code: def is_cuda_memory_close(memory_stats_torch, memory_stats_fabric):
      # We require Fabric's peak memory usage to be smaller or equal to that of PyTorch
      return (
          memory_stats_torch["allocated_bytes.all.peak"]
          >= memory_stats_fabric["allocated_bytes.all.peak"]
      )
  
file_path: pytorch-lightning/tests/parity_fabric/utils.py
imports: import os
  import torch
  from lightning.fabric.accelerators.cuda import _clear_cuda_memory
label_desc: Use image node_id 3 for calling a global function with example usage: is_cuda_memory_close(memory_stats_torch, memory_stats_fabric) and returns: unknown