parameters: (self, gradients)
return_statement: return gradients
docstring: Restore gradients for mixed precision.
  
          User-defined optimizers based on :class:`mindspore.nn.Optimizer` can also call this interface to restore
          gradients.
  
          Args:
              gradients (tuple[Tensor]): The gradients of network parameters, and have the same shape as the parameters.
  
          Returns:
              tuple[Tensor], The gradients after loss scale.
docstring_summary: Restore gradients for mixed precision.
docstring_tokens: Restore gradients for mixed precision .
function: def scale_grad(self, gradients):
          """
          Restore gradients for mixed precision.
  
          User-defined optimizers based on :class:`mindspore.nn.Optimizer` can also call this interface to restore
          gradients.
  
          Args:
              gradients (tuple[Tensor]): The gradients of network parameters, and have the same shape as the parameters.
  
          Returns:
              tuple[Tensor], The gradients after loss scale.
  
          """
          if self.need_scale:
              gradients = self.map_(F.partial(_grad_scale, self.reciprocal_scale), gradients)
  
          return gradients
function_tokens: def scale_grad ( self , gradients ) : if self . need_scale : gradients = self . map_ ( F . partial ( _grad_scale , self . reciprocal_scale ) , gradients ) return gradients