



'''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


lowerCamelCase							:Tuple       = logging.get_logger(__name__)

lowerCamelCase							:Any       = {'''vocab_file''': '''vocab.txt''', '''emoji_file''': '''emoji.json'''}

lowerCamelCase							: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''',
    },
}

lowerCamelCase							:Any       = {
    '''abeja/gpt-neox-japanese-2.7b''': 2_0_4_8,
}



def      a      (			lowerCamelCase__						,				lowerCamelCase__   ):
			'''simple docstring'''





			with open(lowerCamelCase__						,				"""r"""						,				encoding="""utf-8"""   ) as f:
						A_     :						int     =					json.loads(f.read()   )

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

			return vocab, raw_vocab, ids_to_tokens, emoji







class      _lowerCAmelCase							(      __UpperCAmelCase			):
	__SCREAMING_SNAKE_CASE       :		int		      = VOCAB_FILES_NAMES
	__SCREAMING_SNAKE_CASE       :		Dict		      = PRETRAINED_VOCAB_FILES_MAP
	__SCREAMING_SNAKE_CASE       :		Union[str, Any]		      = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	__SCREAMING_SNAKE_CASE       :		Union[str, Any]		      = ['input_ids', 'attention_mask']


	def __init__(self	,				lowercase	,				lowercase	,				lowercase="<|endoftext|>"	,				lowercase="<|endoftext|>"	,				lowercase="<|startoftext|>"	,				lowercase="<|endoftext|>"	,				lowercase=False	,				**lowercase	,				):
				super().__init__(
				    unk_token=lowercase	,				pad_token=lowercase	,				bos_token=lowercase	,				eos_token=lowercase	,				do_clean_text=lowercase	,				**lowercase	,				)
				if not os.path.isfile(lowercase							):
							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(lowercase							):
							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_     :						Optional[int]     =					do_clean_text
				A_     :						int     =					load_vocab_and_emoji(lowercase	,				lowercase							)
				A_     :						Dict     =					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	,				lowercase							):
				return self.subword_tokenizer.tokenize(lowercase	,				clean=self.do_clean_text							)


	def    _a     (self	,				lowercase							):
				return self.vocab.get(lowercase	,				self.vocab.get(self.unk_token							)							)


	def    _a     (self	,				lowercase							):
				return self.subword_tokenizer.convert_id_to_token(lowercase							)


	def    _a     (self	,				lowercase							):
				A_     :						List[Any]     =					"""""".join(lowercase							).strip()
				return out_string


	def    _a     (self	,				lowercase							):
				A_     :						Optional[Any]     =					[]
				for is_user, text in conversation.iter_texts():
							input_ids.extend(self.encode(lowercase	,				add_special_tokens=lowercase							) + [self.eos_token_id]							)

				if len(lowercase							) > self.model_max_length:
							A_     :						Union[str, Any]     =					input_ids[-self.model_max_length :]
				return input_ids


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







class      _lowerCAmelCase							(      __UpperCAmelCase			):


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


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


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


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

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

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


	def    _a     (self	,				lowercase	,				lowercase="\n"							):
				A_     :						Any     =					[]
				A_     :						List[Any]     =					[]
				A_     :						List[Any]     =					self.ids_to_tokens[index][0]
				if word[:6] == "<|byte" and word[-2:] == "|>":
							byte_tokens.append(int(word[6:-2]							)							)
				else:
							if len(lowercase							) > 0:
										words.append(bytearray(lowercase							).decode("""utf-8"""	,				errors="""replace"""							)							)
										A_     :						List[str]     =					[]
							if word[:7] == "<|emoji" and word[-2:] == "|>":
										words.append(self.emoji["""emoji_inv"""][word]							)
							elif word == "<SP>":
										words.append(""" """							)
							elif word == "<BR>":
										words.append(lowercase							)
							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(lowercase							)
				if len(lowercase							) > 0:
							words.append(bytearray(lowercase							).decode("""utf-8"""	,				errors="""replace"""							)							)
				A_     :						List[Any]     =					"""""".join(lowercase							)
				return text








