How to we update the learning on every step?
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I want to update the learning on training steps. However, I found that

  
    
      pytorch-lightning/pytorch_lightning/trainer/optimizers.py
    
    
        Lines 97 to 108
      in
      f477c2f
    
  
  
    

        
          
           def configure_schedulers(self, schedulers: list, monitor: Optional[str] = None): 
        

        
          
               # Convert each scheduler into dict structure with relevant information 
        

        
          
               lr_schedulers = [] 
        

        
          
               default_config = { 
        

        
          
                   'scheduler': None, 
        

        
          
                   'name': None,  # no custom name 
        

        
          
                   'interval': 'epoch',  # after epoch is over 
        

        
          
                   'frequency': 1,  # every epoch/batch 
        

        
          
                   'reduce_on_plateau': False,  # most often not ReduceLROnPlateau scheduler 
        

        
          
                   'monitor': monitor,  # value to monitor for ReduceLROnPlateau 
        

        
          
                   'strict': True,  # enforce that the monitor exists for ReduceLROnPlateau 
        

        
          
               } 
        
    
  


the interval is set as epoch. It means the update will always come after each epoch, even though there is a line to update the learning rate on steps at 
  
    
      pytorch-lightning/pytorch_lightning/trainer/training_loop.py
    
    
         Line 573
      in
      f477c2f
    
  
  
    

        
          
           self.update_train_loop_lr_schedulers(monitor_metrics=monitor_metrics) 
        
    
  


This line will never actually happen because the scheduler's interval (epoch) is different from the argument interval (step).
Maybe I misunderstood. If yes, how could I update the learning rate on every step?