import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__magic_name__								=get_tests_dir('''fixtures/test_sentencepiece.model''')



@require_sentencepiece
class     _A   (    __UpperCamelCase	, unittest.TestCase							):
  SCREAMING_SNAKE_CASE_	:	List[Any]						=XLMProphetNetTokenizer
  SCREAMING_SNAKE_CASE_	:	Any						=False
  SCREAMING_SNAKE_CASE_	:	List[Any]						=True






  def 		_a					(self	)		->      Union[str, Any]:





       '''simple docstring'''





       super().setUp()

       # We have a SentencePiece fixture for testing
       UpperCamelCase__										=      XLMProphetNetTokenizer(SCREAMING_SNAKE_CASE_   ,				keep_accents=SCREAMING_SNAKE_CASE_	)
       tokenizer.save_pretrained(self.tmpdirname	)






  def 		_a					(self	)		->      Optional[Any]:





       '''simple docstring'''





       UpperCamelCase__										=      '''[PAD]'''
       UpperCamelCase__										=      0

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(SCREAMING_SNAKE_CASE_	)   ,				SCREAMING_SNAKE_CASE_	)
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(SCREAMING_SNAKE_CASE_	)   ,				SCREAMING_SNAKE_CASE_	)






  def 		_a					(self	)		->      Optional[int]:





       '''simple docstring'''





       UpperCamelCase__										=      list(self.get_tokenizer().get_vocab().keys()	)

       self.assertEqual(vocab_keys[0]   ,				'''[PAD]'''	)
       self.assertEqual(vocab_keys[1]   ,				'''[CLS]'''	)
       self.assertEqual(vocab_keys[-1]   ,				'''j'''	)
       self.assertEqual(len(SCREAMING_SNAKE_CASE_	)   ,				1012	)






  def 		_a					(self	)		->      Optional[int]:





       '''simple docstring'''





       self.assertEqual(self.get_tokenizer().vocab_size   ,				1012	)






  def 		_a					(self	)		->      Optional[int]:





       '''simple docstring'''





       UpperCamelCase__										=      XLMProphetNetTokenizer(SCREAMING_SNAKE_CASE_   ,				keep_accents=SCREAMING_SNAKE_CASE_	)

       UpperCamelCase__										=      tokenizer.tokenize('''This is a test'''	)
       self.assertListEqual(SCREAMING_SNAKE_CASE_   ,				['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']	)

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_	)   ,				[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,				)

       UpperCamelCase__										=      tokenizer.tokenize('''I was born in 92000, and this is falsé.'''	)
       self.assertListEqual(
           SCREAMING_SNAKE_CASE_   ,				[
               SPIECE_UNDERLINE + '''I''',
               SPIECE_UNDERLINE + '''was''',
               SPIECE_UNDERLINE + '''b''',
               '''or''',
               '''n''',
               SPIECE_UNDERLINE + '''in''',
               SPIECE_UNDERLINE + '''''',
               '''9''',
               '''2''',
               '''0''',
               '''0''',
               '''0''',
               ''',''',
               SPIECE_UNDERLINE + '''and''',
               SPIECE_UNDERLINE + '''this''',
               SPIECE_UNDERLINE + '''is''',
               SPIECE_UNDERLINE + '''f''',
               '''al''',
               '''s''',
               '''é''',
               '''.''',
           ]   ,				)
       UpperCamelCase__										=      tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_	)
       self.assertListEqual(
           SCREAMING_SNAKE_CASE_   ,				[
               value + tokenizer.fairseq_offset
               for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
           ]   ,				)

       UpperCamelCase__										=      tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_	)
       self.assertListEqual(
           SCREAMING_SNAKE_CASE_   ,				[
               SPIECE_UNDERLINE + '''I''',
               SPIECE_UNDERLINE + '''was''',
               SPIECE_UNDERLINE + '''b''',
               '''or''',
               '''n''',
               SPIECE_UNDERLINE + '''in''',
               SPIECE_UNDERLINE + '''''',
               '''[UNK]''',
               '''2''',
               '''0''',
               '''0''',
               '''0''',
               ''',''',
               SPIECE_UNDERLINE + '''and''',
               SPIECE_UNDERLINE + '''this''',
               SPIECE_UNDERLINE + '''is''',
               SPIECE_UNDERLINE + '''f''',
               '''al''',
               '''s''',
               '''[UNK]''',
               '''.''',
           ]   ,				)






  @cached_property
  def 		_a					(self	)		->      List[Any]:





       '''simple docstring'''





       return XLMProphetNetTokenizer.from_pretrained('''microsoft/xprophetnet-large-wiki100-cased'''	)






  @slow
  def 		_a					(self	)		->      Tuple:





       '''simple docstring'''





       UpperCamelCase__										=      '''Hello World!'''
       UpperCamelCase__										=      [3_5389, 6672, 49, 2]
       self.assertListEqual(SCREAMING_SNAKE_CASE_   ,				self.big_tokenizer.encode(SCREAMING_SNAKE_CASE_	)	)






