trainer.global_step print repetitive steps when there are more that one gradient_accumulation_steps 
I am using the latest pytorch_lighting version from conda.  Seems in this version, trainer.global_step change with gradient accumulation steps.  Also, the number of entire training steps. In the previous version, this wasn't the case.
What is the correct approach if I want to do some task in every 5000 training steps? should I use self.trainer.global_step or batch_idx ?
When I use self.trainer.global_step actually repeats a number of times equal to the gradient accumulation steps.