





from typing import TYPE_CHECKING

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


__lowerCamelCase			:	List[Any]					    =	{
    """configuration_chinese_clip""": [
        """CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ChineseCLIPConfig""",
        """ChineseCLIPOnnxConfig""",
        """ChineseCLIPTextConfig""",
        """ChineseCLIPVisionConfig""",
    ],
    """processing_chinese_clip""": ["""ChineseCLIPProcessor"""],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase			:	Tuple					    =	["""ChineseCLIPFeatureExtractor"""]
    __lowerCamelCase			:	List[str]					    =	["""ChineseCLIPImageProcessor"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase			:	str					    =	[
        """CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """ChineseCLIPModel""",
        """ChineseCLIPPreTrainedModel""",
        """ChineseCLIPTextModel""",
        """ChineseCLIPVisionModel""",
    ]

if TYPE_CHECKING:
    from .configuration_chinese_clip import (
        CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ChineseCLIPConfig,
        ChineseCLIPOnnxConfig,
        ChineseCLIPTextConfig,
        ChineseCLIPVisionConfig,
    )
    from .processing_chinese_clip import ChineseCLIPProcessor

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_chinese_clip import (
            CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
            ChineseCLIPModel,
            ChineseCLIPPreTrainedModel,
            ChineseCLIPTextModel,
            ChineseCLIPVisionModel,
        )

else:
    import sys

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







import os



def 						A_							(	)		->					Union[str, Any]:
 with open(os.path.dirname(_lowerCAmelCase	) + "/grid.txt"	) as f:
  UpperCamelCase      :   Optional[Any]			      =  []  # noqa: E741
  for _ in range(20	):
   l.append([int(_lowerCAmelCase	) for x in f.readline().split()]	)

  UpperCamelCase      :   str			      =  0

  # right
  for i in range(20	):
   for j in range(17	):
    UpperCamelCase      :   int			      =  l[i][j] * l[i][j + 1] * l[i][j + 2] * l[i][j + 3]
    if temp > maximum:
     UpperCamelCase      :   List[Any]			      =  temp

        # down
  for i in range(17	):
   for j in range(20	):
    UpperCamelCase      :   List[str]			      =  l[i][j] * l[i + 1][j] * l[i + 2][j] * l[i + 3][j]
    if temp > maximum:
     UpperCamelCase      :   List[str]			      =  temp

        # diagonal 1
  for i in range(17	):
   for j in range(17	):
    UpperCamelCase      :   Any			      =  l[i][j] * l[i + 1][j + 1] * l[i + 2][j + 2] * l[i + 3][j + 3]
    if temp > maximum:
     UpperCamelCase      :   Tuple			      =  temp

        # diagonal 2
  for i in range(17	):
   for j in range(3				,  20	):
    UpperCamelCase      :   Tuple			      =  l[i][j] * l[i + 1][j - 1] * l[i + 2][j - 2] * l[i + 3][j - 3]
    if temp > maximum:
     UpperCamelCase      :   List[Any]			      =  temp
  return maximum


if __name__ == "__main__":
    print(solution())
