






"""simple docstring"""





from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch

from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch






@require_torch
@require_tf
class      a						(					__lowerCamelCase		):






    def    UpperCamelCase       (       self     :							Optional[int]					)     ->		List[str]:
      lowerCamelCase_         =						SMALL_MODEL_IDENTIFIER
      lowerCamelCase_         =						'''pt'''
      lowerCamelCase_         =						'''tf'''






    def    UpperCamelCase       (       self     :							Dict       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]					)     ->		List[str]:
      lowerCamelCase_         =						AutoModel.from_pretrained(self.test_model					)
      model_pt.save_pretrained(__lowercase					)






    def    UpperCamelCase       (       self     :							Any       ,						__SCREAMING_SNAKE_CASE     :							Dict					)     ->		Optional[Any]:
      lowerCamelCase_         =						TFAutoModel.from_pretrained(self.test_model       ,						from_pt=__lowercase					)
      model_tf.save_pretrained(__lowercase					)






    def    UpperCamelCase       (       self     :							str					)     ->		Optional[Any]:
      lowerCamelCase_         =						'''mock_framework'''

      # Framework provided - return whatever the user provides
      lowerCamelCase_         =						FeaturesManager.determine_framework(self.test_model       ,						__lowercase					)
      self.assertEqual(__lowercase       ,						__lowercase					)

      # Local checkpoint and framework provided - return provided framework
      # PyTorch checkpoint
      with TemporaryDirectory() as local_pt_ckpt:
        self._setup_pt_ckpt(__lowercase					)
        lowerCamelCase_         =						FeaturesManager.determine_framework(__lowercase       ,						__lowercase					)
        self.assertEqual(__lowercase       ,						__lowercase					)

      # TensorFlow checkpoint
      with TemporaryDirectory() as local_tf_ckpt:
        self._setup_tf_ckpt(__lowercase					)
        lowerCamelCase_         =						FeaturesManager.determine_framework(__lowercase       ,						__lowercase					)
        self.assertEqual(__lowercase       ,						__lowercase					)






    def    UpperCamelCase       (       self     :							Dict					)     ->		Optional[Any]:
      # PyTorch checkpoint
      with TemporaryDirectory() as local_pt_ckpt:
        self._setup_pt_ckpt(__lowercase					)
        lowerCamelCase_         =						FeaturesManager.determine_framework(__lowercase					)
        self.assertEqual(__lowercase       ,						self.framework_pt					)

      # TensorFlow checkpoint
      with TemporaryDirectory() as local_tf_ckpt:
        self._setup_tf_ckpt(__lowercase					)
        lowerCamelCase_         =						FeaturesManager.determine_framework(__lowercase					)
        self.assertEqual(__lowercase       ,						self.framework_tf					)

      # Invalid local checkpoint
      with TemporaryDirectory() as local_invalid_ckpt:
        with self.assertRaises(__lowercase					):
          lowerCamelCase_         =						FeaturesManager.determine_framework(__lowercase					)






    def    UpperCamelCase       (       self     :							Optional[Any]					)     ->		Optional[int]:
      lowerCamelCase_         =						MagicMock(return_value=__lowercase					)
      with patch('transformers.onnx.features.is_tf_available'       ,						__lowercase					):
        lowerCamelCase_         =						FeaturesManager.determine_framework(self.test_model					)
        self.assertEqual(__lowercase       ,						self.framework_pt					)

      # PyTorch not in environment -> use TensorFlow
      lowerCamelCase_         =						MagicMock(return_value=__lowercase					)
      with patch('transformers.onnx.features.is_torch_available'       ,						__lowercase					):
        lowerCamelCase_         =						FeaturesManager.determine_framework(self.test_model					)
        self.assertEqual(__lowercase       ,						self.framework_tf					)

      # Both in environment -> use PyTorch
      lowerCamelCase_         =						MagicMock(return_value=__lowercase					)
      lowerCamelCase_         =						MagicMock(return_value=__lowercase					)
      with patch('transformers.onnx.features.is_tf_available'       ,						__lowercase					), patch(
          'transformers.onnx.features.is_torch_available'       ,						__lowercase					):
        lowerCamelCase_         =						FeaturesManager.determine_framework(self.test_model					)
        self.assertEqual(__lowercase       ,						self.framework_pt					)

      # Both not in environment -> raise error
      lowerCamelCase_         =						MagicMock(return_value=__lowercase					)
      lowerCamelCase_         =						MagicMock(return_value=__lowercase					)
      with patch('transformers.onnx.features.is_tf_available'       ,						__lowercase					), patch(
          'transformers.onnx.features.is_torch_available'       ,						__lowercase					):
        with self.assertRaises(__lowercase					):
          lowerCamelCase_         =						FeaturesManager.determine_framework(self.test_model					)









import random

from .binary_exp_mod import bin_exp_mod



def 			_lowerCAmelCase       (					__lowerCAmelCase  ,  __lowerCAmelCase=1000      )   ->					str:


				"""simple docstring"""

				if n < 2:
								return False

				if n % 2 == 0:
								return n == 2

				# this means n is odd
				snake_case__	:      Tuple     		=	n - 1
				snake_case__	:      Tuple     		=	0
				while d % 2 == 0:
								d /= 2
								exp += 1

				# n - 1=d*(2**exp)
				snake_case__	:      List[str]     		=	0
				while count < prec:
								snake_case__	:      List[str]     		=	random.randint(2  ,  n - 1      )
								snake_case__	:      Optional[Any]     		=	bin_exp_mod(__lowerCAmelCase  ,  __lowerCAmelCase  ,  __lowerCAmelCase      )
								if b != 1:
												snake_case__	:      List[Any]     		=	True
												for _ in range(__lowerCAmelCase      ):
																if b == n - 1:
																				snake_case__	:      List[str]     		=	False
																				break
																snake_case__	:      str     		=	b * b
																b %= n
												if flag:
																return False
												count += 1
				return True


if __name__ == "__main__":
				A__								=						abs(int(input('''Enter bound : ''').strip()))
				print('''Here\'s the list of primes:''')
				print(''', '''.join(str(i) for i in range(n + 1) if is_prime_big(i)))

