






from __future__ import annotations

from typing import Any


def 				snake_case__							(							UpperCAmelCase							:  list       ):
    if not postfix_notation:
        return 0

    lowerCAmelCase__   :List[str]      							=				{"+", "-", "*", "/"}
    lowerCAmelCase__   :list[Any]      							=				[]

    for token in postfix_notation:
        if token in operations:
            lowerCAmelCase__							,lowerCAmelCase__   :Optional[Any]      							=				stack.pop(), stack.pop()
            if token == "+":
                stack.append(a + b       )
            elif token == "-":
                stack.append(a - b       )
            elif token == "*":
                stack.append(a * b       )
            else:
                if a * b < 0 and a % b != 0:
                    stack.append(a // b + 1       )
                else:
                    stack.append(a // b       )
        else:
            stack.append(int(UpperCAmelCase       )       )

    return stack.pop()


if __name__ == "__main__":
 import doctest

 doctest.testmod()











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_a    :   str        =			{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _a    :   Optional[Any]        =			[
     """WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """WavLMForAudioFrameClassification""",
     """WavLMForCTC""",
     """WavLMForSequenceClassification""",
     """WavLMForXVector""",
     """WavLMModel""",
     """WavLMPreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_wavlm import (
      WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
      WavLMForAudioFrameClassification,
      WavLMForCTC,
      WavLMForSequenceClassification,
      WavLMForXVector,
      WavLMModel,
      WavLMPreTrainedModel,
  )

else:
 import sys

 _a    :   str        =			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



