code: def cuda_rng_step():
      for device_id in range(torch.cuda.device_count()):
          torch.rand(1, device=f"cuda:{device_id}")
  
file_path: avalanche/avalanche/training/determinism/cuda_rng.py
imports: import warnings
  import torch
  from torch import default_generator
label_desc: Use image node_id 5 for calling a global function with example usage: cuda_rng_step() without return types