






import math



def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     int      )  -> Union[str, Any]:





    """simple docstring"""

    if 1 < number < 4:
        # 2 and 3 are primes
        return True
    elif number < 2 or number % 2 == 0 or number % 3 == 0:
        # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
        return False

    # All primes number are in format of 6k +/- 1
    for i in range(5     ,			int(math.sqrt(SCREAMING_SNAKE_CASE__      ) + 1      )     ,			6      ):
        if number % i == 0 or number % (i + 2) == 0:
            return False
    return True



def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     int = 6_0_0_8_5_1_4_7_5_1_4_3      )  -> Union[str, Any]:





    """simple docstring"""

    try:
        __A             =		int(SCREAMING_SNAKE_CASE__      )
    except (TypeError, ValueError):
        raise TypeError("""Parameter n must be int or castable to int."""      )
    if n <= 0:
        raise ValueError("""Parameter n must be greater than or equal to one."""      )
    __A             =		0
    if is_prime(SCREAMING_SNAKE_CASE__      ):
        return n
    while n % 2 == 0:
        n //= 2
    if is_prime(SCREAMING_SNAKE_CASE__      ):
        return n
    for i in range(3     ,			int(math.sqrt(SCREAMING_SNAKE_CASE__      )      ) + 1     ,			2      ):
        if n % i == 0:
            if is_prime(n // i      ):
                __A             =		n // i
                break
            elif is_prime(SCREAMING_SNAKE_CASE__      ):
                __A             =		i
    return max_number


if __name__ == "__main__":
  print(f"""{solution() = }""")












import unittest

from transformers import ErnieMTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__a :    Optional[Any]								=				get_tests_dir("fixtures/spiece.model")


@require_sentencepiece
@require_tokenizers
class  __lowercase (		lowercase_     , unittest.TestCase					):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE				  =			ErnieMTokenizer
     SCREAMING_SNAKE_CASE				  =			False
     SCREAMING_SNAKE_CASE				  =			True
     SCREAMING_SNAKE_CASE				  =			False
     SCREAMING_SNAKE_CASE				  =			False




     def 						lowerCAmelCase_       (			self    :     Optional[Any]			):


         """simple docstring"""



         super().setUp()

         # We have a SentencePiece fixture for testing
         __A             =		ErnieMTokenizer(UpperCamelCase_	,		unk_token="""<unk>"""	,		pad_token="""<pad>"""			)
         tokenizer.save_pretrained(self.tmpdirname			)




     def 						lowerCAmelCase_       (			self    :     Optional[Any]	,		UpperCamelCase_    :     Tuple			):


         """simple docstring"""



         __A             =		"""this is a test"""
         __A             =		"""this is a test"""
         return input_text, output_text




     def 						lowerCAmelCase_       (			self    :     Optional[int]			):


         """simple docstring"""



         __A             =		"""<pad>"""
         __A             =		0

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




     def 						lowerCAmelCase_       (			self    :     Tuple			):


         """simple docstring"""



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

         self.assertEqual(vocab_keys[0]	,		"""<pad>"""			)
         self.assertEqual(vocab_keys[1]	,		"""<unk>"""			)
         self.assertEqual(vocab_keys[-1]	,		"""▁eloquent"""			)
         self.assertEqual(len(UpperCamelCase_			)	,		30_000			)




     def 						lowerCAmelCase_       (			self    :     Tuple			):


         """simple docstring"""



         self.assertEqual(self.get_tokenizer().vocab_size	,		30_000			)




     def 						lowerCAmelCase_       (			self    :     Union[str, Any]			):


         """simple docstring"""



         if not self.test_rust_tokenizer:
             return

         __A             =		self.get_tokenizer()
         __A             =		self.get_rust_tokenizer()

         __A             =		"""I was born in 92000, and this is falsé."""

         __A             =		tokenizer.tokenize(UpperCamelCase_			)
         __A             =		rust_tokenizer.tokenize(UpperCamelCase_			)
         self.assertListEqual(UpperCamelCase_	,		UpperCamelCase_			)

         __A             =		tokenizer.encode(UpperCamelCase_	,		add_special_tokens=UpperCamelCase_			)
         __A             =		rust_tokenizer.encode(UpperCamelCase_	,		add_special_tokens=UpperCamelCase_			)
         self.assertListEqual(UpperCamelCase_	,		UpperCamelCase_			)

         __A             =		self.get_rust_tokenizer()
         __A             =		tokenizer.encode(UpperCamelCase_			)
         __A             =		rust_tokenizer.encode(UpperCamelCase_			)
         self.assertListEqual(UpperCamelCase_	,		UpperCamelCase_			)




     def 						lowerCAmelCase_       (			self    :     Union[str, Any]			):


         """simple docstring"""



         __A             =		ErnieMTokenizer(UpperCamelCase_	,		do_lower_case=UpperCamelCase_	,		unk_token="""<unk>"""	,		pad_token="""<pad>"""			)

         __A             =		tokenizer.tokenize("""This is a test"""			)
         self.assertListEqual(UpperCamelCase_	,		["""▁this""", """▁is""", """▁a""", """▁test"""]			)

         self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase_			)	,		[48, 25, 21, 1_289]			)

         __A             =		tokenizer.tokenize("""I was born in 92000, and this is falsé."""			)
         # ErnieMTokenizer(paddlenlp implementation) outputs '9' instead of '_9' so to mimic that '_9' is changed to '9'
         self.assertListEqual(
             UpperCamelCase_	,		["""▁i""", """▁was""", """▁born""", """▁in""", """9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """é""", """."""]			)
         __A             =		tokenizer.convert_tokens_to_ids(UpperCamelCase_			)
         self.assertListEqual(UpperCamelCase_	,		[31, 23, 386, 19, 518, 3_050, 15, 17, 48, 25, 8_256, 18, 1, 9]			)

         __A             =		tokenizer.convert_ids_to_tokens(UpperCamelCase_			)
         self.assertListEqual(
             UpperCamelCase_	,		["""▁i""", """▁was""", """▁born""", """▁in""", """9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """."""]	,		)




     def 						lowerCAmelCase_       (			self    :     List[str]			):


         """simple docstring"""



         __A             =		ErnieMTokenizer(UpperCamelCase_	,		unk_token="""<unk>"""	,		pad_token="""<pad>"""			)

         __A             =		tokenizer.encode("""sequence builders"""			)
         __A             =		tokenizer.encode("""multi-sequence build"""			)

         __A             =		tokenizer.build_inputs_with_special_tokens(UpperCamelCase_			)
         __A             =		tokenizer.build_inputs_with_special_tokens(UpperCamelCase_	,		UpperCamelCase_			)

         assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
         assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + [
             tokenizer.sep_token_id
         ] + text_a + [tokenizer.sep_token_id]





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


         """simple docstring"""



         __A             =		{"""input_ids""": [[0, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 9, 304, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 5, 5, 5, 16, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 6_460, 1_328, 4_589, 42, 122_009, 115_774, 23, 3_559, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [0, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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, 581, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=UpperCamelCase_	,		model_name="""susnato/ernie-m-base_pytorch"""	,		sequences=[
                 """Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides """
                 """general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural """
                 """Language Understanding (NLU) and Natural Language Generation (NLG) with over32+ pretrained """
                 """models in100+ languages and deep interoperability between Jax, PyTorch and TensorFlow.""",
                 """BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly """
                 """conditioning on both left and right context in all layers.""",
                 """The quick brown fox jumps over the lazy dog.""",
             ]	,		)




