
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 			UpperCamelCase_				(  unittest.TestCase     ):




      '''simple docstring'''







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

            # encoder-decoder outputs
            lowerCAmelCase_						=      torch.tensor([[17, 96_208, 103_471, 2]]).to(_UpperCAmelCase)
            lowerCAmelCase_						=      torch.tensor(
                [[2, 250, 9_953, 34, 69_489, 1_620, 32, 118_424, 624, 210, 105, 2_913, 1_032, 351]]).to(_UpperCAmelCase)
            lowerCAmelCase_						=      model(
                input_ids=_UpperCAmelCase					,					attention_mask=_UpperCAmelCase					,					encoder_outputs=_UpperCAmelCase					,					decoder_input_ids=_UpperCAmelCase)
            lowerCAmelCase_						=      output[0]
            lowerCAmelCase_						=      torch.Size((1, 14, 250_012))
            self.assertEqual(output_predited_logis.shape					,					_UpperCAmelCase)
            lowerCAmelCase_						=      torch.tensor(
                [[[-6.3986, -8.2391, 12.5189], [-6.3289, -8.0864, 12.6211], [-6.2418, -8.0445, 12.7968]]]).to(_UpperCAmelCase)
            self.assertTrue(torch.allclose(output_predited_logis[:, :3, :3]					,					_UpperCAmelCase					,					atol=1E-4))

            # encoder outputs
            lowerCAmelCase_						=      model.prophetnet.encoder(_UpperCAmelCase)[0]
            lowerCAmelCase_						=      torch.tensor(
                [[[-1.4260, -0.7628, 0.8453], [-1.4719, -0.1391, 0.7807], [-1.7678, 0.0114, 0.4646]]]).to(_UpperCAmelCase)
            lowerCAmelCase_						=      torch.Size((1, 4, 1_024))
            self.assertEqual(encoder_outputs.shape					,					_UpperCAmelCase)
            self.assertTrue(torch.allclose(encoder_outputs[:, :3, :3]					,					_UpperCAmelCase					,					atol=1E-4))

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







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

            lowerCAmelCase_						=      torch.tensor([[17, 96_208, 103_471, 2]]).to(_UpperCAmelCase)
            lowerCAmelCase_						=      torch.tensor(
                [[2, 250, 9_953, 34, 69_489, 1_620, 32, 118_424, 624, 210, 105, 2_913, 1_032, 351]]).to(_UpperCAmelCase)
            lowerCAmelCase_						=      model(
                input_ids=_UpperCAmelCase					,					attention_mask=_UpperCAmelCase					,					encoder_outputs=_UpperCAmelCase					,					decoder_input_ids=_UpperCAmelCase)
            lowerCAmelCase_						=      output[0]
            lowerCAmelCase_						=      torch.Size((1, 14, 250_012))
            self.assertEqual(output_predited_logis.shape					,					_UpperCAmelCase)
            # compare the actual values for a slice.
            lowerCAmelCase_						=      torch.tensor(
                [[[-9.2253, -9.7173, -6.3529], [-7.6701, -9.0145, -1.9382], [-8.0195, -7.0004, -0.1523]]]).to(_UpperCAmelCase)

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







      @slow
      def lowercase__		( self):
            lowerCAmelCase_						=      XLMProphetNetForConditionalGeneration.from_pretrained(
                '''microsoft/xprophetnet-large-wiki100-cased-xglue-ntg''')
            model.to(_UpperCAmelCase)
            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=_UpperCAmelCase					,					max_length=255					,					return_tensors='''pt''').input_ids
            lowerCAmelCase_						=      input_ids.to(_UpperCAmelCase)

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

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





_snake_case		  =   {
    "+": lambda x, y: x + y,
    "-": lambda x, y: x - y,
    "*": lambda x, y: x * y,
    "/": lambda x, y: x / y,
}
def lowerCamelCase_       (			A			:      List[Any]						):




      """simple docstring"""
      return c.isdigit()
def lowerCamelCase_       (			A			:      List[Any]						):




      """simple docstring"""
      lowerCAmelCase_						=      []

      # iterate over the string in reverse order
      for c in expression.split()[::-1]:
            # push operand to stack
            if is_operand(A						):
                  stack.append(int(A						)						)

            else:
                  # pop values from stack can calculate the result
                  # push the result onto the stack again
                  lowerCAmelCase_						=      stack.pop()
                  lowerCAmelCase_						=      stack.pop()
                  stack.append(calc[c](A		,					A						)						)

      return stack.pop()


# Driver code
if __name__ == "__main__":
 _snake_case		  =   "+ 9 * 2 6"
 print(evaluate(test_expression))

 _snake_case		  =   "/ * 10 2 + 4 1 "
 print(evaluate(test_expression))



