





def 	lowerCAmelCase_					(			__a      ,       __a      ,       __a      ,       __a						)	->						int:







  """simple docstring"""





  lowerCamelCase__    ,   lowerCamelCase__: Optional[int]         =len(__a						), len(grid[0]						)
  if (
      min(__a      ,       __a						) < 0
      or row == row_length
      or col == col_length
      or (row, col) in visit
      or grid[row][col] == 1
  ):
    return 0
  if row == row_length - 1 and col == col_length - 1:
    return 1

  visit.add((row, col)						)

  lowerCamelCase__: str         =0
  count += depth_first_search(__a      ,       row + 1      ,       __a      ,       __a						)
  count += depth_first_search(__a      ,       row - 1      ,       __a      ,       __a						)
  count += depth_first_search(__a      ,       __a      ,       col + 1      ,       __a						)
  count += depth_first_search(__a      ,       __a      ,       col - 1      ,       __a						)

  visit.remove((row, col)						)
  return count


if __name__ == "__main__":
     import doctest

     doctest.testmod()






'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__          =  {
    "configuration_clap": [
        "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ClapAudioConfig",
        "ClapConfig",
        "ClapTextConfig",
    ],
    "processing_clap": ["ClapProcessor"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE__          =  [
     "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
     "ClapModel",
     "ClapPreTrainedModel",
     "ClapTextModel",
     "ClapTextModelWithProjection",
     "ClapAudioModel",
     "ClapAudioModelWithProjection",
 ]
 SCREAMING_SNAKE_CASE__          =  ["ClapFeatureExtractor"]

if TYPE_CHECKING:
 from .configuration_clap import (
     CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
     ClapAudioConfig,
     ClapConfig,
     ClapTextConfig,
 )
 from .processing_clap import ClapProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_clap import ClapFeatureExtractor
  from .modeling_clap import (
      CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
      ClapAudioModel,
      ClapAudioModelWithProjection,
      ClapModel,
      ClapPreTrainedModel,
      ClapTextModel,
      ClapTextModelWithProjection,
  )


else:
 import sys

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




