





'''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


A_		:  Union[str, Any]		 =						get_tests_dir("fixtures/test_sentencepiece.model")
@require_sentencepiece
class 					__snake_case  (					__SCREAMING_SNAKE_CASE		,				unittest.TestCase							):






   '''simple docstring'''





   lowerCamelCase__    							=      XLMProphetNetTokenizer
   lowerCamelCase__    							=      False
   lowerCamelCase__    							=      True

   def 		__UpperCamelCase						(							self       ):
    super().setUp()

    # We have a SentencePiece fixture for testing
    snake_case__     :					List[str]    =  XLMProphetNetTokenizer(__SCREAMING_SNAKE_CASE	,		keep_accents=__SCREAMING_SNAKE_CASE       )
    tokenizer.save_pretrained(self.tmpdirname       )

   def 		__UpperCamelCase						(							self       ):
    snake_case__     :					Optional[int]    =  """[PAD]"""
    snake_case__     :					Dict    =  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 		__UpperCamelCase						(							self       ):
    snake_case__     :					int    =  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       )	,		1_0_1_2       )

   def 		__UpperCamelCase						(							self       ):
    self.assertEqual(self.get_tokenizer().vocab_size	,		1_0_1_2       )

   def 		__UpperCamelCase						(							self       ):
    snake_case__     :					Optional[Any]    =  XLMProphetNetTokenizer(__SCREAMING_SNAKE_CASE	,		keep_accents=__SCREAMING_SNAKE_CASE       )

    snake_case__     :					Union[str, Any]    =  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 [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]	,		)

    snake_case__     :					Optional[int]    =  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""",
            """.""",
        ]	,		)
    snake_case__     :					Tuple    =  tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE       )
    self.assertListEqual(
        __SCREAMING_SNAKE_CASE	,		[
            value + tokenizer.fairseq_offset
            for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, -9, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, -9, 4]
        ]	,		)

    snake_case__     :					Optional[Any]    =  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 		__UpperCamelCase						(							self       ):
    return XLMProphetNetTokenizer.from_pretrained("""microsoft/xprophetnet-large-wiki100-cased"""       )

   @slow
   def 		__UpperCamelCase						(							self       ):
    snake_case__     :					Dict    =  """Hello World!"""
    snake_case__     :					str    =  [3_5_3_8_9, 6_6_7_2, 4_9, 2]
    self.assertListEqual(__SCREAMING_SNAKE_CASE	,		self.big_tokenizer.encode(__SCREAMING_SNAKE_CASE       )       )


   @slow
   def 		__UpperCamelCase						(							self       ):
    # fmt: off
    snake_case__     :					List[Any]    =  {"""input_ids""": [[1_1_0_7_3, 8_2_7_8_3, 1_8, 2_6, 8_2_7_8_3, 5_4_9, 5_1_5_4_0, 2_4_8, 1_7_2_0_9, 1_3_0_1, 2_1_7, 2_0, 2_1_5_1_8_6, 1_3_2_5, 1_4_7, 1_7_2_0_9, 1_3_0_1, 2_1_7, 2_0, 5_6_3_7_0, 5_3, 1_2_2_0_2_0, 2_0, 1_6_4_7_7, 2_7, 8_7_3_5_5, 4_5_4_8, 2_0, 4_7_2_8, 7_8_3_9_2, 1_7, 1_5_9_9_6_9, 1_8, 2_6, 2_4_4_9_1, 6_2_9, 1_5, 5_3_8, 2_2_7_0_4, 5_4_3_9, 1_5, 2_7_8_8, 2_4_4_9_1, 9_8_8_5, 1_5, 4_3_5_3_4, 6_0_5, 1_5, 8_1_4, 1_8_4_0_3, 3_3_2_0_0, 2_9, 1_5, 4_3_5_3_4, 2_4_4_5_8, 1_2_4_1_0, 1_1_1, 2_4_9_6_6, 8_3_6_6_9, 9_6_3_7, 1_4_4_0_6_8, 2_6, 8_5_0, 2_2_3_4_6, 2_7, 1_4_7, 2_4_9_6_6, 8_3_6_6_9, 8_3_4_9_0, 2_6, 3_9_1_1_3, 7_3_5, 2_7, 6_8_9, 6_5_6, 2_8_0_0, 1_3_3_9, 4_6_0_0, 5_3, 1_2_2_0_2_0, 1_1_5_7_8_5, 3_4, 8_1_6, 1_3_3_9, 4_6_8_8_7, 1_8, 1_4_7, 5_3_9_0_5, 1_9_5_1, 4_2_2_3_8, 4_1_1_7_0, 1_7_7_3_2, 8_3_4, 4_3_6, 1_5, 2_7_5_2_3, 9_8_7_3_3, 2_1_7, 1_4_7, 5_5_4_2, 4_9_8_1, 9_3_0, 1_7_3_4_7, 1_6, 2], [2_0_0_9_1, 6_2_9, 9_4, 8_2_7_8_6, 5_8, 4_9_0, 2_0, 1_5_2_8, 8_4, 5_3_9_0_5, 3_4_4, 8_0_5_9_2, 1_1_0_1_2_8, 1_8_8_2_2, 5_2_6_7, 1_3_0_6, 6_2, 1_5_2_5_3_7, 3_0_8, 7_9_9_7, 4_0_1, 1_2_4_4_2_7, 5_4_9, 3_5_4_4_2, 2_2_5, 1_0_9, 1_5_0_5_5, 2_5_7_4_8, 1_4_7, 7_1_1_9, 4_3_7_1_2, 3_4, 7_6_7, 1_3_5_3_6_6, 1_8, 1_6, 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], [5_9_2, 6_3_7_8_4, 1_1_9_4_6_6, 1_7, 1_4_7_8_0_8, 8_8_2_1_4, 1_8, 6_5_6, 8_1, 3_2, 3_2_9_6, 1_0_2_8_0, 1_6, 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"""	,		)





