code: 
  
  
  '''simple docstring'''
  
  from .balanced_parentheses import balanced_parentheses
  from .stack import Stack
  
  def _SCREAMING_SNAKE_CASE   (A ) -> int:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(A						,				-1 )
  
  def _SCREAMING_SNAKE_CASE   (A ) -> str:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         if not balanced_parentheses(A ):
                raise ValueError('''Mismatched parentheses''' )
         lowercase__       =				Stack()
         lowercase__       =				[]
         for char in expression_str:
                if char.isalpha() or char.isdigit():
                       postfix.append(A )
                elif char == "(":
                       stack.push(A )
                elif char == ")":
                       while not stack.is_empty() and stack.peek() != "(":
                              postfix.append(stack.pop() )
                       stack.pop()
                else:
                       while not stack.is_empty() and precedence(A ) <= precedence(stack.peek() ):
                              postfix.append(stack.pop() )
                       stack.push(A )
         while not stack.is_empty():
                postfix.append(stack.pop() )
         return " ".join(A )
  
  
  if __name__ == "__main__":
   from doctest import testmod
  
   testmod()
   lowerCamelCase							:     Any								=			'a+b*(c^d-e)^(f+g*h)-i'
  
   print('Infix to Postfix Notation demonstration:\n')
   print('Infix notation: ' + expression)
   print('Postfix notation: ' + infix_to_postfix(expression))
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  import torch
  
  from accelerate import Accelerator, DistributedType
  class 						__lowerCAmelCase		:
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def __enter__(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if self.enabled:
                      lowercase__       =				self.model.no_sync()
                      self.model_sync_obj.__enter__()
  
               return self
  
  
  
        def __exit__(self					:					List[str]     ,		UpperCamelCase					:					List[Any]     ,		UpperCamelCase					:					Optional[int]     ,		UpperCamelCase					:					Optional[int]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if self.enabled:
                      # Average all models on exit
                      self._sync_and_avg_model_params()
                      self.model_sync_obj.__exit__(UpperCamelCase     ,		UpperCamelCase     ,		UpperCamelCase				)
  
  
  
        def __init__(self					:					Dict     ,		UpperCamelCase					:					Accelerator     ,		UpperCamelCase					:					torch.nn.Module     ,		UpperCamelCase					:					int     ,		UpperCamelCase					:					bool = True				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if accelerator.distributed_type not in [
                   DistributedType.NO,
                   DistributedType.MULTI_CPU,
                   DistributedType.MULTI_GPU,
               ]:
                      raise NotImplementedError('''LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)'''				)
               lowercase__       =				enabled and accelerator.distributed_type != DistributedType.NO
               lowercase__       =				0
               if self.enabled:
                      lowercase__       =				accelerator
                      lowercase__       =				model
                      lowercase__       =				local_sgd_steps
  
  
  
        def    UpperCamelCase__	(self					:					List[str]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               self.num_steps += 1
               if not self.enabled:
                      return
  
               if self.num_steps % self.local_sgd_steps == 0:
                      self._sync_and_avg_model_params()
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Any				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               self.accelerator.wait_for_everyone()
               with self.accelerator.autocast():
                      for param in self.model.parameters():
                             lowercase__       =				self.accelerator.reduce(param.data     ,		reduction='''mean'''				)
  
  
  
  
  