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 							a_					(		unittest.TestCase		):






 '''simple docstring'''






 @slow
 def 						__snake_case		(     self   :    Optional[int]):







        '''simple docstring'''



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

        # encoder-decoder outputs
        lowerCAmelCase__	      =   torch.tensor([[17, 96_208, 103_471, 2]]).to(lowerCAmelCase__)
        lowerCAmelCase__	      =   torch.tensor(
            [[2, 250, 9_953, 34, 69_489, 1_620, 32, 118_424, 624, 210, 105, 2_913, 1_032, 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, 250_012))
        self.assertEqual(output_predited_logis.shape     ,       lowerCAmelCase__)
        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(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_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(lowerCAmelCase__)
        lowerCAmelCase__	      =   torch.Size((1, 4, 1_024))
        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 						__snake_case		(     self   :    int):







        '''simple docstring'''



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

        lowerCAmelCase__	      =   torch.tensor([[17, 96_208, 103_471, 2]]).to(lowerCAmelCase__)
        lowerCAmelCase__	      =   torch.tensor(
            [[2, 250, 9_953, 34, 69_489, 1_620, 32, 118_424, 624, 210, 105, 2_913, 1_032, 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, 250_012))
        self.assertEqual(output_predited_logis.shape     ,       lowerCAmelCase__)
        # 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(lowerCAmelCase__)

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




 @slow
 def 						__snake_case		(     self   :    Tuple):







        '''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__     ,       )

from __future__ import annotations

def 				UpperCamelCase					(     lowerCAmelCase_ )		->    set[int]:




       '''simple docstring'''






       _A=						{1}
       _A=						[1]
       for _ in range(2							,       depth + 1 ):
              _A=						[*previous_coefficients, 0]
              _A=						[0, *previous_coefficients]
              _A=						[]
              for x, y in zip(lowerCAmelCase_							,       lowerCAmelCase_ ):
                     coefficients.add(x + y )
                     previous_coefficients.append(x + y )
       return coefficients

def 				UpperCamelCase					(     lowerCAmelCase_ )		->    set[int]:




       '''simple docstring'''






       _A=						set()
       for number in unique_coefficients:
              _A=						2
              _A=						number
              while divisor**2 <= copy_number:
                     _A=						0
                     while copy_number % divisor == 0:
                            copy_number //= divisor
                            multiplicity += 1
                     if multiplicity >= 2:
                            non_squarefrees.add(lowerCAmelCase_ )
                            break
                     divisor += 1

       return unique_coefficients.difference(lowerCAmelCase_ )

def 				UpperCamelCase					(     lowerCAmelCase_ = 51 )		->    int:




       '''simple docstring'''






       _A=						get_pascal_triangle_unique_coefficients(lowerCAmelCase_ )
       _A=						get_squarefrees(lowerCAmelCase_ )
       return sum(lowerCAmelCase_ )


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