
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


lowercase__		:str   =    {
    "configuration_vision_text_dual_encoder": ["VisionTextDualEncoderConfig"],
    "processing_vision_text_dual_encoder": ["VisionTextDualEncoderProcessor"],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:List[str]   =    ["VisionTextDualEncoderModel"]


try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Optional[int]   =    ["FlaxVisionTextDualEncoderModel"]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Dict   =    ["TFVisionTextDualEncoderModel"]


if TYPE_CHECKING:
							from .configuration_vision_text_dual_encoder import VisionTextDualEncoderConfig
							from .processing_vision_text_dual_encoder import VisionTextDualEncoderProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_vision_text_dual_encoder import VisionTextDualEncoderModel

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_vision_text_dual_encoder import FlaxVisionTextDualEncoderModel

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_vision_text_dual_encoder import TFVisionTextDualEncoderModel


else:
							import sys

							lowercase__		:Dict   =    _LazyModule(__name__, globals()["__file__"], _import_structure)






import random

from .binary_exp_mod import bin_exp_mod



def        UpperCamelCase    (							lowerCAmelCase__ ,			lowerCAmelCase__=1000		):
					'''simple docstring'''
					if n < 2:
										return False

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

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

					# n - 1=d*(2**exp)
					lowercase							=						0
					while count < prec:
										lowercase							=						random.randint(2 ,			n - 1		)
										lowercase							=						bin_exp_mod(lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		)
										if b != 1:
															lowercase							=						True
															for _ in range(lowerCAmelCase__		):
																				if b == n - 1:
																									lowercase							=						False
																									break
																				lowercase							=						b * b
																				b %= n
															if flag:
																				return False
															count += 1
					return True


if __name__ == "__main__":
							lowercase__		:Tuple   =    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)))




