如何在 Python 中获取每秒的 GPU 使用率 [英] How to get every second's GPU usage in Python

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问题描述

我有一个由 tensorflow-gpu 运行的模型,我的设备是 nvidia.我想列出每一秒的 GPU 使用率,以便我可以测量平均/最大 GPU 使用率.我可以手动打开两个终端,一个是运行模型,另一个是通过nvidia-smi -l 1测量.当然,这不是一个好方法.我也尝试使用 Thread 来做到这一点,在这里.

I have a model which runs by tensorflow-gpu and my device is nvidia. And I want to list every second's GPU usage so that I can measure average/max GPU usage. I can do this mannually by open two terminals, one is to run model and another is to measure by nvidia-smi -l 1. Of course, this is not a good way. I also tried to use a Thread to do that, here it is.

import subprocess as sp
import os
from threading import Thread

class MyThread(Thread):
    def __init__(self, func, args):
        super(MyThread, self).__init__()
        self.func = func
        self.args = args

    def run(self):
        self.result = self.func(*self.args)

    def get_result(self):
        return self.result

def get_gpu_memory():
   output_to_list = lambda x: x.decode('ascii').split('\n')[:-1]
   ACCEPTABLE_AVAILABLE_MEMORY = 1024
   COMMAND = "nvidia-smi -l 1 --query-gpu=memory.used --format=csv"
   memory_use_info = output_to_list(sp.check_output(COMMAND.split()))[1:]
   memory_use_values = [int(x.split()[0]) for i, x in enumerate(memory_use_info)]
   return memory_use_values

def run():
   pass

t1 = MyThread(run, args=())
t2 = MyThread(get_gpu_memory, args=())

t1.start()
t2.start()
t1.join()
t2.join()
res1 = t2.get_result()

然而,这也不会返回每一秒的使用情况.有什么好的解决办法吗?

However, this does not return every second's usage as well. Is there a good solution?

推荐答案

在命令nvidia-smi -l 1 --query-gpu=memory.used --format=csv

-l 代表:

-l, --loop= 以指定的第二个间隔探测直到 Ctrl+C.

所以命令:

COMMAND = 'nvidia-smi -l 1 --query-gpu=memory.used --format=csv'
sp.check_output(COMMAND.split())

永远不会终止并返回.

如果您将事件循环从命令 (nvidia-smi) 中删除到 python,它会起作用.

It works if you remove the event loop from the command(nvidia-smi) to python.

代码如下:

import subprocess as sp
import os
from threading import Thread , Timer
import sched, time

def get_gpu_memory():
    output_to_list = lambda x: x.decode('ascii').split('\n')[:-1]
    ACCEPTABLE_AVAILABLE_MEMORY = 1024
    COMMAND = "nvidia-smi --query-gpu=memory.used --format=csv"
    try:
        memory_use_info = output_to_list(sp.check_output(COMMAND.split(),stderr=sp.STDOUT))[1:]
    except sp.CalledProcessError as e:
        raise RuntimeError("command '{}' return with error (code {}): {}".format(e.cmd, e.returncode, e.output))
    memory_use_values = [int(x.split()[0]) for i, x in enumerate(memory_use_info)]
    # print(memory_use_values)
    return memory_use_values


def print_gpu_memory_every_5secs():
    """
        This function calls itself every 5 secs and print the gpu_memory.
    """
    Timer(5.0, print_gpu_memory_every_5secs).start()
    print(get_gpu_memory())

print_gpu_memory_every_5secs()

"""
Do stuff.
"""

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