
import random


def     __lowerCAmelCase			(			a__  )       ->  bool:
				__a										=    num - 1
				__a										=    0

				while s % 2 == 0:
								__a										=    s // 2
								t += 1

				for _ in range(5  ):
								__a										=    random.randrange(2						,    num - 1  )
								__a										=    pow(a__						,    a__						,    a__  )
								if v != 1:
												__a										=    0
												while v != (num - 1):
																if i == t - 1:
																				return False
																else:
																				__a										=    i + 1
																				__a										=    (v**2) % num
				return True


def     __lowerCAmelCase			(			a__  )       ->  bool:
				if num < 2:
								return False

				__a										=    [
				    2,
				    3,
				    5,
				    7,
				    11,
				    13,
				    17,
				    19,
				    23,
				    29,
				    31,
				    37,
				    41,
				    43,
				    47,
				    53,
				    59,
				    61,
				    67,
				    71,
				    73,
				    79,
				    83,
				    89,
				    97,
				    101,
				    103,
				    107,
				    109,
				    113,
				    127,
				    131,
				    137,
				    139,
				    149,
				    151,
				    157,
				    163,
				    167,
				    173,
				    179,
				    181,
				    191,
				    193,
				    197,
				    199,
				    211,
				    223,
				    227,
				    229,
				    233,
				    239,
				    241,
				    251,
				    257,
				    263,
				    269,
				    271,
				    277,
				    281,
				    283,
				    293,
				    307,
				    311,
				    313,
				    317,
				    331,
				    337,
				    347,
				    349,
				    353,
				    359,
				    367,
				    373,
				    379,
				    383,
				    389,
				    397,
				    401,
				    409,
				    419,
				    421,
				    431,
				    433,
				    439,
				    443,
				    449,
				    457,
				    461,
				    463,
				    467,
				    479,
				    487,
				    491,
				    499,
				    503,
				    509,
				    521,
				    523,
				    541,
				    547,
				    557,
				    563,
				    569,
				    571,
				    577,
				    587,
				    593,
				    599,
				    601,
				    607,
				    613,
				    617,
				    619,
				    631,
				    641,
				    643,
				    647,
				    653,
				    659,
				    661,
				    673,
				    677,
				    683,
				    691,
				    701,
				    709,
				    719,
				    727,
				    733,
				    739,
				    743,
				    751,
				    757,
				    761,
				    769,
				    773,
				    787,
				    797,
				    809,
				    811,
				    821,
				    823,
				    827,
				    829,
				    839,
				    853,
				    857,
				    859,
				    863,
				    877,
				    881,
				    883,
				    887,
				    907,
				    911,
				    919,
				    929,
				    937,
				    941,
				    947,
				    953,
				    967,
				    971,
				    977,
				    983,
				    991,
				    997,
				]

				if num in low_primes:
								return True

				for prime in low_primes:
								if (num % prime) == 0:
												return False

				return rabin_miller(a__  )


def     __lowerCAmelCase			(			a__ = 1024  )       ->  int:
				while True:
								__a										=    random.randrange(2 ** (keysize - 1)						,    2 ** (keysize)  )
								if is_prime_low_num(a__  ):
												return num


if __name__ == "__main__":
					A     :	Any    = generate_large_prime()
					print(('Prime number:', num))
					print(('is_prime_low_num:', is_prime_low_num(num)))
"""simple docstring"""






import unittest

import numpy as np

from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
       import jax.numpy as jnp

       from transformers.models.roformer.modeling_flax_roformer import (
           FlaxRoFormerForMaskedLM,
           FlaxRoFormerForMultipleChoice,
           FlaxRoFormerForQuestionAnswering,
           FlaxRoFormerForSequenceClassification,
           FlaxRoFormerForTokenClassification,
           FlaxRoFormerModel,
       )


class     UpperCAmelCase						(unittest.TestCase  ):



    """simple docstring"""

