






"""simple docstring"""


from typing import TYPE_CHECKING

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


lowercase_								=	{
    'configuration_ernie_m': ['ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieMConfig'],
}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_								=	['ErnieMTokenizer']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_								=	[
           'ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST',
           'ErnieMForMultipleChoice',
           'ErnieMForQuestionAnswering',
           'ErnieMForSequenceClassification',
           'ErnieMForTokenClassification',
           'ErnieMModel',
           'ErnieMPreTrainedModel',
           'ErnieMForInformationExtraction',
       ]


if TYPE_CHECKING:
       from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

       try:
              if not is_sentencepiece_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_ernie_m import ErnieMTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_ernie_m import (
                  ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ErnieMForInformationExtraction,
                  ErnieMForMultipleChoice,
                  ErnieMForQuestionAnswering,
                  ErnieMForSequenceClassification,
                  ErnieMForTokenClassification,
                  ErnieMModel,
                  ErnieMPreTrainedModel,
              )


else:
       import sys

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





"""simple docstring"""


def 						UpperCamelCase				(	_lowerCAmelCase   :							Dict				, _lowerCAmelCase   :							Tuple						):
    __a			      =						len(_lowerCAmelCase						)
    # Create a stack and push index of fist element to it
    __a			      =						[]
    st.append(0						)

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

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

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

def 						UpperCamelCase				(	_lowerCAmelCase   :							Dict				, _lowerCAmelCase   :							Optional[Any]						):
    for i in range(0				, _lowerCAmelCase						):
        print(arr[i]				, end=""" """						)


# Driver program to test above function
__A       			=      [10, 4, 5, 90, 1_20, 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))
