


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

A							:					Dict     						=     {'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							:					Dict     						=     {
    'abeja/gpt-neox-japanese-2.7b': 2048,
}





def 	_lowerCAmelCase       (    _lowerCAmelCase      ,	_lowerCAmelCase )						->	List[Any]:


						'''simple docstring'''






						with open(_lowerCAmelCase      ,	"r"      ,	encoding="utf-8" ) as f:
												__snake_case				=		json.loads(f.read() )

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

						return vocab, raw_vocab, ids_to_tokens, emoji






class     UpperCamelCase(  _a   ):
					snake_case_		:				Optional[Any]										=	VOCAB_FILES_NAMES
					snake_case_		:				Tuple										=	PRETRAINED_VOCAB_FILES_MAP
					snake_case_		:				Any										=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					snake_case_		:				Dict										=	["""input_ids""", """attention_mask"""]


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




											'''simple docstring'''

											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)`"						)
											__snake_case				=		do_clean_text
											__snake_case		,					__snake_case		,					__snake_case		,					__snake_case				=		load_vocab_and_emoji(SCREAMING_SNAKE_CASE     ,    SCREAMING_SNAKE_CASE						)
											__snake_case				=		SubWordJapaneseTokenizer(
											    vocab=self.vocab     ,    ids_to_tokens=self.ids_to_tokens     ,    emoji=self.emoji						)


					@property
					def 							SCREAMING_SNAKE_CASE_  (						self	:		Dict						)			->	Optional[Any]:




											'''simple docstring'''

											return len(self.raw_vocab						)


					def 							SCREAMING_SNAKE_CASE_  (						self	:		List[str]						)			->	Tuple:




											'''simple docstring'''

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


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Optional[Any]     ,    SCREAMING_SNAKE_CASE	:		Any						)			->	List[Any]:




											'''simple docstring'''

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


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Union[str, Any]     ,    SCREAMING_SNAKE_CASE	:		Any						)			->	int:




											'''simple docstring'''

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


					def 							SCREAMING_SNAKE_CASE_  (						self	:		List[str]     ,    SCREAMING_SNAKE_CASE	:		Optional[int]						)			->	Dict:




											'''simple docstring'''

											return self.subword_tokenizer.convert_id_to_token(SCREAMING_SNAKE_CASE						)


					def 							SCREAMING_SNAKE_CASE_  (						self	:		List[Any]     ,    SCREAMING_SNAKE_CASE	:		Optional[Any]						)			->	Union[str, Any]:




											'''simple docstring'''

											__snake_case				=		"".join(SCREAMING_SNAKE_CASE						).strip()
											return out_string


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Optional[int]     ,    SCREAMING_SNAKE_CASE	:		"Conversation"						)			->	List[int]:




											'''simple docstring'''

											__snake_case				=		[]
											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:
																	__snake_case				=		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						)			->	Tuple[str]:




											'''simple docstring'''

											__snake_case				=		0
											if os.path.isdir(SCREAMING_SNAKE_CASE						):
																	__snake_case				=		os.path.join(
																	    SCREAMING_SNAKE_CASE     ,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
																	__snake_case				=		os.path.join(
																	    SCREAMING_SNAKE_CASE     ,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["emoji_file"]						)
											else:
																	__snake_case				=		(
																	    (filename_prefix + "-" if filename_prefix else "") + save_directory + VOCAB_FILES_NAMES["vocab_file"]
																	)
																	__snake_case				=		(
																	    (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!"						)
																													__snake_case				=		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     UpperCamelCase(  _a   ):


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




											'''simple docstring'''

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


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




											'''simple docstring'''

											return len(self.ids_to_tokens						)


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Union[str, Any]     ,    SCREAMING_SNAKE_CASE	:		Optional[Any]						)			->	str:




											'''simple docstring'''

