





"""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       (		a__	, unittest.TestCase		):
							lowerCamelCase     :      Union[str, Any]         =PhobertTokenizer
							lowerCamelCase     :      Dict         =False






							def 					__a     (     self   )			->				Any:
								super().setUp()

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

								a   :	Dict			=       os.path.join(self.tmpdirname   ,      VOCAB_FILES_NAMES["vocab_file"]   )
								a   :	Dict			=       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   ,      **lowerCAmelCase__   )			->				Optional[int]:
								kwargs.update(self.special_tokens_map   )
								return PhobertTokenizer.from_pretrained(self.tmpdirname   ,      **lowerCAmelCase__   )






							def 					__a     (     self   ,      lowerCAmelCase__   )			->				List[Any]:
								a   :	Union[str, Any]			=       "Tôi là VinAI Research"
								a   :	int			=       "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   )			->				Optional[Any]:
								a   :	Tuple			=       PhobertTokenizer(self.vocab_file   ,      self.merges_file   ,      **self.special_tokens_map   )
								a   :	str			=       "Tôi là VinAI Research"
								a   :	str			=       "T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
								a   :	str			=       tokenizer.tokenize(lowerCAmelCase__   )
								print(lowerCAmelCase__   )
								self.assertListEqual(lowerCAmelCase__   ,      lowerCAmelCase__   )

								a   :	Union[str, Any]			=       tokens + [tokenizer.unk_token]

								a   :	int			=       [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"""




a		:				str  			=    8.314_4598






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					float					, _lowercase		:					float      )				->float:






	'''simple docstring'''






	if temperature < 0:
		raise Exception("Temperature cannot be less than 0 K"      )
	if molar_mass <= 0:
		raise Exception("Molar mass cannot be less than or equal to 0 kg/mol"      )
	else:
		return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
		import doctest

		# run doctest
		doctest.testmod()

		# example
		a		:				Any  			=    300
		a		:				Dict  			=    28
		a		:				Dict  			=    rms_speed_of_molecule(temperature, molar_mass)
		print(F'''Vrms of Nitrogen gas at 300 K is {vrms} m/s''')


