


'''simple docstring'''



import sys




def 			_a			(		_lowercase      :			Optional[int]						):





     '''simple docstring'''






     __UpperCAmelCase			:				int													=    len(_lowercase						)
     __UpperCAmelCase			:				List[Any]													=    [[0 for x in range(_lowercase						)] for x in range(_lowercase						)]
     __UpperCAmelCase			:				str													=    [[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			:				Union[str, Any]													=    a + chain_length - 1

               __UpperCAmelCase			:				int													=    sys.maxsize
               for c in range(_lowercase    ,      _lowercase						):
                    __UpperCAmelCase			:				str													=    (
                        matrix[a][c] + matrix[c + 1][b] + array[a - 1] * array[c] * array[b]
                    )
                    if cost < matrix[a][b]:
                         __UpperCAmelCase			:				Dict													=    cost
                         __UpperCAmelCase			:				Any													=    c
     return matrix, sol




def 			_a			(		_lowercase      :			Dict    ,      _lowercase      :			List[Any]    ,      _lowercase      :			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 			_a			(		):





     '''simple docstring'''






     __UpperCAmelCase			:				str													=    [30, 35, 15, 5, 10, 20, 25]
     __UpperCAmelCase			:				List[Any]													=    len(_lowercase						)
     # Size of matrix created from above array will be
     # 30*35 35*15 15*5 5*10 10*20 20*25
     __UpperCAmelCase			:				Union[str, Any]													=    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()



'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


__UpperCAmelCase    :Optional[Any]				       =     {
    "configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
    "processing_layoutlmv2": ["LayoutLMv2Processor"],
    "tokenization_layoutlmv2": ["LayoutLMv2Tokenizer"],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase    :Any				       =     ["LayoutLMv2TokenizerFast"]

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase    :int				       =     ["LayoutLMv2FeatureExtractor"]
      __UpperCAmelCase    :Optional[int]				       =     ["LayoutLMv2ImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase    :List[Any]				       =     [
          "LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST",
          "LayoutLMv2ForQuestionAnswering",
          "LayoutLMv2ForSequenceClassification",
          "LayoutLMv2ForTokenClassification",
          "LayoutLMv2Layer",
          "LayoutLMv2Model",
          "LayoutLMv2PreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
      from .processing_layoutlmva import LayoutLMvaProcessor
      from .tokenization_layoutlmva import LayoutLMvaTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_layoutlmva import (
                LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
                LayoutLMvaForQuestionAnswering,
                LayoutLMvaForSequenceClassification,
                LayoutLMvaForTokenClassification,
                LayoutLMvaLayer,
                LayoutLMvaModel,
                LayoutLMvaPreTrainedModel,
            )
else:
      import sys

      __UpperCAmelCase    :Any				       =     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)