





"""simple docstring"""






import unittest

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


if is_torch_available():
    import torch

    from transformers import XLMProphetNetForConditionalGeneration, XLMProphetNetTokenizer



@require_torch
class 						lowerCAmelCase       (   unittest.TestCase				):






       @slow
       def 				__A			( self  ):
              _UpperCAmelCase			     =  XLMProphetNetForConditionalGeneration.from_pretrained('microsoft/xprophetnet-large-wiki100-cased'  )
              model.to(a__  )

              # encoder-decoder outputs
              _UpperCAmelCase			     =  torch.tensor([[17, 9_62_08, 10_34_71, 2]]  ).to(a__  )
              _UpperCAmelCase			     =  torch.tensor(
                  [[2, 2_50, 99_53, 34, 6_94_89, 16_20, 32, 11_84_24, 6_24, 2_10, 1_05, 29_13, 10_32, 3_51]]  ).to(a__  )
              _UpperCAmelCase			     =  model(
                  input_ids=a__     ,	attention_mask=a__     ,	encoder_outputs=a__     ,	decoder_input_ids=a__  )
              _UpperCAmelCase			     =  output[0]
              _UpperCAmelCase			     =  torch.Size((1, 14, 25_00_12)  )
              self.assertEqual(output_predited_logis.shape     ,	a__  )
              _UpperCAmelCase			     =  torch.tensor(
                  [[[-6.3_986, -8.2_391, 12.5_189], [-6.3_289, -8.0_864, 12.6_211], [-6.2_418, -8.0_445, 12.7_968]]]  ).to(a__  )
              self.assertTrue(torch.allclose(output_predited_logis[:, :3, :3]     ,	a__     ,	atol=1E-4  )  )

              # encoder outputs
              _UpperCAmelCase			     =  model.prophetnet.encoder(a__  )[0]
              _UpperCAmelCase			     =  torch.tensor(
                  [[[-1.4_260, -0.7_628, 0.8_453], [-1.4_719, -0.1_391, 0.7_807], [-1.7_678, 0.0_114, 0.4_646]]]  ).to(a__  )
              _UpperCAmelCase			     =  torch.Size((1, 4, 10_24)  )
              self.assertEqual(encoder_outputs.shape     ,	a__  )
              self.assertTrue(torch.allclose(encoder_outputs[:, :3, :3]     ,	a__     ,	atol=1E-4  )  )

              # decoder outputs
              _UpperCAmelCase			     =  model.prophetnet.decoder(
                  a__     ,	encoder_hidden_states=a__     ,	)
              _UpperCAmelCase			     =  decoder_outputs[1].view(1     ,	model.config.ngram     ,	14     ,	-1  )
              _UpperCAmelCase			     =  model.lm_head(a__  )
              _UpperCAmelCase			     =  predicting_streams_logits[:, 0]
              self.assertTrue(torch.allclose(next_first_stream_logits[:, :3, :3]     ,	a__     ,	atol=1E-4  )  )






       @slow
       def 				__A			( self  ):
              _UpperCAmelCase			     =  XLMProphetNetForConditionalGeneration.from_pretrained(
                  'microsoft/xprophetnet-large-wiki100-cased-xglue-ntg'  )
              model.to(a__  )

              _UpperCAmelCase			     =  torch.tensor([[17, 9_62_08, 10_34_71, 2]]  ).to(a__  )
              _UpperCAmelCase			     =  torch.tensor(
                  [[2, 2_50, 99_53, 34, 6_94_89, 16_20, 32, 11_84_24, 6_24, 2_10, 1_05, 29_13, 10_32, 3_51]]  ).to(a__  )
              _UpperCAmelCase			     =  model(
                  input_ids=a__     ,	attention_mask=a__     ,	encoder_outputs=a__     ,	decoder_input_ids=a__  )
              _UpperCAmelCase			     =  output[0]
              _UpperCAmelCase			     =  torch.Size((1, 14, 25_00_12)  )
              self.assertEqual(output_predited_logis.shape     ,	a__  )
              # compare the actual values for a slice.
              _UpperCAmelCase			     =  torch.tensor(
                  [[[-9.2_253, -9.7_173, -6.3_529], [-7.6_701, -9.0_145, -1.9_382], [-8.0_195, -7.0_004, -0.1_523]]]  ).to(a__  )

              self.assertTrue(torch.allclose(output_predited_logis[:, :3, :3]     ,	a__     ,	atol=1E-4  )  )






       @slow
       def 				__A			( self  ):
              _UpperCAmelCase			     =  XLMProphetNetForConditionalGeneration.from_pretrained(
                  'microsoft/xprophetnet-large-wiki100-cased-xglue-ntg'  )
              model.to(a__  )
              _UpperCAmelCase			     =  5_12

              _UpperCAmelCase			     =  XLMProphetNetTokenizer.from_pretrained('microsoft/xprophetnet-large-wiki100-cased-xglue-ntg'  )

              _UpperCAmelCase			     =  (
                  """Microsoft Corporation intends to officially end free support for the Windows 7 operating system after"""
                  """ January 14, 2020, according to the official portal of the organization. From that day, users of this"""
                  """ system will not be able to receive security updates, which could make their computers vulnerable to"""
                  """ cyber attacks."""
              )
              _UpperCAmelCase			     =  (
                  """орпорация Microsoft намерена официально прекратить бесплатную поддержку операционной системы Windows 7"""
                  """ после 14 января 2020 года, сообщается на официальном портале организации . С указанного дня пользователи"""
                  """ этой системы не смогут получать обновления безопасности, из-за чего их компьютеры могут стать уязвимыми"""
                  """ к кибератакам."""
              )
              _UpperCAmelCase			     =  (
                  """根据该组织的官方门户网站，微软公司打算在2020年1月14日之后正式终止对Windows 7操作系统的免费支持。从那时起，该系统的用户将无法接收安全更新，这可能会使他们的计算机容易受到网络攻击。"""
              )

