





from typing import TYPE_CHECKING

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


__lowerCamelCase       :     Optional[Any]   =     {"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase       :     List[str]   =     ["""GLPNFeatureExtractor"""]
    __lowerCamelCase       :     int   =     ["""GLPNImageProcessor"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase       :     Optional[Any]   =     [
        """GLPN_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """GLPNForDepthEstimation""",
        """GLPNLayer""",
        """GLPNModel""",
        """GLPNPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_glpn import GLPNFeatureExtractor
        from .image_processing_glpn import GLPNImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_glpn import (
            GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
            GLPNForDepthEstimation,
            GLPNLayer,
            GLPNModel,
            GLPNPreTrainedModel,
        )


else:
    import sys

    __lowerCamelCase       :     List[Any]   =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

def    a__       (						__UpperCamelCase = 1_0_0_0 ):
      SCREAMING_SNAKE_CASE_      =     -1
      SCREAMING_SNAKE_CASE_      =     0
      for a in range(1   ,					n // 3 ):
            # Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
            SCREAMING_SNAKE_CASE_      =     (n * n - 2 * a * n) // (2 * n - 2 * a)
            SCREAMING_SNAKE_CASE_      =     n - a - b
            if c * c == (a * a + b * b):
                  SCREAMING_SNAKE_CASE_      =     a * b * c
                  if candidate >= product:
                        SCREAMING_SNAKE_CASE_      =     candidate
      return product


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


