'''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 		UpperCamelCase__							( self					)			->  List[Any]:
								_lowerCAmelCase					    =XLMProphetNetForConditionalGeneration.from_pretrained('microsoft/xprophetnet-large-wiki100-cased'					)
								model.to(__A					)

								# encoder-decoder outputs
								_lowerCAmelCase					    =torch.tensor([[17, 9_6208, 10_3471, 2]]					).to(__A					)
								_lowerCAmelCase					    =torch.tensor(
								    [[2, 250, 9953, 34, 6_9489, 1620, 32, 11_8424, 624, 210, 105, 2913, 1032, 351]]					).to(__A					)
								_lowerCAmelCase					    =model(
								    input_ids=__A		,    attention_mask=__A		,    encoder_outputs=__A		,    decoder_input_ids=__A					)
								_lowerCAmelCase					    =output[0]
								_lowerCAmelCase					    =torch.Size((1, 14, 25_0012)					)
								self.assertEqual(output_predited_logis.shape		,    __A					)
								_lowerCAmelCase					    =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
								_lowerCAmelCase					    =model.prophetnet.encoder(__A					)[0]
								_lowerCAmelCase					    =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					)
								_lowerCAmelCase					    =torch.Size((1, 4, 1024)					)
								self.assertEqual(encoder_outputs.shape		,    __A					)
								self.assertTrue(torch.allclose(encoder_outputs[:, :3, :3]		,    __A		,    atol=1E-4					)					)

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






		@slow
		def 		UpperCamelCase__							( self					)			->  List[Any]:
								_lowerCAmelCase					    =XLMProphetNetForConditionalGeneration.from_pretrained(
								    'microsoft/xprophetnet-large-wiki100-cased-xglue-ntg'					)
								model.to(__A					)

								_lowerCAmelCase					    =torch.tensor([[17, 9_6208, 10_3471, 2]]					).to(__A					)
								_lowerCAmelCase					    =torch.tensor(
								    [[2, 250, 9953, 34, 6_9489, 1620, 32, 11_8424, 624, 210, 105, 2913, 1032, 351]]					).to(__A					)
								_lowerCAmelCase					    =model(
								    input_ids=__A		,    attention_mask=__A		,    encoder_outputs=__A		,    decoder_input_ids=__A					)
								_lowerCAmelCase					    =output[0]
								_lowerCAmelCase					    =torch.Size((1, 14, 25_0012)					)
								self.assertEqual(output_predited_logis.shape		,    __A					)
								# compare the actual values for a slice.
								_lowerCAmelCase					    =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 		UpperCamelCase__							( self					)			->  str:
								_lowerCAmelCase					    =XLMProphetNetForConditionalGeneration.from_pretrained(
								    'microsoft/xprophetnet-large-wiki100-cased-xglue-ntg'					)
								model.to(__A					)
								_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=__A		,    max_length=255		,    return_tensors='pt'					).input_ids
								_lowerCAmelCase					    =input_ids.to(__A					)

								_lowerCAmelCase					    =model.generate(
								    __A		,    num_beams=10		,    length_penalty=1.0		,    no_repeat_ngram_size=3		,    early_stopping=__A					)
								_lowerCAmelCase					    =[tokenizer.decode(__A		,    skip_special_tokens=__A					) 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]		,    __A		,    )

								_lowerCAmelCase					    =model.generate(
								    __A		,    num_beams=1		,    length_penalty=1.0		,    no_repeat_ngram_size=3		,    early_stopping=__A					)
								_lowerCAmelCase					    =[
								    tokenizer.convert_ids_to_tokens(__A		,    skip_special_tokens=__A					) 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]		,    __A		,    )






'''simple docstring'''

from ..utils import DummyObject, requires_backends
class 	SCREAMING_SNAKE_CASE      (    metaclass=__lowercase):







		"""simple docstring"""
		lowercase :   List[Any]							=				['tensorflow_text']






		def __init__( self		,    *__A		,    **__A					)			->  List[Any]:
								requires_backends(self		,    ['tensorflow_text']					)





