


"""simple docstring"""


def    _lowerCamelCase   (     lowerCamelCase__	:							list  ):

 if not grid or not grid[0]:
  raise TypeError("""The grid does not contain the appropriate information"""  )

 for cell_n in range(1       ,		len(grid[0]  )  ):
  grid[0][cell_n] += grid[0][cell_n - 1]
 lowercase__       :       int				=						grid[0]

 for row_n in range(1       ,		len(lowerCamelCase__  )  ):
  lowercase__       :       Optional[int]				=						grid[row_n]
  lowercase__       :       List[Any]				=						fill_row(lowerCamelCase__       ,		lowerCamelCase__  )
  lowercase__       :       Tuple				=						grid[row_n]

 return grid[-1][-1]


def    _lowerCamelCase   (     lowerCamelCase__	:							list       ,		lowerCamelCase__	:							list  ):
 current_row[0] += row_above[0]
 for cell_n in range(1       ,		len(lowerCamelCase__  )  ):
  current_row[cell_n] += min(current_row[cell_n - 1]       ,		row_above[cell_n]  )

 return current_row


if __name__ == "__main__":
   import doctest

   doctest.testmod()



"""simple docstring"""


from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case    					=					{
    'configuration_informer': [
        'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'InformerConfig',
    ],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case    					=					[
       'INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
       'InformerForPrediction',
       'InformerModel',
       'InformerPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_informer import INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, InformerConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_informer import (
          INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          InformerForPrediction,
          InformerModel,
          InformerPreTrainedModel,
      )

else:
   import sys

   __snake_case    					=					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)