              _UpperCAmelCase			     =  tokenizer(
                  [EN_SENTENCE, RU_SENTENCE, ZH_SENTENCE]     ,	padding=a__     ,	max_length=2_55     ,	return_tensors='pt'  ).input_ids
              _UpperCAmelCase			     =  input_ids.to(a__  )

              _UpperCAmelCase			     =  model.generate(
                  a__     ,	num_beams=10     ,	length_penalty=1.0     ,	no_repeat_ngram_size=3     ,	early_stopping=a__  )
              _UpperCAmelCase			     =  [tokenizer.decode(a__     ,	skip_special_tokens=a__  ) for g in summary_ids]
              _UpperCAmelCase			     =  """Microsoft to end Windows 7 free support after January 14, 2020"""
              _UpperCAmelCase			     =  """Microsoft намерена прекратить бесплатную поддержку Windows 7 после 14 января 2020 года"""
              _UpperCAmelCase			     =  """微软打算终止对Windows 7操作系统的免费支持"""
              self.assertListEqual(
                  [EXPECTED_TITLE_EN, EXPECTED_TITLE_RU, EXPECTED_TITLE_ZH]     ,	a__     ,	)

              _UpperCAmelCase			     =  model.generate(
                  a__     ,	num_beams=1     ,	length_penalty=1.0     ,	no_repeat_ngram_size=3     ,	early_stopping=a__  )
              _UpperCAmelCase			     =  [
                  tokenizer.convert_ids_to_tokens(a__     ,	skip_special_tokens=a__  ) for g in summary_ids_beama
              ]
              _UpperCAmelCase			     =  """▁Microsoft ▁to ▁end ▁free ▁support ▁for ▁Windows ▁7""".split(' '  )
              _UpperCAmelCase			     =  """▁Microsoft ▁намерен а ▁прекрати ть ▁бес плат ную ▁поддержку ▁Windows ▁7 ▁после ▁14 ▁января ▁2020 ▁года""".split(
                  ' '  )
              _UpperCAmelCase			     =  """微软 公司 打算 终止 对 Windows ▁7 操作 系统的 免费 支持""".split(' '  )
              self.assertListEqual(
                  [EXPECTED_TITLE_EN_BEAM1_TOK, EXPECTED_TITLE_RU_BEAM1_TOK, EXPECTED_TITLE_ZH_BEAM1_TOK]     ,	a__     ,	)










'''simple docstring'''
import unittest
from timeit import timeit



def 				lowerCAmelCase__	(       UpperCAmelCase    ,       UpperCAmelCase     ):






       """simple docstring"""





       snake_case__					:	Any          =					first_num if first_num >= second_num else second_num
       snake_case__					:	Optional[Any]          =					max_num
       while (common_mult % first_num > 0) or (common_mult % second_num > 0):
              common_mult += max_num
       return common_mult



def 				lowerCAmelCase__	(       UpperCAmelCase    ,       UpperCAmelCase     ):






       """simple docstring"""





       return b if a == 0 else greatest_common_divisor(b % a    ,       UpperCAmelCase     )



def 				lowerCAmelCase__	(       UpperCAmelCase    ,       UpperCAmelCase     ):






       """simple docstring"""





       return first_num // greatest_common_divisor(UpperCAmelCase    ,       UpperCAmelCase     ) * second_num



def 				lowerCAmelCase__	(       ):






       """simple docstring"""





       snake_case__					:	Tuple          =					(
           """from __main__ import least_common_multiple_slow, least_common_multiple_fast"""
       )
       print(
           """least_common_multiple_slow():"""    ,       timeit("""least_common_multiple_slow(1000, 999)"""    ,       setup=UpperCAmelCase     )    ,       )
       print(
           """least_common_multiple_fast():"""    ,       timeit("""least_common_multiple_fast(1000, 999)"""    ,       setup=UpperCAmelCase     )    ,       )







class 					_A						(						unittest.TestCase							):



   '''simple docstring'''






   _lowercase    						= (
       (10, 20),
       (13, 15),
       (4, 31),
       (10, 42),
       (43, 34),
       (5, 12),
       (12, 25),
       (10, 25),
       (6, 9),
   )
   _lowercase    						= (20, 195, 124, 210, 1462, 60, 300, 50, 18)




   def   __lowerCAmelCase						(	self	:					Optional[int]						)->	Optional[Any]:
          for i, (first_num, second_num) in enumerate(self.test_inputs						):
                 snake_case__					:	List[Any]          =					least_common_multiple_slow(lowerCamelCase					, lowerCamelCase						)
                 snake_case__					:	Optional[Any]          =					least_common_multiple_fast(lowerCamelCase					, lowerCamelCase						)
                 with self.subTest(i=lowerCamelCase						):
                        self.assertEqual(lowerCamelCase					, self.expected_results[i]						)
                        self.assertEqual(lowerCamelCase					, self.expected_results[i]						)


if __name__ == "__main__":
     benchmark()
     unittest.main()




