



from typing import TYPE_CHECKING

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


A_		:  List[str]										=  {
    '''configuration_sam''': [
        '''SAM_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SamConfig''',
        '''SamMaskDecoderConfig''',
        '''SamPromptEncoderConfig''',
        '''SamVisionConfig''',
    ],
    '''processing_sam''': ['''SamProcessor'''],
}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  int										=  [
         '''SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''SamModel''',
         '''SamPreTrainedModel''',
     ]
try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  Dict										=  [
         '''TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TFSamModel''',
         '''TFSamPreTrainedModel''',
     ]
try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  Optional[Any]										=  ['''SamImageProcessor''']


if TYPE_CHECKING:
     from .configuration_sam import (
         SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
         SamConfig,
         SamMaskDecoderConfig,
         SamPromptEncoderConfig,
         SamVisionConfig,
     )
     from .processing_sam import SamProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .image_processing_sam import SamImageProcessor

else:
     import sys

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









"""simple docstring"""





from itertools import combinations, product



def      __lowercase       (     a			:					int							,		a			:					int							,		a			:					int							,		a			:					int			)       ->       bool:
      if xa == ya == 0 or xa == ya == 0:
            return False
      __snake_case   :     Any	      =xa * xa + ya * ya
      __snake_case   :     Tuple	      =xa * xa + ya * ya
      __snake_case   :     List[Any]	      =(xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
      return (
          a_square + b_square == c_square
          or a_square + c_square == b_square
          or b_square + c_square == a_square
      )



def      __lowercase       (     a			:					int = 50			)       ->       int:
      return sum(
          1
          for pta, pta in combinations(product(range(limit + 1			)							,		repeat=2			)							,		2			)
          if is_right(*a							,		*a			)			)


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