  @slow
  def 		_a					(self	)		->      Dict:





       '''simple docstring'''





       UpperCamelCase__										=      {'''input_ids''': [[1_1073, 8_2783, 18, 26, 8_2783, 549, 5_1540, 248, 1_7209, 1301, 217, 20, 21_5186, 1325, 147, 1_7209, 1301, 217, 20, 5_6370, 53, 12_2020, 20, 1_6477, 27, 8_7355, 4548, 20, 4728, 7_8392, 17, 15_9969, 18, 26, 2_4491, 629, 15, 538, 2_2704, 5439, 15, 2788, 2_4491, 9885, 15, 4_3534, 605, 15, 814, 1_8403, 3_3200, 29, 15, 4_3534, 2_4458, 1_2410, 111, 2_4966, 8_3669, 9637, 14_4068, 26, 850, 2_2346, 27, 147, 2_4966, 8_3669, 8_3490, 26, 3_9113, 735, 27, 689, 656, 2800, 1339, 4600, 53, 12_2020, 11_5785, 34, 816, 1339, 4_6887, 18, 147, 5_3905, 1951, 4_2238, 4_1170, 1_7732, 834, 436, 15, 2_7523, 9_8733, 217, 147, 5542, 4981, 930, 1_7347, 16, 2], [2_0091, 629, 94, 8_2786, 58, 490, 20, 1528, 84, 5_3905, 344, 8_0592, 11_0128, 1_8822, 5267, 1306, 62, 15_2537, 308, 7997, 401, 12_4427, 549, 3_5442, 225, 109, 1_5055, 2_5748, 147, 7119, 4_3712, 34, 767, 13_5366, 18, 16, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [592, 6_3784, 11_9466, 17, 14_7808, 8_8214, 18, 656, 81, 32, 3296, 1_0280, 16, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=SCREAMING_SNAKE_CASE_   ,				model_name='''microsoft/xprophetnet-large-wiki100-cased'''   ,				revision='''1acad1643ddd54a44df6a1b797ada8373685d90e'''   ,				)




import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
     import torch

     from transformers.activations import gelu_new, gelu_python, get_activation



@require_torch
class     _A   (    unittest.TestCase							):






  def 		_a					(self	)		->      str:





       '''simple docstring'''





       UpperCamelCase__										=      torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]	)
       UpperCamelCase__										=      get_activation('''gelu'''	)
       self.assertTrue(torch.allclose(gelu_python(SCREAMING_SNAKE_CASE_	)   ,				torch_builtin(SCREAMING_SNAKE_CASE_	)	)	)
       self.assertFalse(torch.allclose(gelu_python(SCREAMING_SNAKE_CASE_	)   ,				gelu_new(SCREAMING_SNAKE_CASE_	)	)	)






  def 		_a					(self	)		->      str:





       '''simple docstring'''





       UpperCamelCase__										=      torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]	)
       UpperCamelCase__										=      get_activation('''gelu'''	)
       UpperCamelCase__										=      get_activation('''gelu_10'''	)

       UpperCamelCase__										=      torch_builtin(SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      geluaa(SCREAMING_SNAKE_CASE_	)

       UpperCamelCase__										=      torch.where(y_gelu_aa < 10.0   ,				1   ,				0	)

       self.assertTrue(torch.max(SCREAMING_SNAKE_CASE_	).item() == 10.0	)
       self.assertTrue(torch.allclose(y_gelu * clipped_mask   ,				y_gelu_aa * clipped_mask	)	)






  def 		_a					(self	)		->      Optional[Any]:





       '''simple docstring'''





       get_activation('''gelu'''	)
       get_activation('''gelu_10'''	)
       get_activation('''gelu_fast'''	)
       get_activation('''gelu_new'''	)
       get_activation('''gelu_python'''	)
       get_activation('''gelu_pytorch_tanh'''	)
       get_activation('''linear'''	)
       get_activation('''mish'''	)
       get_activation('''quick_gelu'''	)
       get_activation('''relu'''	)
       get_activation('''sigmoid'''	)
       get_activation('''silu'''	)
       get_activation('''swish'''	)
       get_activation('''tanh'''	)
       with self.assertRaises(SCREAMING_SNAKE_CASE_	):
            get_activation('''bogus'''	)
       with self.assertRaises(SCREAMING_SNAKE_CASE_	):
            get_activation(SCREAMING_SNAKE_CASE_	)






  def 		_a					(self	)		->      Optional[Any]:





       '''simple docstring'''





       UpperCamelCase__										=      get_activation('''gelu'''	)
       UpperCamelCase__										=      1
       UpperCamelCase__										=      get_activation('''gelu'''	)
       self.assertEqual(acta.a   ,				1	)
       with self.assertRaises(SCREAMING_SNAKE_CASE_	):
            UpperCamelCase__										=      acta.a



