



"""simple docstring"""


import sys

def  _lowerCAmelCase      (   lowercase_						):
						UpperCAmelCase             = len(lowercase_						)
						UpperCAmelCase             = [[0 for x in range(lowercase_						)] for x in range(lowercase_						)]
						UpperCAmelCase             = [[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						):
																		UpperCAmelCase             = a + chain_length - 1

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

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

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A									=				{"configuration_ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig", "IBertOnnxConfig"]}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __A									=				[
         "IBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "IBertForMaskedLM",
         "IBertForMultipleChoice",
         "IBertForQuestionAnswering",
         "IBertForSequenceClassification",
         "IBertForTokenClassification",
         "IBertModel",
         "IBertPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_ibert import (
              IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              IBertForMaskedLM,
              IBertForMultipleChoice,
              IBertForQuestionAnswering,
              IBertForSequenceClassification,
              IBertForTokenClassification,
              IBertModel,
              IBertPreTrainedModel,
          )

else:
     import sys

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

