






"""simple docstring"""



import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin





class 					_UpperCAmelCase       ( _A   ,						unittest.TestCase							):
					SCREAMING_SNAKE_CASE_		:				Any							    =   BioGptTokenizer
					SCREAMING_SNAKE_CASE_		:				int							    =   False




					def   A  (				self     :						Any   )  ->  Tuple:
							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							lowercase_ : Dict							       =   [
							    '''l''',
							    '''o''',
							    '''w''',
							    '''e''',
							    '''r''',
							    '''s''',
							    '''t''',
							    '''i''',
							    '''d''',
							    '''n''',
							    '''w</w>''',
							    '''r</w>''',
							    '''t</w>''',
							    '''lo''',
							    '''low''',
							    '''er</w>''',
							    '''low</w>''',
							    '''lowest</w>''',
							    '''newer</w>''',
							    '''wider</w>''',
							    '''<unk>''',
							]
							lowercase_ : Dict							       =   dict(zip(A    ,						range(len(A   )   )   )   )
							lowercase_ : List[str]							       =   ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

							lowercase_ : Union[str, Any]							       =   os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES['''vocab_file''']   )
							lowercase_ : Any							       =   os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES['''merges_file''']   )
							with open(self.vocab_file    ,						'''w'''   ) as fp:
									fp.write(json.dumps(A   )   )
							with open(self.merges_file    ,						'''w'''   ) as fp:
									fp.write('''\n'''.join(A   )   )




					def   A  (				self     :						Tuple    ,						A     :						Dict   )  ->  int:
							lowercase_ : List[str]							       =   '''lower newer'''
							lowercase_ : List[str]							       =   '''lower newer'''
							return input_text, output_text




					def   A  (				self     :						Any   )  ->  str:
							lowercase_ : Dict							       =   BioGptTokenizer(self.vocab_file    ,						self.merges_file   )

							lowercase_ : List[Any]							       =   '''lower'''
							lowercase_ : Dict							       =   ['''low''', '''er</w>''']
							lowercase_ : Any							       =   tokenizer.tokenize(A   )
							self.assertListEqual(A    ,						A   )

							lowercase_ : List[Any]							       =   tokens + ['''<unk>''']
							lowercase_ : Dict							       =   [14, 15, 20]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(A   )    ,						A   )






					@slow
					def   A  (				self     :						int   )  ->  List[str]:
							lowercase_ : Dict							       =   BioGptTokenizer.from_pretrained('''microsoft/biogpt'''   )

							lowercase_ : int							       =   tokenizer.encode('''sequence builders'''    ,						add_special_tokens=A   )
							lowercase_ : Tuple							       =   tokenizer.encode('''multi-sequence build'''    ,						add_special_tokens=A   )

							lowercase_ : Tuple							       =   tokenizer.build_inputs_with_special_tokens(A   )
							lowercase_ : Tuple							       =   tokenizer.build_inputs_with_special_tokens(A    ,						A   )

							self.assertTrue(encoded_sentence == [2] + text   )
							self.assertTrue(encoded_pair == [2] + text + [2] + text_a   )











"""simple docstring"""



def 						lowercase    (				__snake_case				: int = 1_0_0	):
		lowercase_ : str							       =   0
		lowercase_ : List[Any]							       =   0
		for i in range(1		,					n + 1	):
				sum_of_squares += i**2
				sum_of_ints += i
		return sum_of_ints**2 - sum_of_squares


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



