
def     _a					(						lowerCamelCase,	lowerCamelCase							):
 return x if y == 0 else greatest_common_divisor(lowerCamelCase,	x % y							)





def     _a					(						lowerCamelCase,	lowerCamelCase							):
 return (x * y) // greatest_common_divisor(lowerCamelCase,	lowerCamelCase							)





def     _a					(						lowerCamelCase = 20							):
 lowerCamelCase		:	Any							=      1
 for i in range(1,	n + 1							):
  lowerCamelCase		:	Dict							=      lcm(lowerCamelCase,	lowerCamelCase							)
 return g


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






from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
      import numpy as np
      import tensorflow as tf

      from transformers import TFCamembertModel





@require_tf
@require_sentencepiece
@require_tokenizers
class 							A__		(	unittest.TestCase):
      @slow
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Union[str, Any]							=      TFCamembertModel.from_pretrained("""jplu/tf-camembert-base"""      )

       lowerCamelCase		:	Any							=      tf.convert_to_tensor(
           [[5, 1_2_1, 1_1, 6_6_0, 1_6, 7_3_0, 2_5_5_4_3, 1_1_0, 8_3, 6]]    ,  dtype=tf.intaa    ,  )  # J'aime le camembert !"

       lowerCamelCase		:	str							=      model(__magic_name__      )["""last_hidden_state"""]
       lowerCamelCase		:	Union[str, Any]							=      tf.TensorShape((1, 1_0, 7_6_8)      )
       self.assertEqual(output.shape    ,  __magic_name__      )
       # compare the actual values for a slice.
       lowerCamelCase		:	Dict							=      tf.convert_to_tensor(
           [[[-0.0_254, 0.0_235, 0.1_027], [0.0_606, -0.1_811, -0.0_418], [-0.1_561, -0.1_127, 0.2_687]]]    ,  dtype=tf.floataa    ,  )
       # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
       # camembert.eval()
       # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

       self.assertTrue(np.allclose(output[:, :3, :3].numpy()    ,  expected_slice.numpy()    ,  atol=1e-4      )      )




