code: 
  '''simple docstring'''
  
  _UpperCAmelCase   :      Dict 						=  {
      """+""": lambda x, y: x + y,
      """-""": lambda x, y: x - y,
      """*""": lambda x, y: x * y,
      """/""": lambda x, y: x / y,
  }
  
  
  
  
  
  
  
  def 						snake_case__	(      UpperCamelCase	) ->      Optional[int]:
  		return c.isdigit()
  
  
  
  
  
  
  
  def 						snake_case__	(      UpperCamelCase	) ->      Union[str, Any]:
  		_UpperCamelCase       : List[Any]    =      []
  
  		# iterate over the string in reverse order
  		for c in expression.split()[::-1]:
  				# push operand to stack
  				if is_operand(UpperCamelCase	):
  						stack.append(int(UpperCamelCase	)	)
  
  				else:
  						# pop values from stack can calculate the result
  						# push the result onto the stack again
  						_UpperCamelCase       : List[str]    =      stack.pop()
  						_UpperCamelCase       : Optional[int]    =      stack.pop()
  						stack.append(calc[c](UpperCamelCase			,UpperCamelCase	)	)
  
  		return stack.pop()
  
  
  # Driver code
  if __name__ == "__main__":
  	_UpperCAmelCase   :      Optional[int] 						=  """+ 9 * 2 6"""
  	print(evaluate(test_expression))
  
  	_UpperCAmelCase   :      Any 						=  """/ * 10 2 + 4 1 """
  	print(evaluate(test_expression))
  
  
  
  
style_context: 
  '''simple docstring'''
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_tf_available,
      is_torch_available,
  )
  
  
  _UpperCAmelCase   :      int 						=  {
      """configuration_gptsan_japanese""": ["""GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTSanJapaneseConfig"""],
      """tokenization_gptsan_japanese""": ["""GPTSanJapaneseTokenizer"""],
  }
  
  try:
  	if not is_torch_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	_UpperCAmelCase   :      int 						=  [
  	    """GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST""",
  	    """GPTSanJapaneseForConditionalGeneration""",
  	    """GPTSanJapaneseModel""",
  	    """GPTSanJapanesePreTrainedModel""",
  	]
  	_UpperCAmelCase   :      str 						=  [
  	    """GPTSanJapaneseTokenizer""",
  	]
  
  
  if TYPE_CHECKING:
  	from .configuration_gptsan_japanese import GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTSanJapaneseConfig
  	from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer
  
  	try:
  		if not is_torch_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_gptsan_japanese import (
  		    GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
  		    GPTSanJapaneseForConditionalGeneration,
  		    GPTSanJapaneseModel,
  		    GPTSanJapanesePreTrainedModel,
  		)
  		from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer
  
  
  else:
  	import sys
  
  	_UpperCAmelCase   :      List[str] 						=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
  
  
  
  