




'''simple docstring'''

import math




def    snake_case__     (  a	)			->       Dict:





			'''simple docstring'''






			snake_case__          =						0
			if n % 2 == 0:
						count += 1
						while n % 2 == 0:
									snake_case__          =						int(n / 2	)
    # the n input value must be odd so that
    # we can skip one element (ie i += 2)

			snake_case__          =						3

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

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

			if n > 2:
						count += 1
			return count


if __name__ == "__main__":
		a__         =     51_242_183
		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}")
"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase      : Dict       ={'''configuration_sew_d''': ['''SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWDConfig''']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase      : List[str]       =[
           '''SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''SEWDForCTC''',
           '''SEWDForSequenceClassification''',
           '''SEWDModel''',
           '''SEWDPreTrainedModel''',
       ]

if TYPE_CHECKING:
       from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_sew_d import (
                  SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
                  SEWDForCTC,
                  SEWDForSequenceClassification,
                  SEWDModel,
                  SEWDPreTrainedModel,
              )


else:
       import sys

       lowerCamelCase      : str       =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



