

def  lowerCamelCase__ (					_a = 1000000):
 SCREAMING_SNAKE_CASE   :      Tuple				     =       set(range(3							,			snake_case__							,			2))
 primes.add(2)
 for p in range(3							,			snake_case__							,			2):
  if p not in primes:
   continue
  primes.difference_update(set(range(p * p							,			snake_case__							,			snake_case__)))

 SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       [float(snake_case__) for n in range(limit + 1)]

 for p in primes:
  for n in range(snake_case__							,			limit + 1							,			snake_case__):
   phi[n] *= 1 - 1 / p

 return int(sum(phi[2:]))


if __name__ == "__main__":
   print(F'''{solution() = }''')


from typing import TYPE_CHECKING

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


a_						     =    {
    'configuration_bridgetower': [
        'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BridgeTowerConfig',
        'BridgeTowerTextConfig',
        'BridgeTowerVisionConfig',
    ],
    'processing_bridgetower': ['BridgeTowerProcessor'],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_						     =    ['BridgeTowerImageProcessor']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_						     =    [
			    'BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'BridgeTowerForContrastiveLearning',
			    'BridgeTowerForImageAndTextRetrieval',
			    'BridgeTowerForMaskedLM',
			    'BridgeTowerModel',
			    'BridgeTowerPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_bridgetower import (
			    BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    BridgeTowerConfig,
			    BridgeTowerTextConfig,
			    BridgeTowerVisionConfig,
			)
			from .processing_bridgetower import BridgeTowerProcessor

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .image_processing_bridgetower import BridgeTowerImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_bridgetower import (
						    BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
						    BridgeTowerForContrastiveLearning,
						    BridgeTowerForImageAndTextRetrieval,
						    BridgeTowerForMaskedLM,
						    BridgeTowerModel,
						    BridgeTowerPreTrainedModel,
						)


else:
			import sys

			a_						     =    _LazyModule(__name__, globals()['__file__'], _import_structure)