"""simple docstring"""







import math



def       A__    (	lowercase_     :	List[str]						)  ->							int:
   __lowerCamelCase    		=					0
   if n % 2 == 0:
      count += 1
      while n % 2 == 0:
         __lowerCamelCase    		=					int(n / 2						)
    # the n input value must be odd so that
    # we can skip one element (ie i += 2)

   __lowerCamelCase    		=					3

   while i <= int(math.sqrt(A__						)						):
      if n % i == 0:
         count += 1
         while n % i == 0:
            __lowerCamelCase    		=					int(n / i						)
      __lowerCamelCase    		=					i + 2

   # this condition checks the prime
   # number n is greater than 2

   if n > 2:
      count += 1
   return count


if __name__ == "__main__":
     _SCREAMING_SNAKE_CASE	:		Dict   =   5_1_2_4_2_1_8_3
     print(F"The number of distinct prime factors is/are {exact_prime_factor_count(n)}")
     print(F"The value of log(log(n)) is {math.log(math.log(n)):.4f}")







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCAmelCase__	:  int						=  {
    '''configuration_deta''': ['''DETA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DetaConfig'''],
}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__	:  Union[str, Any]						=  ['''DetaImageProcessor''']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__	:  Optional[int]						=  [
				    '''DETA_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''DetaForObjectDetection''',
				    '''DetaModel''',
				    '''DetaPreTrainedModel''',
				]


if TYPE_CHECKING:
				from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .image_processing_deta import DetaImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_deta import (
								    DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DetaForObjectDetection,
								    DetaModel,
								    DetaPreTrainedModel,
								)

else:
				import sys

				lowerCAmelCase__	:  int						=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


