

'''simple docstring'''

import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin






class    snake_case     (      lowercase_,						unittest.TestCase		):






				"""simple docstring"""
				_a    	=     PhobertTokenizer
				_a    	=     False



				def   a__					(    self       )     ->							Dict:
											super().setUp()

											# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
											SCREAMING_SNAKE_CASE_				=				['T@@', 'i', 'I', 'R@@', 'r', 'e@@']
											SCREAMING_SNAKE_CASE_				=				dict(zip(_lowercase,     range(len(_lowercase       )       )       )       )
											SCREAMING_SNAKE_CASE_				=				['#version: 0.2', 'l à</w>']
											SCREAMING_SNAKE_CASE_				=				{'unk_token': '<unk>'}

											SCREAMING_SNAKE_CASE_				=				os.path.join(self.tmpdirname,     VOCAB_FILES_NAMES['vocab_file']       )
											SCREAMING_SNAKE_CASE_				=				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(_lowercase       )       )



				def   a__					(    self,     **_lowercase       )     ->							List[Any]:
											kwargs.update(self.special_tokens_map       )
											return PhobertTokenizer.from_pretrained(self.tmpdirname,     **_lowercase       )



				def   a__					(    self,     _lowercase       )     ->							Union[str, Any]:
											SCREAMING_SNAKE_CASE_				=				'Tôi là VinAI Research'
											SCREAMING_SNAKE_CASE_				=				'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]:
											SCREAMING_SNAKE_CASE_				=				PhobertTokenizer(self.vocab_file,     self.merges_file,     **self.special_tokens_map       )
											SCREAMING_SNAKE_CASE_				=				'Tôi là VinAI Research'
											SCREAMING_SNAKE_CASE_				=				'T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'.split()
											SCREAMING_SNAKE_CASE_				=				tokenizer.tokenize(_lowercase       )
											print(_lowercase       )
											self.assertListEqual(_lowercase,     _lowercase       )

											SCREAMING_SNAKE_CASE_				=				tokens + [tokenizer.unk_token]

											SCREAMING_SNAKE_CASE_				=				[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(_lowercase       ),     _lowercase       )








'''simple docstring'''

import os

# Precomputes a list of the 100 first triangular numbers
SCREAMING_SNAKE_CASE							:				List[Any]     	=			[int(0.5 * n * (n + 1)) for n in range(1, 101)]




def 							_UpperCamelCase				(   )      -> List[Any]:
							SCREAMING_SNAKE_CASE_				=				os.path.dirname(os.path.realpath(lowerCAmelCase__   )   )
							SCREAMING_SNAKE_CASE_				=				os.path.join(lowerCAmelCase__		,'words.txt'   )

							SCREAMING_SNAKE_CASE_				=				''
							with open(lowerCAmelCase__   ) as f:
														SCREAMING_SNAKE_CASE_				=				f.readline()

							SCREAMING_SNAKE_CASE_				=				[word.strip('"'   ) for word in words.strip('\r\n'   ).split(','   )]
							SCREAMING_SNAKE_CASE_				=				[
							    word
							    for word in [sum(ord(lowerCAmelCase__   ) - 64 for x in word   ) for word in words]
							    if word in TRIANGULAR_NUMBERS
							]
							return len(lowerCAmelCase__   )


if __name__ == "__main__":
							print(solution())





