    f"""{mode}.txt"""				)
          lowercase    :				Tuple       		=							1
          lowercase    :				List[str]       		=							[]

          with open(_a	,    encoding="utf-8"				) as f:
                 for sentence in parse_incr(_a				):
                        lowercase    :				Optional[Any]       		=							[]
                        lowercase    :				str       		=							[]
                        for token in sentence:
                               words.append(token["form"]				)
                               labels.append(token["upos"]				)
                        assert len(_a				) == len(_a				)
                        if words:
                               examples.append(InputExample(guid=f"""{mode}-{guid_index}"""	,    words=_a	,    labels=_a				)				)
                               guid_index += 1
          return examples
   def 			__magic_name__			(			self	,    _a	,    _a	,    _a				):
          lowercase    :				str       		=							0
          for sentence in parse_incr(_a				):
                 lowercase    :				List[Any]       		=							preds_list[example_id]
                 lowercase    :				List[str]       		=							""
                 for token in sentence:
                        out += f"""{token["form"]} ({token["upos"]}|{s_p.pop(0				)}) """
                 out += "\n"
                 writer.write(_a				)
                 example_id += 1

   def 			__magic_name__			(			self	,    _a				):
          if path:
                 with open(_a	,    "r"				) as f:
                        return f.read().splitlines()
          else:
                 return [
                     "ADJ",
                     "ADP",
                     "ADV",
                     "AUX",
                     "CCONJ",
                     "DET",
                     "INTJ",
                     "NOUN",
                     "NUM",
                     "PART",
                     "PRON",
                     "PROPN",
                     "PUNCT",
                     "SCONJ",
                     "SYM",
                     "VERB",
                     "X",
                 ]


