


import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


A							:					int     						=     get_tests_dir('fixtures/test_sentencepiece_bpe.model')






class     UpperCamelCase(  _a     ,							unittest.TestCase   ):
					snake_case_		:				Union[str, Any]										=	BartphoTokenizer
					snake_case_		:				Any										=	False
					snake_case_		:				str										=	True


					def 							SCREAMING_SNAKE_CASE_  (						self	:		List[Any]						)			->	Dict:




											'''simple docstring'''

											super().setUp()

											__snake_case				=		["▁This", "▁is", "▁a", "▁t", "est"]
											__snake_case				=		dict(zip(SCREAMING_SNAKE_CASE     ,    range(len(SCREAMING_SNAKE_CASE						)						)						)						)
											__snake_case				=		{"unk_token": "<unk>"}

											__snake_case				=		os.path.join(self.tmpdirname     ,    VOCAB_FILES_NAMES["monolingual_vocab_file"]						)
											with open(self.monolingual_vocab_file     ,    "w"     ,    encoding="utf-8"						) as fp:
																	for token in vocab_tokens:
																							fp.write(f'''{token} {vocab_tokens[token]}\n'''						)

											__snake_case				=		BartphoTokenizer(SCREAMING_SNAKE_CASE     ,    self.monolingual_vocab_file     ,    **self.special_tokens_map						)
											tokenizer.save_pretrained(self.tmpdirname						)


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




											'''simple docstring'''

											kwargs.update(self.special_tokens_map						)
											return BartphoTokenizer.from_pretrained(self.tmpdirname     ,    **SCREAMING_SNAKE_CASE						)


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




											'''simple docstring'''

											__snake_case				=		"This is a là test"
											__snake_case				=		"This is a<unk><unk> test"
											return input_text, output_text






					def 							SCREAMING_SNAKE_CASE_  (						self	:		Any						)			->	Any:




											'''simple docstring'''

											__snake_case				=		BartphoTokenizer(SCREAMING_SNAKE_CASE     ,    self.monolingual_vocab_file     ,    **self.special_tokens_map						)
											__snake_case				=		"This is a là test"
											__snake_case				=		"▁This ▁is ▁a ▁l à ▁t est".split()
											__snake_case				=		tokenizer.tokenize(SCREAMING_SNAKE_CASE						)
											self.assertListEqual(SCREAMING_SNAKE_CASE     ,    SCREAMING_SNAKE_CASE						)

											__snake_case				=		tokens + [tokenizer.unk_token]
											__snake_case				=		[4, 5, 6, 3, 3, 7, 8, 3]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE						)     ,    SCREAMING_SNAKE_CASE						)









from __future__ import annotations

from decimal import Decimal
from math import *  # noqa: F403

from sympy import diff





def 	_lowerCAmelCase       (    _lowerCAmelCase      ,	_lowerCAmelCase      ,	_lowerCAmelCase = 10**-10 )						->	float:


						'''simple docstring'''






						__snake_case				=		a
						while True:
												__snake_case				=		Decimal(_lowerCAmelCase ) - (
												    Decimal(eval(_lowerCAmelCase ) ) / Decimal(eval(str(diff(_lowerCAmelCase ) ) ) )  # noqa: S307
												)
												# This number dictates the accuracy of the answer
												if abs(eval(_lowerCAmelCase ) ) < precision:  # noqa: S307
																		return float(_lowerCAmelCase )


# Let's Execute
if __name__ == "__main__":
	# Find root of trigonometric function
	# Find value of pi
	print(f'''The root of sin(x) = 0 is {newton_raphson("sin(x)", 2)}''')
	# Find root of polynomial
	print(f'''The root of x**2 - 5*x + 2 = 0 is {newton_raphson("x**2 - 5*x + 2", 0.4)}''')
	# Find Square Root of 5
	print(f'''The root of log(x) - 1 = 0 is {newton_raphson("log(x) - 1", 2)}''')
	# Exponential Roots
	print(f'''The root of exp(x) - 1 = 0 is {newton_raphson("exp(x) - 1", 0)}''')





