






from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__				     =			{
    '''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:
							SCREAMING_SNAKE_CASE__				     =			['''BridgeTowerImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__				     =			[
							    '''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

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






'''simple docstring'''


import math
import sys

def   A_      (       SCREAMING_SNAKE_CASE_						)			->int:
  if number != int(SCREAMING_SNAKE_CASE_						):
    raise ValueError("""the value of input must be a natural number"""						)
  if number < 0:
    raise ValueError("""the value of input must not be a negative number"""						)
  if number == 0:
    return 1
  lowercase_     =       [-1] * (number + 1)
  lowercase_     =       0
  for i in range(1 ,	number + 1						):
    lowercase_     =       sys.maxsize
    lowercase_     =       int(math.sqrt(SCREAMING_SNAKE_CASE_						)						)
    for j in range(1 ,	root + 1						):
      lowercase_     =       1 + answers[i - (j**2)]
      lowercase_     =       min(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)
    lowercase_     =       answer
  return answers[number]


if __name__ == "__main__":
       import doctest

       doctest.testmod()