											__snake_case				=		self.content_repattera.sub("<URL>"     ,    SCREAMING_SNAKE_CASE						)
											__snake_case				=		self.content_repattera.sub("<EMAIL>"     ,    SCREAMING_SNAKE_CASE						)
											__snake_case				=		self.content_repattera.sub("<TEL>"     ,    SCREAMING_SNAKE_CASE						)
											__snake_case				=		self.content_repattera.sub("<DATE>"     ,    SCREAMING_SNAKE_CASE						)
											__snake_case				=		self.content_repattera.sub("<DATE>"     ,    SCREAMING_SNAKE_CASE						)
											__snake_case				=		self.content_repattera.sub("<PRICE>"     ,    SCREAMING_SNAKE_CASE						)
											__snake_case				=		content.translate(self.content_transa						)
											while "<BLOCK><BLOCK>" in content:
																	__snake_case				=		content.replace("<BLOCK><BLOCK>"     ,    "<BLOCK>"						)
											return content


					def 							SCREAMING_SNAKE_CASE_  (						self	:		int     ,    SCREAMING_SNAKE_CASE	:		List[str]     ,    SCREAMING_SNAKE_CASE	:		Any=False						)			->	Any:




											'''simple docstring'''

											__snake_case				=		text.replace(" "     ,    "<SP>"						)
											__snake_case				=		text.replace("　"     ,    "<SP>"						)
											__snake_case				=		text.replace("\r\n"     ,    "<BR>"						)
											__snake_case				=		text.replace("\n"     ,    "<BR>"						)
											__snake_case				=		text.replace("\r"     ,    "<BR>"						)
											__snake_case				=		text.replace("\t"     ,    "<TAB>"						)
											__snake_case				=		text.replace("—"     ,    "ー"						)
											__snake_case				=		text.replace("−"     ,    "ー"						)
											for k, v in self.emoji["emoji"].items():
																	if k in text:
																							__snake_case				=		text.replace(SCREAMING_SNAKE_CASE     ,    SCREAMING_SNAKE_CASE						)
											if clean:
																	__snake_case				=		self.clean_text(SCREAMING_SNAKE_CASE						)

											def check_simbol(SCREAMING_SNAKE_CASE	:		List[str]						):
																	__snake_case				=		x.encode()
																	if len(SCREAMING_SNAKE_CASE						) == 1 and len(SCREAMING_SNAKE_CASE						) == 2:
																							__snake_case				=		(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	:		Optional[int]						):
																	__snake_case				=		x.encode()
																	if len(SCREAMING_SNAKE_CASE						) == 1 and len(SCREAMING_SNAKE_CASE						) == 3:
																							__snake_case				=		(int(e[0]						) << 1_6) + (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

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






					def 							SCREAMING_SNAKE_CASE_  (						self	:		Optional[int]     ,    SCREAMING_SNAKE_CASE	:		Optional[int]     ,    SCREAMING_SNAKE_CASE	:		List[str]="\n"						)			->	List[Any]:




											'''simple docstring'''

											__snake_case				=		[]
											__snake_case				=		[]
											__snake_case				=		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"						)						)
																							__snake_case				=		[]
																	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"						)						)
											__snake_case				=		"".join(SCREAMING_SNAKE_CASE						)
											return text









def 	_lowerCAmelCase       (    _lowerCAmelCase = "The quick brown fox jumps over the lazy dog"      ,	)						->	bool:


						'''simple docstring'''






						__snake_case				=		set()

						# Replace all the whitespace in our sentence
						__snake_case				=		input_str.replace(" "      ,	"" )
						for alpha in input_str:
												if "a" <= alpha.lower() <= "z":
																		frequency.add(alpha.lower() )
						return len(_lowerCAmelCase ) == 26





def 	_lowerCAmelCase       (    _lowerCAmelCase = "The quick brown fox jumps over the lazy dog"      ,	)						->	bool:


						'''simple docstring'''






						__snake_case				=		[False] * 26
						for char in input_str:
												if char.islower():
																		__snake_case				=		True
												elif char.isupper():
																		__snake_case				=		True
						return all(_lowerCAmelCase )





def 	_lowerCAmelCase       (    _lowerCAmelCase = "The quick brown fox jumps over the lazy dog"      ,	)						->	bool:


						'''simple docstring'''






						return len({char for char in input_str.lower() if char.isalpha()} ) == 26





def 	_lowerCAmelCase       (    )						->	None:


						'''simple docstring'''






						from timeit import timeit

						__snake_case				=		"from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest"
						print(timeit("is_pangram()"      ,	setup=_lowerCAmelCase ) )
						print(timeit("is_pangram_faster()"      ,	setup=_lowerCAmelCase ) )
						print(timeit("is_pangram_fastest()"      ,	setup=_lowerCAmelCase ) )
						# 5.348480500048026, 2.6477354579837993, 1.8470395830227062
						# 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	benchmark()





