




def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			return x if y == 0 else greatest_common_divisor(SCREAMING_SNAKE_CASE					,	x % y   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			return (x * y) // greatest_common_divisor(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE = 20   ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					1
			for i in range(1					,	n + 1   ):
						SCREAMING_SNAKE_CASE           =					lcm(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   )
			return g


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












import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
		from transformers import AutoModelForSeqaSeqLM, AutoTokenizer




@require_torch
@require_sentencepiece
@require_tokenizers
class 			UpperCAmelCase_      (   unittest.TestCase       ):




							'''simple docstring'''



							@slow
							def    _UpperCAmelCase     (					self       :	Optional[int]			)			->					Tuple:
										SCREAMING_SNAKE_CASE           =					AutoModelForSeqaSeqLM.from_pretrained("""google/mt5-small"""       ,     return_dict=a			).to(a			)
										SCREAMING_SNAKE_CASE           =					AutoTokenizer.from_pretrained("""google/mt5-small"""			)

										SCREAMING_SNAKE_CASE           =					tokenizer("""Hello there"""       ,     return_tensors="""pt"""			).input_ids
										SCREAMING_SNAKE_CASE           =					tokenizer("""Hi I am"""       ,     return_tensors="""pt"""			).input_ids

										SCREAMING_SNAKE_CASE           =					model(input_ids.to(a			)       ,     labels=labels.to(a			)			).loss
										SCREAMING_SNAKE_CASE           =					-(labels.shape[-1] * loss.item())

										SCREAMING_SNAKE_CASE           =					-84.9127
										self.assertTrue(abs(mtf_score - EXPECTED_SCORE			) < 1E-4			)






