'''simple docstring'''




import sys







def 			A_   ( _lowerCamelCase			:							int  ,  _lowerCamelCase			:							list[int]    ):
      if not numbers:
            return 0
      if target == 0 and target in numbers:
            return 0
      if not isinstance(_lowerCamelCase  ,  (list, tuple)    ) or not all(
          isinstance(_lowerCamelCase  ,  _lowerCamelCase    ) for number in numbers    ):
            raise ValueError('numbers must be an iterable of integers'    )

      _lowerCAmelCase		   =   _lowerCAmelCase		   =   _lowerCAmelCase		   =   0
      _lowerCAmelCase		   =   sys.maxsize

      while right < len(_lowerCamelCase    ):
            curr_sum += numbers[right]
            while curr_sum >= target and left <= right:
                  _lowerCAmelCase		   =   min(_lowerCamelCase  ,  right - left + 1    )
                  curr_sum -= numbers[left]
                  left += 1
            right += 1

      return 0 if min_len == sys.maxsize else min_len






'''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        SCREAMING_SNAKE_CASE   (				unittest.TestCase ):
  """simple docstring"""







  @slow
  def   a   (  self   :					List[str]					):


        """simple docstring"""



        _lowerCAmelCase		   =   XLMProphetNetForConditionalGeneration.from_pretrained('microsoft/xprophetnet-large-wiki100-cased'					)
        model.to(__lowerCAmelCase					)

        # encoder-decoder outputs
        _lowerCAmelCase		   =   torch.tensor([[17, 9_6208, 10_3471, 2]]					).to(__lowerCAmelCase					)
        _lowerCAmelCase		   =   torch.tensor(
            [[2, 250, 9953, 34, 6_9489, 1620, 32, 11_8424, 624, 210, 105, 2913, 1032, 351]]					).to(__lowerCAmelCase					)
        _lowerCAmelCase		   =   model(
            input_ids=__lowerCAmelCase					,					attention_mask=__lowerCAmelCase					,					encoder_outputs=__lowerCAmelCase					,					decoder_input_ids=__lowerCAmelCase					)
        _lowerCAmelCase		   =   output[0]
        _lowerCAmelCase		   =   torch.Size((1, 14, 25_0012)					)
        self.assertEqual(output_predited_logis.shape					,					__lowerCAmelCase					)
        _lowerCAmelCase		   =   torch.tensor(
            [[[-6.3_9_8_6, -8.2_3_9_1, 1_2.5_1_8_9], [-6.3_2_8_9, -8.0_8_6_4, 1_2.6_2_1_1], [-6.2_4_1_8, -8.0_4_4_5, 1_2.7_9_6_8]]]					).to(__lowerCAmelCase					)
        self.assertTrue(torch.allclose(output_predited_logis[:, :3, :3]					,					__lowerCAmelCase					,					atol=1e-4					)					)

        # encoder outputs
        _lowerCAmelCase		   =   model.prophetnet.encoder(__lowerCAmelCase					)[0]
        _lowerCAmelCase		   =   torch.tensor(
            [[[-1.4_2_6_0, -0.7_6_2_8, 0.8_4_5_3], [-1.4_7_1_9, -0.1_3_9_1, 0.7_8_0_7], [-1.7_6_7_8, 0.0_1_1_4, 0.4_6_4_6]]]					).to(__lowerCAmelCase					)
        _lowerCAmelCase		   =   torch.Size((1, 4, 1024)					)
        self.assertEqual(encoder_outputs.shape					,					__lowerCAmelCase					)
        self.assertTrue(torch.allclose(encoder_outputs[:, :3, :3]					,					__lowerCAmelCase					,					atol=1e-4					)					)

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



  @slow
  def   a   (  self   :					Tuple					):


        """simple docstring"""



        _lowerCAmelCase		   =   XLMProphetNetForConditionalGeneration.from_pretrained(
            'microsoft/xprophetnet-large-wiki100-cased-xglue-ntg'					)
        model.to(__lowerCAmelCase					)

