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我知道Tensorflow可以通过"/cpu0"
或"/gpu0"
明确地将计算放置在任何设备上。但是,这是硬编码的。有没有办法用内置的API迭代所有可见的设备?在Tensorflow中循环cpu和gpu设备
我知道Tensorflow可以通过"/cpu0"
或"/gpu0"
明确地将计算放置在任何设备上。但是,这是硬编码的。有没有办法用内置的API迭代所有可见的设备?在Tensorflow中循环cpu和gpu设备
这里是你想拥有的一切:
import tensorflow as tf
from tensorflow.python.client import device_lib
def get_all_devices():
local_device_protos = device_lib.list_local_devices()
return [x.name for x in local_device_protos]
all_devices = get_all_devices()
for device_name in all_devices:
with tf.device(device_name):
if "cpu" in device_name:
# Do something
pass
if "gpu" in device_name:
# Do something else
pass
代码是从最好的答案在这里启发:How to get current available GPUs in tensorflow?
【如何获得tensorflow当前可用的GPU?](HTTPS的可能重复: //stackoverflow.com/questions/38559755/how-to-get-current-available-gpus-in-tensorflow) –