"""simple docstring"""






class     UpperCAmelCase						:  # Public class to implement a graph



    """simple docstring"""

    def __init__(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase    ,			_UpperCAmelCase							):
       lowercase__:   Optional[Any]					=      row
       lowercase__:   Optional[int]					=      col
       lowercase__:   Tuple					=      graph






    def _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase    ,			_UpperCAmelCase							):
       return (
           0 <= i < self.ROW
           and 0 <= j < self.COL
           and not visited[i][j]
           and self.graph[i][j]
       )






    def _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase    ,			_UpperCAmelCase							):
       # Checking all 8 elements surrounding nth element
       lowercase__:   Union[str, Any]					=      [-1, -1, -1, 0, 0, 1, 1, 1]  # Coordinate order
       lowercase__:   List[Any]					=      [-1, 0, 1, -1, 1, -1, 0, 1]
       lowercase__:   Dict					=      True  # Make those cells visited
       for k in range(8							):
          if self.is_safe(i + row_nbr[k]    ,			j + col_nbr[k]    ,			_UpperCAmelCase							):
             self.diffs(i + row_nbr[k]    ,			j + col_nbr[k]    ,			_UpperCAmelCase							)






    def _snake_case			(   self							):  # And finally, count all islands.
       lowercase__:   int					=      [[False for j in range(self.COL							)] for i in range(self.ROW							)]
       lowercase__:   str					=      0
       for i in range(self.ROW							):
          for j in range(self.COL							):
             if visited[i][j] is False and self.graph[i][j] == 1:
                self.diffs(_UpperCAmelCase    ,			_UpperCAmelCase    ,			_UpperCAmelCase							)
                count += 1
       return count

"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A			   = {
    "configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __A			   = [
           "LILT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "LiltForQuestionAnswering",
           "LiltForSequenceClassification",
           "LiltForTokenClassification",
           "LiltModel",
           "LiltPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_lilt import (
                  LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  LiltForQuestionAnswering,
                  LiltForSequenceClassification,
                  LiltForTokenClassification,
                  LiltModel,
                  LiltPreTrainedModel,
              )

else:
       import sys

       __A			   = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
