


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		:				Optional[int]									=       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		:				Optional[int]									=       {
    '''abeja/gpt-neox-japanese-2.7b''': 2_048,
}



def     __lowerCAmelCase						(							snake_case	:    int						,      snake_case	:    Tuple )       ->							int:
   with open(snake_case						,      """r"""						,      encoding="""utf-8""" ) as f:
      __lowerCamelCase:				str     =	json.loads(f.read() )

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

   return vocab, raw_vocab, ids_to_tokens, emoji



class        a					(			_UpperCAmelCase   ):
     UpperCAmelCase__ :  List[Any]						      =	VOCAB_FILES_NAMES
     UpperCAmelCase__ :  int						      =	PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__ :  Optional[int]						      =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase__ :  Optional[int]						      =	["input_ids", "attention_mask"]





     def __init__(    self					:				int    ,	SCREAMING_SNAKE_CASE_					:				Any    ,	SCREAMING_SNAKE_CASE_					:				Optional[int]    ,	SCREAMING_SNAKE_CASE_					:				Optional[Any]="<|endoftext|>"    ,	SCREAMING_SNAKE_CASE_					:				Union[str, Any]="<|endoftext|>"    ,	SCREAMING_SNAKE_CASE_					:				Any="<|startoftext|>"    ,	SCREAMING_SNAKE_CASE_					:				Union[str, Any]="<|endoftext|>"    ,	SCREAMING_SNAKE_CASE_					:				List[str]=False    ,	**SCREAMING_SNAKE_CASE_					:				Optional[int]    ,	):
        super().__init__(
            unk_token=SCREAMING_SNAKE_CASE_    ,	pad_token=SCREAMING_SNAKE_CASE_    ,	bos_token=SCREAMING_SNAKE_CASE_    ,	eos_token=SCREAMING_SNAKE_CASE_    ,	do_clean_text=SCREAMING_SNAKE_CASE_    ,	**SCREAMING_SNAKE_CASE_    ,	)
        if not os.path.isfile(SCREAMING_SNAKE_CASE_							):
           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(SCREAMING_SNAKE_CASE_							):
           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:				List[Any]     =	do_clean_text
        __lowerCamelCase   ,     __lowerCamelCase   ,     __lowerCamelCase   ,     __lowerCamelCase:				int     =	load_vocab_and_emoji(SCREAMING_SNAKE_CASE_    ,	SCREAMING_SNAKE_CASE_							)
        __lowerCamelCase:				List[Any]     =	SubWordJapaneseTokenizer(
            vocab=self.vocab    ,	ids_to_tokens=self.ids_to_tokens    ,	emoji=self.emoji							)





     @property
     def  SCREAMING_SNAKE_CASE__       (    self					:				List[str]							):
        # self.vocab contains support for character fluctuation unique to Japanese, and has a large number of vocab
        return len(self.raw_vocab							)





     def  SCREAMING_SNAKE_CASE__       (    self					:				Any							):
        return dict(self.raw_vocab    ,	**self.added_tokens_encoder							)





     def  SCREAMING_SNAKE_CASE__       (    self					:				Optional[Any]    ,	SCREAMING_SNAKE_CASE_					:				Dict							):
        return self.subword_tokenizer.tokenize(SCREAMING_SNAKE_CASE_    ,	clean=self.do_clean_text							)





     def  SCREAMING_SNAKE_CASE__       (    self					:				str    ,	SCREAMING_SNAKE_CASE_					:				Optional[Any]							):
        return self.vocab.get(SCREAMING_SNAKE_CASE_    ,	self.vocab.get(self.unk_token							)							)





     def  SCREAMING_SNAKE_CASE__       (    self					:				int    ,	SCREAMING_SNAKE_CASE_					:				str							):
        return self.subword_tokenizer.convert_id_to_token(SCREAMING_SNAKE_CASE_							)





     def  SCREAMING_SNAKE_CASE__       (    self					:				Dict    ,	SCREAMING_SNAKE_CASE_					:				List[str]							):
        __lowerCamelCase:				str     =	"""""".join(SCREAMING_SNAKE_CASE_							).strip()
        return out_string





     def  SCREAMING_SNAKE_CASE__       (    self					:				str    ,	SCREAMING_SNAKE_CASE_					:				"Conversation"							):
        __lowerCamelCase:				Any     =	[]
        for is_user, text in conversation.iter_texts():
           input_ids.extend(self.encode(SCREAMING_SNAKE_CASE_    ,	add_special_tokens=SCREAMING_SNAKE_CASE_							) + [self.eos_token_id]							)

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







     def  SCREAMING_SNAKE_CASE__       (    self					:				Union[str, Any]    ,	SCREAMING_SNAKE_CASE_					:				str    ,	SCREAMING_SNAKE_CASE_					:				Optional[str] = None							):
        __lowerCamelCase:				Optional[int]     =	0
        if os.path.isdir(SCREAMING_SNAKE_CASE_							):
           __lowerCamelCase:				List[Any]     =	os.path.join(
               SCREAMING_SNAKE_CASE_    ,	(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)
           __lowerCamelCase:				int     =	os.path.join(
               SCREAMING_SNAKE_CASE_    ,	(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""emoji_file"""]							)
        else:
           __lowerCamelCase:				Dict     =	(
               (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(SCREAMING_SNAKE_CASE_    ,	"""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:				Optional[int]     =	token_index
              writer.write(""",""".join(SCREAMING_SNAKE_CASE_							) + """\n"""							)
              index += 1
        with open(SCREAMING_SNAKE_CASE_    ,	"""w"""    ,	encoding="""utf-8"""							) as writer:
           json.dump(self.emoji    ,	SCREAMING_SNAKE_CASE_							)
        return vocab_file, emoji_file



class        a					(			_UpperCAmelCase   ):





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





     def __len__(    self					:				Dict							):
        return len(self.ids_to_tokens							)





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





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

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







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






import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
   _A		:				str									=       argparse.ArgumentParser()

   parser.add_argument('''--dump_path''', default=None, type=str, required=True, help='''Path to the output model.''')

   parser.add_argument(
       '''--txt2img_unclip''',
       default='''kakaobrain/karlo-v1-alpha''',
       type=str,
       required=False,
       help='''The pretrained txt2img unclip.''',
   )

   _A		:				Optional[Any]									=       parser.parse_args()

   _A		:				str									=       UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

   _A		:				Optional[Any]									=       CLIPImageProcessor()
   _A		:				List[Any]									=       CLIPVisionModelWithProjection.from_pretrained('''openai/clip-vit-large-patch14''')

   _A		:				str									=       UnCLIPImageVariationPipeline(
       decoder=txtaimg.decoder,
       text_encoder=txtaimg.text_encoder,
       tokenizer=txtaimg.tokenizer,
       text_proj=txtaimg.text_proj,
       feature_extractor=feature_extractor,
       image_encoder=image_encoder,
       super_res_first=txtaimg.super_res_first,
       super_res_last=txtaimg.super_res_last,
       decoder_scheduler=txtaimg.decoder_scheduler,
       super_res_scheduler=txtaimg.super_res_scheduler,
   )

   imgaimg.save_pretrained(args.dump_path)