'''simple docstring'''




from __future__ import annotations

from collections.abc import Callable

lowerCamelCase							:List[Any]       = list[list[float | int]]



def      a      (			lowerCamelCase__						,				lowerCamelCase__   ):
			'''simple docstring'''





			A_     :						int     =					len(lowerCamelCase__   )
			A_     :						Matrix     =					[[0 for _ in range(size + 1   )] for _ in range(lowerCamelCase__   )]
			A_     :						int
			A_     :						int
			A_     :						int
			A_     :						int
			A_     :						int
			A_     :						float

			for row in range(lowerCamelCase__   ):
						for col in range(lowerCamelCase__   ):
									A_     :						List[str]     =					matrix[row][col]

						A_     :						Optional[int]     =					vector[row][0]

			A_     :						Tuple     =					0
			A_     :						Tuple     =					0
			while row < size and col < size:
						# pivoting
						A_     :						Dict     =					max((abs(augmented[rowa][col]   ), rowa) for rowa in range(lowerCamelCase__						,				lowerCamelCase__   )   )[
						    1
						]
						if augmented[pivot_row][col] == 0:
									col += 1
									continue
						else:
									A_,   A_     :						Optional[Any]     =					augmented[pivot_row], augmented[row]

						for rowa in range(row + 1						,				lowerCamelCase__   ):
									A_     :						int     =					augmented[rowa][col] / augmented[row][col]
									A_     :						Union[str, Any]     =					0
									for cola in range(col + 1						,				size + 1   ):
												augmented[rowa][cola] -= augmented[row][cola] * ratio

						row += 1
						col += 1

			# back substitution
			for col in range(1						,				lowerCamelCase__   ):
						for row in range(lowerCamelCase__   ):
									A_     :						Tuple     =					augmented[row][col] / augmented[col][col]
									for cola in range(lowerCamelCase__						,				size + 1   ):
												augmented[row][cola] -= augmented[col][cola] * ratio

    # round to get rid of numbers like 2.000000000000004
			return [
			    [round(augmented[row][size] / augmented[row][row]						,				10   )] for row in range(lowerCamelCase__   )
			]



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			A_     :						int     =					len(lowerCamelCase__   )
			A_     :						Matrix     =					[[0 for _ in range(lowerCamelCase__   )] for _ in range(lowerCamelCase__   )]
			A_     :						Matrix     =					[[0] for _ in range(lowerCamelCase__   )]
			A_     :						Matrix
			A_     :						int
			A_     :						int
			A_     :						int

			for x_val, y_val in enumerate(lowerCamelCase__   ):
						for col in range(lowerCamelCase__   ):
									A_     :						Dict     =					(x_val + 1) ** (size - col - 1)
						A_     :						Any     =					y_val

			A_     :						Dict     =					solve(lowerCamelCase__						,				lowerCamelCase__   )

			def interpolated_func(lowerCamelCase__   ) -> int:
						return sum(
						    round(coeffs[x_val][0]   ) * (var ** (size - x_val - 1))
						    for x_val in range(lowerCamelCase__   )   )

			return interpolated_func



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			return (
			    1
			    - variable
			    + variable**2
			    - variable**3
			    + variable**4
			    - variable**5
			    + variable**6
			    - variable**7
			    + variable**8
			    - variable**9
			    + variable**10
			)



def      a      (			lowerCamelCase__ = question_function						,				lowerCamelCase__ = 10   ):
			'''simple docstring'''





			A_     :						list[int]     =					[func(lowerCamelCase__   ) for x_val in range(1						,				order + 1   )]

			A_     :						list[Callable[[int], int]]     =					[
			    interpolate(data_points[:max_coeff]   ) for max_coeff in range(1						,				order + 1   )
			]

			A_     :						int     =					0
			A_     :						Callable[[int], int]
			A_     :						int

			for poly in polynomials:
						A_     :						int     =					1
						while func(lowerCamelCase__   ) == poly(lowerCamelCase__   ):
									x_val += 1

						ret += poly(lowerCamelCase__   )

			return ret


if __name__ == "__main__":
						print(F"{solution() = }")