


"""simple docstring"""







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


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


@require_sentencepiece
class 				SCREAMING_SNAKE_CASE__    (		lowercase       ,   unittest.TestCase    ):
       """simple docstring"""


       a  :    int       =XLMProphetNetTokenizer
       a  :    str       =False
       a  :    Any       =True

       def 	lowercase__							(						self						):






         """simple docstring"""





         super().setUp()

         # We have a SentencePiece fixture for testing
         lowerCAmelCase					:					Optional[Any]								=							XLMProphetNetTokenizer(snake_case__		,					keep_accents=snake_case__						)
         tokenizer.save_pretrained(self.tmpdirname						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[int]								=							"[PAD]"
         lowerCAmelCase					:					List[Any]								=							0

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

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Union[str, Any]								=							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(snake_case__						)		,					1_012						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         self.assertEqual(self.get_tokenizer().vocab_size		,					1_012						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Union[str, Any]								=							XLMProphetNetTokenizer(snake_case__		,					keep_accents=snake_case__						)

         lowerCAmelCase					:					List[Any]								=							tokenizer.tokenize("This is a test"						)
         self.assertListEqual(snake_case__		,					["▁This", "▁is", "▁a", "▁t", "est"]						)

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

         lowerCAmelCase					:					Union[str, Any]								=							tokenizer.tokenize("I was born in 92000, and this is falsé."						)
         self.assertListEqual(
             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",
                 ".",
             ]		,					)
         lowerCAmelCase					:					str								=							tokenizer.convert_tokens_to_ids(snake_case__						)
         self.assertListEqual(
             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]
             ]		,					)

         lowerCAmelCase					:					List[Any]								=							tokenizer.convert_ids_to_tokens(snake_case__						)
         self.assertListEqual(
             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 	lowercase__							(						self						):






         """simple docstring"""





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

       @slow
       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[Any]								=							"Hello World!"
         lowerCAmelCase					:					int								=							[35_389, 6_672, 49, 2]
         self.assertListEqual(snake_case__		,					self.big_tokenizer.encode(snake_case__						)						)







       @slow
       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[str]								=							{"input_ids": [[11_073, 82_783, 18, 26, 82_783, 549, 51_540, 248, 17_209, 1_301, 217, 20, 215_186, 1_325, 147, 17_209, 1_301, 217, 20, 56_370, 53, 122_020, 20, 16_477, 27, 87_355, 4_548, 20, 4_728, 78_392, 17, 159_969, 18, 26, 24_491, 629, 15, 538, 22_704, 5_439, 15, 2_788, 24_491, 9_885, 15, 43_534, 605, 15, 814, 18_403, 33_200, 29, 15, 43_534, 24_458, 12_410, 111, 24_966, 83_669, 9_637, 144_068, 26, 850, 22_346, 27, 147, 24_966, 83_669, 83_490, 26, 39_113, 735, 27, 689, 656, 2_800, 1_339, 4_600, 53, 122_020, 115_785, 34, 816, 1_339, 46_887, 18, 147, 53_905, 1_951, 42_238, 41_170, 17_732, 834, 436, 15, 27_523, 98_733, 217, 147, 5_542, 4_981, 930, 17_347, 16, 2], [20_091, 629, 94, 82_786, 58, 490, 20, 1_528, 84, 53_905, 344, 80_592, 110_128, 18_822, 5_267, 1_306, 62, 152_537, 308, 7_997, 401, 124_427, 549, 35_442, 225, 109, 15_055, 25_748, 147, 7_119, 43_712, 34, 767, 135_366, 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, 63_784, 119_466, 17, 147_808, 88_214, 18, 656, 81, 32, 3_296, 10_280, 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=snake_case__		,					model_name="microsoft/xprophetnet-large-wiki100-cased"		,					revision="1acad1643ddd54a44df6a1b797ada8373685d90e"		,					)









"""simple docstring"""







import pytest

from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested

from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def  a__      (    SCREAMING_SNAKE_CASE   :   str    ):  # picklable for multiprocessing


  '''simple docstring'''







  return i + 1
@require_dill_gt_0_3_2
@require_joblibspark
@require_not_windows
def  a__      (    ):


  '''simple docstring'''







  with parallel_backend("spark"    ):
    assert ParallelBackendConfig.backend_name == "spark"

  lowerCAmelCase					:					List[str]								=							[1, 2, 3]
  with pytest.raises(SCREAMING_SNAKE_CASE    ):
    with parallel_backend("unsupported backend"    ):
      map_nested(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				num_proc=2    )

  with pytest.raises(SCREAMING_SNAKE_CASE    ):
    with parallel_backend("unsupported backend"    ):
      map_nested(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				num_proc=-1    )





@require_dill_gt_0_3_2
@require_joblibspark
@require_not_windows
@pytest.mark.parametrize("num_proc"    ,				[2, -1]    )
def  a__      (    SCREAMING_SNAKE_CASE   :   Tuple    ):


  '''simple docstring'''







  lowerCAmelCase					:					Tuple								=							[1, 2]
  lowerCAmelCase					:					int								=							{"a": 1, "b": 2}
  lowerCAmelCase					:					List[str]								=							{"a": [1, 2], "b": [3, 4]}
  lowerCAmelCase					:					Dict								=							{"a": {"1": 1}, "b": 2}
  lowerCAmelCase					:					Tuple								=							{"a": 1, "b": 2, "c": 3, "d": 4}
  lowerCAmelCase					:					Any								=							[2, 3]
  lowerCAmelCase					:					Any								=							{"a": 2, "b": 3}
  lowerCAmelCase					:					Optional[int]								=							{"a": [2, 3], "b": [4, 5]}
  lowerCAmelCase					:					Optional[int]								=							{"a": {"1": 2}, "b": 3}
  lowerCAmelCase					:					str								=							{"a": 2, "b": 3, "c": 4, "d": 5}

  with parallel_backend("spark"    ):
    assert map_nested(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				num_proc=SCREAMING_SNAKE_CASE    ) == expected_map_nested_sa
    assert map_nested(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				num_proc=SCREAMING_SNAKE_CASE    ) == expected_map_nested_sa
    assert map_nested(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				num_proc=SCREAMING_SNAKE_CASE    ) == expected_map_nested_sa
    assert map_nested(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				num_proc=SCREAMING_SNAKE_CASE    ) == expected_map_nested_sa
    assert map_nested(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				num_proc=SCREAMING_SNAKE_CASE    ) == expected_map_nested_sa





