


def 						a    (		lowerCamelCase_ = 1000       ):






				'''simple docstring'''
				lowercase__     				=    -1
				lowercase__     				=    0
				for a in range(1	,     n // 3       ):
								# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
								lowercase__     				=    (n * n - 2 * a * n) // (2 * n - 2 * a)
								lowercase__     				=    n - a - b
								if c * c == (a * a + b * b):
												lowercase__     				=    a * b * c
												if candidate >= product:
																lowercase__     				=    candidate
				return product


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












from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class    _UpperCAmelCase      ( A__			):

				"""simple docstring"""




				lowercase__       							= DistilBertTokenizer
				lowercase__       							= DistilBertTokenizerFast
				lowercase__       							= True




				@slow
				def        lowercase__     (  self		:					str						):

								'''simple docstring'''
								lowercase__     				=    DistilBertTokenizer.from_pretrained('''distilbert-base-uncased'''						)

								lowercase__     				=    tokenizer.encode('''sequence builders''',						add_special_tokens=lowerCamelCase						)
								lowercase__     				=    tokenizer.encode('''multi-sequence build''',						add_special_tokens=lowerCamelCase						)

								lowercase__     				=    tokenizer.build_inputs_with_special_tokens(lowerCamelCase						)
								lowercase__     				=    tokenizer.build_inputs_with_special_tokens(lowerCamelCase,						lowerCamelCase						)

								assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
								assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
								    tokenizer.sep_token_id
								]




