tensorflow查看使用的是cpu还是gpu

https://stackoverflow.com/questions/38009682/how-to-tell-if-tensorflow-is-using-gpu-acceleration-from-inside-python-shell

• 方法１

from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())

• 方法２
  
  

• 方法３
  
  

import tensorflow as tf
with tf.device('/gpu:0'):
    a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
    b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
    c = tf.matmul(a, b)

with tf.Session() as sess:
    print (sess.run(c))

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安装了tensorflow-gpu,但是train的时候用的还是cpu.用方法1能检测到gpu,但实际上计算的时候还是用了cpu．用方法3可以检测出来.

import tensorflow as tf
tf.test.is_gpu_available()

找到libcudart.so所在位置,添加路径到.bashrc

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64

吐血,我机器上的是cuda10.1．　　

https://github.com/tensorflow/tensorflow/issues/26289



pip装的不支持cuda10.1....支持到cuda10.0

重新安装cuda10.0 https://developer.nvidia.com/cuda-10.0-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1604&target_type=runfilelocal下载,安装．done!

安装cudnn

https://developer.nvidia.com/rdp/cudnn-download

感动,终于在gpu上跑起来了！

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