Usually it doesn’t make sense to use this option, as it might slow down your code significantly.
The small differences in the output usually don’t matter, so I would suggest to only use deterministic=True e.g. for debugging purposes.
Not related to the topic, but if your input size stays the same, you can get some performance boost using torch.backends.cudnn.benchmark = True. This option will perform some benchmarks at the beginning of your training to find and use the best suiting methods internally.