    def __init__(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase=13    ,			_UpperCAmelCase=7    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=99    ,			_UpperCAmelCase=32    ,			_UpperCAmelCase=5    ,			_UpperCAmelCase=4    ,			_UpperCAmelCase=37    ,			_UpperCAmelCase="gelu"    ,			_UpperCAmelCase=0.1    ,			_UpperCAmelCase=0.1    ,			_UpperCAmelCase=512    ,			_UpperCAmelCase=16    ,			_UpperCAmelCase=2    ,			_UpperCAmelCase=0.02    ,			_UpperCAmelCase=4    ,			):
       lowercase__:   Dict					=      parent
       lowercase__:   List[str]					=      batch_size
       lowercase__:   Optional[Any]					=      seq_length
       lowercase__:   List[Any]					=      is_training
       lowercase__:   int					=      use_attention_mask
       lowercase__:   Tuple					=      use_token_type_ids
       lowercase__:   Union[str, Any]					=      use_labels
       lowercase__:   str					=      vocab_size
       lowercase__:   str					=      hidden_size
       lowercase__:   str					=      num_hidden_layers
       lowercase__:   Optional[int]					=      num_attention_heads
       lowercase__:   List[str]					=      intermediate_size
       lowercase__:   List[str]					=      hidden_act
       lowercase__:   Tuple					=      hidden_dropout_prob
       lowercase__:   int					=      attention_probs_dropout_prob
       lowercase__:   int					=      max_position_embeddings
       lowercase__:   Union[str, Any]					=      type_vocab_size
       lowercase__:   List[Any]					=      type_sequence_label_size
       lowercase__:   Any					=      initializer_range
       lowercase__:   str					=      num_choices






    def _snake_case			(   self							):
       lowercase__:   int					=      ids_tensor([self.batch_size, self.seq_length]    ,			self.vocab_size							)

       lowercase__:   List[Any]					=      None
       if self.use_attention_mask:
          lowercase__:   Tuple					=      random_attention_mask([self.batch_size, self.seq_length]							)

       lowercase__:   List[Any]					=      None
       if self.use_token_type_ids:
          lowercase__:   str					=      ids_tensor([self.batch_size, self.seq_length]    ,			self.type_vocab_size							)

       lowercase__:   Optional[int]					=      RoFormerConfig(
           vocab_size=self.vocab_size    ,			hidden_size=self.hidden_size    ,			num_hidden_layers=self.num_hidden_layers    ,			num_attention_heads=self.num_attention_heads    ,			intermediate_size=self.intermediate_size    ,			hidden_act=self.hidden_act    ,			hidden_dropout_prob=self.hidden_dropout_prob    ,			attention_probs_dropout_prob=self.attention_probs_dropout_prob    ,			max_position_embeddings=self.max_position_embeddings    ,			type_vocab_size=self.type_vocab_size    ,			is_decoder=_UpperCAmelCase    ,			initializer_range=self.initializer_range    ,			)

       return config, input_ids, token_type_ids, attention_mask






    def _snake_case			(   self							):
       lowercase__:   str					=      self.prepare_config_and_inputs()
       lowercase__, lowercase__, lowercase__, lowercase__:   Optional[Any]					=      config_and_inputs
       lowercase__:   Dict					=      {'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': attention_mask}
       return config, inputs_dict



@require_flax
class     UpperCAmelCase						(_UpperCAmelCase    ,unittest.TestCase  ):



    """simple docstring"""

    _UpperCAmelCase	:List[str]						    = True

    _UpperCAmelCase	:Union[str, Any]						    = (
        (
            FlaxRoFormerModel,
            FlaxRoFormerForMaskedLM,
            FlaxRoFormerForSequenceClassification,
            FlaxRoFormerForTokenClassification,
            FlaxRoFormerForMultipleChoice,
            FlaxRoFormerForQuestionAnswering,
        )
        if is_flax_available()
        else ()
    )






    def _snake_case			(   self							):
       lowercase__:   str					=      FlaxRoFormerModelTester(self							)






    @slow
    def _snake_case			(   self							):
       for model_class_name in self.all_model_classes:
          lowercase__:   Dict					=      model_class_name.from_pretrained('''junnyu/roformer_chinese_small'''    ,			from_pt=_UpperCAmelCase							)
          lowercase__:   int					=      model(np.ones((1, 1)							)							)
          self.assertIsNotNone(_UpperCAmelCase							)



@require_flax
class     UpperCAmelCase						(unittest.TestCase  ):



    """simple docstring"""

    @slow
    def _snake_case			(   self							):
       lowercase__:   Any					=      FlaxRoFormerForMaskedLM.from_pretrained('''junnyu/roformer_chinese_base'''							)
       lowercase__:   Optional[int]					=      jnp.array([[0, 1, 2, 3, 4, 5]]							)
       lowercase__:   List[Any]					=      model(_UpperCAmelCase							)[0]

       lowercase__:   str					=      50000

       lowercase__:   Tuple					=      (1, 6, vocab_size)
       self.assertEqual(output.shape    ,			_UpperCAmelCase							)

       lowercase__:   List[Any]					=      jnp.array(
           [[[-0.1_205, -1.0_265, 0.2_922], [-1.5_134, 0.1_974, 0.1_519], [-5.0_135, -3.9_003, -0.8_404]]]							)

       self.assertTrue(jnp.allclose(output[:, :3, :3]    ,			_UpperCAmelCase    ,			atol=1e-4							)							)