"""simple docstring"""


def      __UpperCAmelCase       (      lowercase		):







  """simple docstring"""
  _UpperCAmelCase    			=   0
  _UpperCAmelCase    			=   len(lowercase		)

  for i in range(n - 1		):
    for j in range(i + 1 ,lowercase		):
      if arr[i] > arr[j]:
        num_inversions += 1

  return num_inversions






def      __UpperCAmelCase       (      lowercase		):







  """simple docstring"""
  if len(lowercase		) <= 1:
    return arr, 0
  _UpperCAmelCase    			=   len(lowercase		) // 2
  _UpperCAmelCase    			=   arr[0:mid]
  _UpperCAmelCase    			=   arr[mid:]

  _UpperCAmelCase			,					_UpperCAmelCase    			=   count_inversions_recursive(lowercase		)
  _UpperCAmelCase			,					_UpperCAmelCase    			=   count_inversions_recursive(lowercase		)
  _UpperCAmelCase			,					_UpperCAmelCase    			=   _count_cross_inversions(lowercase ,lowercase		)

  _UpperCAmelCase    			=   inversion_p + inversions_q + cross_inversions
  return c, num_inversions






def      __UpperCAmelCase       (      lowercase ,lowercase		):







  """simple docstring"""
  _UpperCAmelCase    			=   []
  _UpperCAmelCase    			=   _UpperCAmelCase    			=   _UpperCAmelCase    			=   0
  while i < len(lowercase		) and j < len(lowercase		):
    if p[i] > q[j]:
      # if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
      # These are all inversions. The claim emerges from the
      # property that P is sorted.
      num_inversion += len(lowercase		) - i
      r.append(q[j]		)
      j += 1
    else:
      r.append(p[i]		)
      i += 1

  if i < len(lowercase		):
    r.extend(p[i:]		)
  else:
    r.extend(q[j:]		)

  return r, num_inversion






def      __UpperCAmelCase       (      ):







  """simple docstring"""
  _UpperCAmelCase    			=   [10, 2, 1, 5, 5, 2, 11]

  # this arr has 8 inversions:
  # (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

  _UpperCAmelCase    			=   count_inversions_bf(lowercase		)
  _UpperCAmelCase			,					_UpperCAmelCase    			=   count_inversions_recursive(lowercase		)

  assert num_inversions_bf == num_inversions_recursive == 8

  print("""number of inversions = """ ,lowercase		)

  # testing an array with zero inversion (a sorted arr_1)

  arr_a.sort()
  _UpperCAmelCase    			=   count_inversions_bf(lowercase		)
  _UpperCAmelCase			,					_UpperCAmelCase    			=   count_inversions_recursive(lowercase		)

  assert num_inversions_bf == num_inversions_recursive == 0
  print("""number of inversions = """ ,lowercase		)

  # an empty list should also have zero inversions
  _UpperCAmelCase    			=   []
  _UpperCAmelCase    			=   count_inversions_bf(lowercase		)
  _UpperCAmelCase			,					_UpperCAmelCase    			=   count_inversions_recursive(lowercase		)

  assert num_inversions_bf == num_inversions_recursive == 0
  print("""number of inversions = """ ,lowercase		)


if __name__ == "__main__":
    main()
