

"""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_	:			Any  	=      logging.get_logger(__name__)

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

A_	:			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',
    },
}

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

def 						UpperCamelCase (lowercase_:			Dict   ,				lowercase_:			List[str] )					->				List[Any]:
	with open(lowercase_   ,				"""r"""   ,				encoding="""utf-8""" ) as f:
		A__							:   List[Any]					       =		json.loads(f.read() )

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

	return vocab, raw_vocab, ids_to_tokens, emoji



class    _a						(__magic_name__    ):


					'''simple docstring'''






					UpperCAmelCase__:       List[str]  							=	VOCAB_FILES_NAMES
					UpperCAmelCase__:       Optional[Any]  							=	PRETRAINED_VOCAB_FILES_MAP
					UpperCAmelCase__:       Optional[int]  							=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					UpperCAmelCase__:       List[Any]  							=	['''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)`"""      )
						A__							:   int					       =		do_clean_text
						A__							:   Optional[int]					       =		load_vocab_and_emoji(A__   ,	A__      )
						A__							:   Tuple					       =		SubWordJapaneseTokenizer(
						    vocab=self.vocab   ,	ids_to_tokens=self.ids_to_tokens   ,	emoji=self.emoji      )






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






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






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






					def   __A      (			self   ,	A__      ):
						return self.vocab.get(A__   ,	self.vocab.get(self.unk_token      )      )






					def   __A      (			self   ,	A__      ):
						return self.subword_tokenizer.convert_id_to_token(A__      )






					def   __A      (			self   ,	A__      ):
						A__							:   Union[str, Any]					       =		"""""".join(A__      ).strip()
						return out_string






					def   __A      (			self   ,	A__      ):
						A__							:   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:
							A__							:   Union[str, Any]					       =		input_ids[-self.model_max_length :]
						return input_ids






					def   __A      (			self   ,	A__   ,	A__ = None      ):
						A__							:   str					       =		0
						if os.path.isdir(A__      ):
							A__							:   List[str]					       =		os.path.join(
							    A__   ,	(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )
							A__							:   int					       =		os.path.join(
							    A__   ,	(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""emoji_file"""]      )
						else:
							A__							:   int					       =		(
							    (filename_prefix + """-""" if filename_prefix else """""") + save_directory + VOCAB_FILES_NAMES["""vocab_file"""]
							)
							A__							:   Dict					       =		(
							    (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!"""      )
									A__							:   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						(__magic_name__    ):


					'''simple docstring'''






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






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






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






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

						def check_simbol(A__      ):
							A__							:   Any					       =		x.encode()
							if len(A__      ) == 1 and len(A__      ) == 2:
								A__							:   Any					       =		(int(e[0]      ) << 8) + int(e[1]      )
								if (
								    (c >= 0xC_2A1 and c <= 0xC_2BF)
								    or (c >= 0xC_780 and c <= 0xC_783)
								    or (c >= 0xC_AB9 and c <= 0xC_BBF)
								    or (c >= 0xC_C80 and c <= 0xC_DA2)
								):
									return True
							return False

						def checkuae(A__      ):
							A__							:   Any					       =		x.encode()
							if len(A__      ) == 1 and len(A__      ) == 3:
								A__							:   Union[str, Any]					       =		(int(e[0]      ) << 16) + (int(e[1]      ) << 8) + int(e[2]      )
								if c >= 0xE28_080 and c <= 0xE2B_07F:
									return True
							return False

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






					def   __A      (			self   ,	A__   ,	A__="\n"      ):
						A__							:   Tuple					       =		[]
						A__							:   Tuple					       =		[]
						A__							:   Union[str, 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"""      )      )
								A__							:   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"""      )      )
						A__							:   List[str]					       =		"""""".join(A__      )
						return text






from queue import PriorityQueue
from typing import Any

import numpy as np

def 						UpperCamelCase (lowercase_:			dict   ,				lowercase_:			str   ,				lowercase_:			set   ,				lowercase_:			set   ,				lowercase_:			dict   ,				lowercase_:			dict   ,				lowercase_:			PriorityQueue   ,				lowercase_:			dict   ,				lowercase_:			float | int   ,				)					->				float | int:
	for nxt, d in graph[v]:
		if nxt in visited_forward:
			continue
		A__							:   Any					       =		cst_fwd.get(lowercase_   ,				np.inf )
		A__							:   List[Any]					       =		cst_fwd[v] + d
		if new_cost_f < old_cost_f:
			queue.put((new_cost_f, nxt) )
			A__							:   Tuple					       =		new_cost_f
			A__							:   Any					       =		v
		if nxt in visited_backward:
			if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
				A__							:   Optional[int]					       =		cst_fwd[v] + d + cst_bwd[nxt]
	return shortest_distance

def 						UpperCamelCase (lowercase_:			str   ,				lowercase_:			str   ,				lowercase_:			dict   ,				lowercase_:			dict )					->				int:
	A__							:   Dict					       =		-1

	A__							:   List[Any]					       =		set()
	A__							:   Union[str, Any]					       =		set()
	A__							:   Optional[Any]					       =		{source: 0}
	A__							:   int					       =		{destination: 0}
	A__							:   Optional[Any]					       =		{source: None}
	A__							:   Union[str, Any]					       =		{destination: None}
	A__							:   PriorityQueue[Any]					       =		PriorityQueue()
	A__							:   PriorityQueue[Any]					       =		PriorityQueue()

	A__							:   List[Any]					       =		np.inf

	queue_forward.put((0, source) )
	queue_backward.put((0, destination) )

	if source == destination:
		return 0

	while not queue_forward.empty() and not queue_backward.empty():
		A__       ,       A__							:   Tuple					       =		queue_forward.get()
		visited_forward.add(lowercase_ )

		A__       ,       A__							:   Optional[Any]					       =		queue_backward.get()
		visited_backward.add(lowercase_ )

		A__							:   List[Any]					       =		pass_and_relaxation(
		    lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				)

		A__							:   List[Any]					       =		pass_and_relaxation(
		    lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				lowercase_   ,				)

		if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
			break

	if shortest_distance != np.inf:
		A__							:   int					       =		shortest_distance
	return shortest_path_distance


A_	:			List[Any]  	=      {
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}
A_	:			Optional[int]  	=      {
    'B': [['E', 1]],
    'C': [['B', 1]],
    'D': [['C', 1]],
    'F': [['D', 1], ['G', 1]],
    'E': [[None, np.inf]],
    'G': [['E', 2]],
}

if __name__ == "__main__":
	import doctest

	doctest.testmod()



