





'''simple docstring'''


import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin






class       UpperCamelCase__  (		__lowerCAmelCase	,unittest.TestCase     ):
	lowerCAmelCase__					:			List[str]								=						PhobertTokenizer
	lowerCAmelCase__					:			int								=						False







	def 						__a   (				self			:   Optional[int]		):




				'''simple docstring'''
				super().setUp()

				# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
				a__     = ["T@@", "i", "I", "R@@", "r", "e@@"]
				a__     = dict(zip(lowerCamelCase , range(len(lowerCamelCase		)		)		)		)
				a__     = ["#version: 0.2", "l à</w>"]
				a__     = {"unk_token": "<unk>"}

				a__     = os.path.join(self.tmpdirname , VOCAB_FILES_NAMES["vocab_file"]		)
				a__     = os.path.join(self.tmpdirname , VOCAB_FILES_NAMES["merges_file"]		)

				with open(self.vocab_file , "w" , encoding="utf-8"		) as fp:
							for token in vocab_tokens:
										fp.write(F'''{token} {vocab_tokens[token]}\n'''		)
				with open(self.merges_file , "w" , encoding="utf-8"		) as fp:
							fp.write("\n".join(lowerCamelCase		)		)







	def 						__a   (				self			:   int , **lowerCamelCase			:   Dict		):




				'''simple docstring'''
				kwargs.update(self.special_tokens_map		)
				return PhobertTokenizer.from_pretrained(self.tmpdirname , **lowerCamelCase		)







	def 						__a   (				self			:   int , lowerCamelCase			:   Dict		):




				'''simple docstring'''
				a__     = "Tôi là VinAI Research"
				a__     = "T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
				return input_text, output_text







	def 						__a   (				self			:   List[str]		):




				'''simple docstring'''
				a__     = PhobertTokenizer(self.vocab_file , self.merges_file , **self.special_tokens_map		)
				a__     = "Tôi là VinAI Research"
				a__     = "T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
				a__     = tokenizer.tokenize(lowerCamelCase		)
				print(lowerCamelCase		)
				self.assertListEqual(lowerCamelCase , lowerCamelCase		)

				a__     = tokens + [tokenizer.unk_token]

				a__     = [4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase		) , lowerCamelCase		)










'''simple docstring'''


from __future__ import annotations

from math import pi







def    _lowerCamelCase  (__lowerCamelCase  :     float					,  __lowerCamelCase  :     float					,  __lowerCamelCase  :     float     )   ->    dict[str, float]:

			if (inductance, frequency, reactance).count(0     ) != 1:
						raise ValueError("One and only one argument must be 0"     )
			if inductance < 0:
						raise ValueError("Inductance cannot be negative"     )
			if frequency < 0:
						raise ValueError("Frequency cannot be negative"     )
			if reactance < 0:
						raise ValueError("Inductive reactance cannot be negative"     )
			if inductance == 0:
						return {"inductance": reactance / (2 * pi * frequency)}
			elif frequency == 0:
						return {"frequency": reactance / (2 * pi * inductance)}
			elif reactance == 0:
						return {"reactance": 2 * pi * frequency * inductance}
			else:
						raise ValueError("Exactly one argument must be 0"     )


if __name__ == "__main__":
		import doctest

		doctest.testmod()



