Hello! I’m working on making a inspector which examines each tensor, or nn.Module’s gpu/cpu memory resource consumption. (since nvidia-smi only shows total consumption) Is there any built-in pytorch method to achieve this goal? Thanks!

Hi Smth, running a very basic code on pytorch to learn about the memory usage. But the following error pops up. Any suggestions would be helpful OSError Traceback (most recent call last) in () 1 cpuStats() ----> 2 memReport() in memReport() 1 def memReport()…

@aakashbhatia19 i’ve edited the original snippet for PyTorch 0.4 and above.

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Inspect memory usage

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smth September 30, 2017, 10:36pm 2

How pytorch releases variable garbage?

Two methods which I frequently use for debugging: By @smth def memReport(): for obj in gc.get_objects(): if torch.is_tensor(obj): print(type(obj), obj.size()) def cpuStats(): print(sys.version) print(psutil.cpu_percent()) print(psutil.virtual_memory()) # physical memory usage pid = os.getpid() py = psutil.Process(pid) memoryUse = py.memory_info()[0] / 2. ** 30 # memory use in GB...I think print('memory GB:',…

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