




import sys







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	List[Any]:



       """simple docstring"""

       A__							=   len(lowercase_						)
       A__							=   [[0 for x in range(lowercase_						)] for x in range(lowercase_						)]
       A__							=   [[0 for x in range(lowercase_						)] for x in range(lowercase_						)]

       for chain_length in range(2			,    lowercase_						):
              for a in range(1			,    n - chain_length + 1						):
                     A__							=   a + chain_length - 1

                     A__							=   sys.maxsize
                     for c in range(lowercase_			,    lowercase_						):
                            A__							=   (
                                matrix[a][c] + matrix[c + 1][b] + array[a - 1] * array[c] * array[b]
                            )
                            if cost < matrix[a][b]:
                                   A__							=   cost
                                   A__							=   c
       return matrix, sol







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_			,    lowercase_						)       ->	Optional[Any]:



       """simple docstring"""

       if i == j:
              print('''A''' + str(lowercase_						)			,    end=''' '''						)
       else:
              print('''('''			,    end=''' '''						)
              print_optiomal_solution(lowercase_			,    lowercase_			,    optimal_solution[i][j]						)
              print_optiomal_solution(lowercase_			,    optimal_solution[i][j] + 1			,    lowercase_						)
              print(''')'''			,    end=''' '''						)







def SCREAMING_SNAKE_CASE    (	)       ->	List[Any]:



       """simple docstring"""

       A__							=   [30, 35, 15, 5, 10, 20, 25]
       A__							=   len(lowercase_						)
       # Size of matrix created from above array will be
       # 30*35 35*15 15*5 5*10 10*20 20*25
       A__			,							A__							=   matrix_chain_order(lowercase_						)

       print('''No. of Operation required: ''' + str(matrix[1][n - 1]						)						)
       print_optiomal_solution(lowercase_			,    1			,    n - 1						)


if __name__ == "__main__":
  main()








from typing import TYPE_CHECKING

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


_lowerCamelCase     :		str								=       {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase     :		Dict								=       [
      """FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """FocalNetForImageClassification""",
      """FocalNetForMaskedImageModeling""",
      """FocalNetBackbone""",
      """FocalNetModel""",
      """FocalNetPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_focalnet import (
        FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        FocalNetBackbone,
        FocalNetForImageClassification,
        FocalNetForMaskedImageModeling,
        FocalNetModel,
        FocalNetPreTrainedModel,
    )

else:
  import sys

  _lowerCamelCase     :		Tuple								=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


