






'''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


UpperCAmelCase__						:Union[str, Any]          =			logging.get_logger(__name__)

UpperCAmelCase__						:Dict          =			{"""vocab_file""": """vocab.txt""", """emoji_file""": """emoji.json"""}

UpperCAmelCase__						:List[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""",
    },
}

UpperCAmelCase__						:Optional[Any]          =			{
    """abeja/gpt-neox-japanese-2.7b""": 2_048,
}
def     __lowercase  (_lowercase,						_lowercase     )   ->     str:


     """simple docstring"""
     with open(_lowercase,						"""r""",						encoding="""utf-8"""     ) as f:
          __lowerCamelCase						:       Dict				   =				json.loads(f.read()     )

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

     return vocab, raw_vocab, ids_to_tokens, emoji







class 	SCREAMING_SNAKE_CASE	(      lowerCAmelCase_  ):
       snake_case__    :     Optional[Any]   		=			VOCAB_FILES_NAMES
       snake_case__    :     List[str]   		=			PRETRAINED_VOCAB_FILES_MAP
       snake_case__    :     Union[str, Any]   		=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       snake_case__    :     Union[str, Any]   		=			['input_ids', 'attention_mask']




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


            """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						:       Tuple				   =				do_clean_text
            __lowerCamelCase   ,      __lowerCamelCase   ,      __lowerCamelCase   ,      __lowerCamelCase						:       List[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 					a_					(					self      : List[Any]					):


            """simple docstring"""







            return len(self.raw_vocab					)




       def 					a_					(					self      : Union[str, Any]					):


            """simple docstring"""







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




       def 					a_					(					self      : List[Any]	,    A__      : Optional[int]					):


            """simple docstring"""







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




       def 					a_					(					self      : Optional[Any]	,    A__      : Any					):


            """simple docstring"""







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




       def 					a_					(					self      : Any	,    A__      : Any					):


            """simple docstring"""







            return self.subword_tokenizer.convert_id_to_token(A__					)




       def 					a_					(					self      : Optional[int]	,    A__      : Optional[Any]					):


            """simple docstring"""







            __lowerCamelCase						:       List[Any]				   =				"""""".join(A__					).strip()
            return out_string




       def 					a_					(					self      : str	,    A__      : "Conversation"					):


            """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						:       str				   =				input_ids[-self.model_max_length :]
            return input_ids




       def 					a_					(					self      : str	,    A__      : str	,    A__      : Optional[str] = None					):


            """simple docstring"""







            __lowerCamelCase						:       List[str]				   =				0
            if os.path.isdir(A__					):
                 __lowerCamelCase						:       Union[str, Any]				   =				os.path.join(
                     A__	,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]					)
                 __lowerCamelCase						:       int				   =				os.path.join(
                     A__	,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""emoji_file"""]					)
            else:
                 __lowerCamelCase						:       str				   =				(
                     (filename_prefix + """-""" if filename_prefix else """""") + save_directory + VOCAB_FILES_NAMES["""vocab_file"""]
                 )
                 __lowerCamelCase						:       int				   =				(
                     (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						:       Union[str, 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 	SCREAMING_SNAKE_CASE	(      lowerCAmelCase_  ):




       def __init__(					self      : Union[str, Any]	,    A__      : Any	,    A__      : str	,    A__      : Optional[Any]					):


            """simple docstring"""







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




       def __len__(					self      : Tuple					):


            """simple docstring"""







            return len(self.ids_to_tokens					)




       def 					a_					(					self      : Dict	,    A__      : Tuple					):


            """simple docstring"""







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




       def 					a_					(					self      : List[Any]	,    A__      : Dict	,    A__      : Optional[Any]=False					):


            """simple docstring"""







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

            def check_simbol(A__      : Union[str, Any]					):
                 __lowerCamelCase						:       str				   =				x.encode()
                 if len(A__					) == 1 and len(A__					) == 2:
                      __lowerCamelCase						:       Optional[int]				   =				(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(A__      : Tuple					):
                 __lowerCamelCase						:       List[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 >= 0XE2_80_80 and c <= 0XE2_B0_7F:
                           return True
                 return False

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




       def 					a_					(					self      : Optional[Any]	,    A__      : Optional[int]	,    A__      : Any="\n"					):


            """simple docstring"""







            __lowerCamelCase						:       Tuple				   =				[]
            __lowerCamelCase						:       List[Any]				   =				[]
            __lowerCamelCase						:       Optional[int]				   =				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						:       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(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						:       str				   =				"""""".join(A__					)
            return text











'''simple docstring'''

import argparse
import json

from tqdm import tqdm
def     __lowercase  ()   ->     Tuple:


     """simple docstring"""
     __lowerCamelCase						:       Union[str, Any]				   =				argparse.ArgumentParser()

     # Required parameters
     parser.add_argument(
         """--src_path""",						type=_lowercase,						default="""biencoder-nq-dev.json""",						help="""Path to raw DPR training data""",						)
     parser.add_argument(
         """--evaluation_set""",						type=_lowercase,						help="""where to store parsed evaluation_set file""",						)
     parser.add_argument(
         """--gold_data_path""",						type=_lowercase,						help="""where to store parsed gold_data_path file""",						)
     __lowerCamelCase						:       Tuple				   =				parser.parse_args()

     with open(args.src_path,						"""r"""     ) as src_file, open(args.evaluation_set,						"""w"""     ) as eval_file, open(
         args.gold_data_path,						"""w"""     ) as gold_file:
          __lowerCamelCase						:       int				   =				json.load(_lowercase     )
          for dpr_record in tqdm(_lowercase     ):
               __lowerCamelCase						:       List[Any]				   =				dpr_record["""question"""]
               __lowerCamelCase						:       List[str]				   =				[context["""title"""] for context in dpr_record["""positive_ctxs"""]]
               eval_file.write(question + """\n"""     )
               gold_file.write("""\t""".join(_lowercase     ) + """\n"""     )


if __name__ == "__main__":
   main()



