code: def clear_mem(verbose: bool = False):
      """
      This function is used to clear the memory allocated by PyTorch.
      It does so by calling the garbage collector to release unused GPU memory.
      After clearing the memory, it prints the current amount of memory still allocated by PyTorch (post-clean).
  
      Parameters:
      verbose (bool): Whether to print additional information.
      """
  
      gc.collect()
      torch.cuda.empty_cache()
      print(
          f"torch.cuda.memory_allocated: {torch.cuda.memory_allocated(0) / 1024**3:.2f}GB"
      )
  
      if verbose:
  
          def try_attr(x, a):
              try:
                  return getattr(x, a)
              except:
                  # amazing that this can cause...
                  # (AttributeError, OSError, AssertionError, RuntimeError, ModuleNotFoundError)
                  return None
  
          for obj in gc.get_objects():
              if torch.is_tensor(obj) or torch.is_tensor(
                  try_attr(obj, "data")
              ):
                  print(type(obj), obj.size(), obj.dtype)
  
imports: import gc
  import torch
  from transformers import AutoTokenizer
label_desc: Use image node_id 2 for calling a global function with example usage: clear_mem(verbose) and returns: getattr, None