
def 					lowerCamelCase__					(    a__	:	Optional[int]						,   a__	:	List[str]  )		->						Dict:
       UpperCamelCase_											=							len(a__  )
       # Create a stack and push index of fist element to it
       UpperCamelCase_											=							[]
       st.append(0  )

       # Span value of first element is always 1
       UpperCamelCase_											=							1

       # Calculate span values for rest of the elements
       for i in range(1						,   a__  ):
              # Pop elements from stack while stack is not
              # empty and top of stack is smaller than price[i]
              while len(a__  ) > 0 and price[st[0]] <= price[i]:
                     st.pop()

              # If stack becomes empty, then price[i] is greater
              # than all elements on left of it, i.e. price[0],
              # price[1], ..price[i-1]. Else the price[i]  is
              # greater than elements after top of stack
              UpperCamelCase_											=							i + 1 if len(a__  ) <= 0 else (i - st[0])

              # Push this element to stack
              st.append(a__  )




def 					lowerCamelCase__					(    a__	:	Union[str, Any]						,   a__	:	Union[str, Any]  )		->						Optional[Any]:
       for i in range(0						,   a__  ):
              print(arr[i]						,   end=""" """  )


# Driver program to test above function
_A							=       [10, 4, 5, 90, 120, 80]
_A							=       [0 for i in range(len(price) + 1)]

# Fill the span values in array S[]
calculation_span(price, S)







print_array(S, len(price))





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A							=       {'''configuration_dinat''': ['''DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DinatConfig''']}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _A							=       [
          '''DINAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''DinatForImageClassification''',
          '''DinatModel''',
          '''DinatPreTrainedModel''',
          '''DinatBackbone''',
      ]

if TYPE_CHECKING:
      from .configuration_dinat import DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP, DinatConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_dinat import (
                DINAT_PRETRAINED_MODEL_ARCHIVE_LIST,
                DinatBackbone,
                DinatForImageClassification,
                DinatModel,
                DinatPreTrainedModel,
            )

else:
      import sys

      _A							=       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



