本文所述如题; 给出两个python版本的NVIDIA显卡管理查询工具 1. py3nvml github下载地址: https://github.com/fbcotter/py3nvml Requires Python 3.5+. Installation From PyPi: $ pip install py3nvml From GitHub:
本文所述如题;
给出两个python版本的NVIDIA显卡管理查询工具
1. py3nvml
github下载地址:
https://github.com/fbcotter/py3nvml
Requires
Python 3.5+.
Installation
From PyPi:
$ pip install py3nvmlFrom GitHub:
$ pip install -e git+https://github.com/fbcotter/py3nvml#egg=py3nvmlOr, download and pip install:
$ git clone https://github.com/fbcotter/py3nvml$ cd py3nvml
$ pip install .
2. pyvnml
github地址:
https://github.com/gpuopenanalytics/pynvml
Requires
Python 3, or an earlier version with the ctypes module.
Installation
pip install .Usage
You can use the lower level nvml bindings
>>> from pynvml import *>>> nvmlInit()
>>> print("Driver Version:", nvmlSystemGetDriverVersion())
Driver Version: 410.00
>>> deviceCount = nvmlDeviceGetCount()
>>> for i in range(deviceCount):
... handle = nvmlDeviceGetHandleByIndex(i)
... print("Device", i, ":", nvmlDeviceGetName(handle))
...
Device 0 : Tesla V100
>>> nvmlShutdown()
Or the higher level nvidia_smi API
from pynvml.smi import nvidia_sminvsmi = nvidia_smi.getInstance()
nvsmi.DeviceQuery('memory.free, memory.total')from pynvml.smi import nvidia_smi
nvsmi = nvidia_smi.getInstance()
print(nvsmi.DeviceQuery('--help-query-gpu'), end='\n')