        _lowerCAmelCase		   =   torch.tensor([[17, 9_6208, 10_3471, 2]]					).to(__lowerCAmelCase					)
        _lowerCAmelCase		   =   torch.tensor(
            [[2, 250, 9953, 34, 6_9489, 1620, 32, 11_8424, 624, 210, 105, 2913, 1032, 351]]					).to(__lowerCAmelCase					)
        _lowerCAmelCase		   =   model(
            input_ids=__lowerCAmelCase					,					attention_mask=__lowerCAmelCase					,					encoder_outputs=__lowerCAmelCase					,					decoder_input_ids=__lowerCAmelCase					)
        _lowerCAmelCase		   =   output[0]
        _lowerCAmelCase		   =   torch.Size((1, 14, 25_0012)					)
        self.assertEqual(output_predited_logis.shape					,					__lowerCAmelCase					)
        # compare the actual values for a slice.
        _lowerCAmelCase		   =   torch.tensor(
            [[[-9.2_2_5_3, -9.7_1_7_3, -6.3_5_2_9], [-7.6_7_0_1, -9.0_1_4_5, -1.9_3_8_2], [-8.0_1_9_5, -7.0_0_0_4, -0.1_5_2_3]]]					).to(__lowerCAmelCase					)

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



  @slow
  def   a   (  self   :					int					):


        """simple docstring"""



        _lowerCAmelCase		   =   XLMProphetNetForConditionalGeneration.from_pretrained(
            'microsoft/xprophetnet-large-wiki100-cased-xglue-ntg'					)
        model.to(__lowerCAmelCase					)
        _lowerCAmelCase		   =   512

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

        _lowerCAmelCase		   =   (
            '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.'
        )
        _lowerCAmelCase		   =   (
            '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.'
        )
        _lowerCAmelCase		   =   (
            '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。'
        )

        _lowerCAmelCase		   =   tokenizer(
            [EN_SENTENCE, RU_SENTENCE, ZH_SENTENCE]					,					padding=__lowerCAmelCase					,					max_length=255					,					return_tensors='pt'					).input_ids
        _lowerCAmelCase		   =   input_ids.to(__lowerCAmelCase					)

        _lowerCAmelCase		   =   model.generate(
            __lowerCAmelCase					,					num_beams=10					,					length_penalty=1.0					,					no_repeat_ngram_size=3					,					early_stopping=__lowerCAmelCase					)
        _lowerCAmelCase		   =   [tokenizer.decode(__lowerCAmelCase					,					skip_special_tokens=__lowerCAmelCase					) for g in summary_ids]
        _lowerCAmelCase		   =   'Microsoft to end Windows 7 free support after January 14, 2020'
        _lowerCAmelCase		   =   'Microsoft намерена прекратить бесплатную поддержку Windows 7 после 14 января 2020 года'
        _lowerCAmelCase		   =   '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]					,					__lowerCAmelCase					,					)

        _lowerCAmelCase		   =   model.generate(
            __lowerCAmelCase					,					num_beams=1					,					length_penalty=1.0					,					no_repeat_ngram_size=3					,					early_stopping=__lowerCAmelCase					)
        _lowerCAmelCase		   =   [
            tokenizer.convert_ids_to_tokens(__lowerCAmelCase					,					skip_special_tokens=__lowerCAmelCase					) for g in summary_ids_beama
        ]
        _lowerCAmelCase		   =   '▁Microsoft ▁to ▁end ▁free ▁support ▁for ▁Windows ▁7'.split(' '					)
        _lowerCAmelCase		   =   '▁Microsoft ▁намерен а ▁прекрати ть ▁бес плат ную ▁поддержку ▁Windows ▁7 ▁после ▁14 ▁января ▁2020 ▁года'.split(
            ' '					)
        _lowerCAmelCase		   =   '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]					,					__lowerCAmelCase					,					)





