






'''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


UpperCAmelCase__						:Optional[Any]          =			get_tests_dir("""fixtures/test_sentencepiece.model""")







@require_sentencepiece
class 	SCREAMING_SNAKE_CASE	(      lowercase__    ,   unittest.TestCase  ):
       snake_case__    :     Optional[int]   		=			XLMProphetNetTokenizer
       snake_case__    :     List[Any]   		=			False
       snake_case__    :     Optional[Any]   		=			True




       def 					a_					(					self      : List[Any]					):


            """simple docstring"""







            super().setUp()

            # We have a SentencePiece fixture for testing
            __lowerCamelCase						:       int				   =				XLMProphetNetTokenizer(__lowerCamelCase	,    keep_accents=__lowerCamelCase					)
            tokenizer.save_pretrained(self.tmpdirname					)




       def 					a_					(					self      : int					):


            """simple docstring"""







            __lowerCamelCase						:       Any				   =				"[PAD]"
            __lowerCamelCase						:       Optional[Any]				   =				0

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




       def 					a_					(					self      : List[Any]					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[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(__lowerCamelCase					)	,    1012					)




       def 					a_					(					self      : Any					):


            """simple docstring"""







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




       def 					a_					(					self      : Any					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[Any]				   =				XLMProphetNetTokenizer(__lowerCamelCase	,    keep_accents=__lowerCamelCase					)

            __lowerCamelCase						:       Tuple				   =				tokenizer.tokenize("""This is a test"""					)
            self.assertListEqual(__lowerCamelCase	,    ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]					)

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

            __lowerCamelCase						:       List[Any]				   =				tokenizer.tokenize("""I was born in 92000, and this is falsé."""					)
            self.assertListEqual(
                __lowerCamelCase	,    [
                    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						:       List[str]				   =				tokenizer.convert_tokens_to_ids(__lowerCamelCase					)
            self.assertListEqual(
                __lowerCamelCase	,    [
                    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						:       str				   =				tokenizer.convert_ids_to_tokens(__lowerCamelCase					)
            self.assertListEqual(
                __lowerCamelCase	,    [
                    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      : Optional[int]					):


            """simple docstring"""







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




       @slow
       def 					a_					(					self      : Tuple					):


            """simple docstring"""







            __lowerCamelCase						:       str				   =				"Hello World!"
            __lowerCamelCase						:       str				   =				[35389, 6672, 49, 2]
            self.assertListEqual(__lowerCamelCase	,    self.big_tokenizer.encode(__lowerCamelCase					)					)




       @slow
       def 					a_					(					self      : List[str]					):


            """simple docstring"""







            __lowerCamelCase						:       str				   =				{"input_ids": [[11073, 82783, 18, 26, 82783, 549, 51540, 248, 17209, 1301, 217, 20, 215186, 1325, 147, 17209, 1301, 217, 20, 56370, 53, 122020, 20, 16477, 27, 87355, 4548, 20, 4728, 78392, 17, 159969, 18, 26, 24491, 629, 15, 538, 22704, 5439, 15, 2788, 24491, 9885, 15, 43534, 605, 15, 814, 18403, 33200, 29, 15, 43534, 24458, 12410, 111, 24966, 83669, 9637, 144068, 26, 850, 22346, 27, 147, 24966, 83669, 83490, 26, 39113, 735, 27, 689, 656, 2800, 1339, 4600, 53, 122020, 115785, 34, 816, 1339, 46887, 18, 147, 53905, 1951, 42238, 41170, 17732, 834, 436, 15, 27523, 98733, 217, 147, 5542, 4981, 930, 17347, 16, 2], [20091, 629, 94, 82786, 58, 490, 20, 1528, 84, 53905, 344, 80592, 110128, 18822, 5267, 1306, 62, 152537, 308, 7997, 401, 124427, 549, 35442, 225, 109, 15055, 25748, 147, 7119, 43712, 34, 767, 135366, 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, 63784, 119466, 17, 147808, 88214, 18, 656, 81, 32, 3296, 10280, 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=__lowerCamelCase	,    model_name="""microsoft/xprophetnet-large-wiki100-cased"""	,    revision="""1acad1643ddd54a44df6a1b797ada8373685d90e"""	,    )











'''simple docstring'''

UpperCAmelCase__						:List[Any]          =			256
# Modulus to hash a string
UpperCAmelCase__						:str          =			1_000_003
def     __lowercase  (_lowercase,						_lowercase     )   ->     bool:


     """simple docstring"""
     __lowerCamelCase						:       str				   =				len(_lowercase     )
     __lowerCamelCase						:       List[str]				   =				len(_lowercase     )
     if p_len > t_len:
          return False

     __lowerCamelCase						:       Optional[Any]				   =				0
     __lowerCamelCase						:       Tuple				   =				0
     __lowerCamelCase						:       Dict				   =				1

     # Calculating the hash of pattern and substring of text
     for i in range(_lowercase     ):
          __lowerCamelCase						:       Optional[int]				   =				(ord(pattern[i]     ) + p_hash * alphabet_size) % modulus
          __lowerCamelCase						:       Dict				   =				(ord(text[i]     ) + text_hash * alphabet_size) % modulus
          if i == p_len - 1:
               continue
          __lowerCamelCase						:       Dict				   =				(modulus_power * alphabet_size) % modulus

     for i in range(0,						t_len - p_len + 1     ):
          if text_hash == p_hash and text[i : i + p_len] == pattern:
               return True
          if i == t_len - p_len:
               continue
          # Calculate the https://en.wikipedia.org/wiki/Rolling_hash
          __lowerCamelCase						:       Dict				   =				(
              (text_hash - ord(text[i]     ) * modulus_power) * alphabet_size
              + ord(text[i + p_len]     )
          ) % modulus
     return False
def     __lowercase  ()   ->     None:


     """simple docstring"""
     __lowerCamelCase						:       List[Any]				   =				"""abc1abc12"""
     __lowerCamelCase						:       Optional[Any]				   =				"""alskfjaldsabc1abc1abc12k23adsfabcabc"""
     __lowerCamelCase						:       List[Any]				   =				"""alskfjaldsk23adsfabcabc"""
     assert rabin_karp(_lowercase,						_lowercase     ) and not rabin_karp(_lowercase,						_lowercase     )

     # Test 2)
     __lowerCamelCase						:       Optional[int]				   =				"""ABABX"""
     __lowerCamelCase						:       Dict				   =				"""ABABZABABYABABX"""
     assert rabin_karp(_lowercase,						_lowercase     )

     # Test 3)
     __lowerCamelCase						:       Any				   =				"""AAAB"""
     __lowerCamelCase						:       int				   =				"""ABAAAAAB"""
     assert rabin_karp(_lowercase,						_lowercase     )

     # Test 4)
     __lowerCamelCase						:       Any				   =				"""abcdabcy"""
     __lowerCamelCase						:       Dict				   =				"""abcxabcdabxabcdabcdabcy"""
     assert rabin_karp(_lowercase,						_lowercase     )

     # Test 5)
     __lowerCamelCase						:       str				   =				"""Lü"""
     __lowerCamelCase						:       str				   =				"""Lüsai"""
     assert rabin_karp(_lowercase,						_lowercase     )
     __lowerCamelCase						:       Tuple				   =				"""Lue"""
     assert not rabin_karp(_lowercase,						_lowercase     )
     print("""Success."""     )


if __name__ == "__main__":
   test_rabin_karp()



