标签：nas theano range lse mes 小程序 int fun top
安装了keras、theano之后，一直以为自己用的GPU，今天找到一个小程序测试一下，竟然一直在用CPU（黑人问号）
from theano import function, config, shared, sandbox
import theano.tensor as T
import numpy
import time
vlen = 10 * 30 * 768 # 10 x #cores x # threads per core
iters = 1000
rng = numpy.random.RandomState(22)
x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
f = function([], T.exp(x))
print(f.maker.fgraph.toposort())
t0 = time.time()
for i in range(iters):
r = f()
t1 = time.time()
print("Looping %d times took %f seconds" % (iters, t1 - t0))
print("Result is %s" % (r,))
if numpy.any([isinstance(x.op, T.Elemwise) for x in f.maker.fgraph.toposort()]):
print(‘Used the cpu‘)
else:
print(‘Used the gpu‘)
解决方案：
pip list 查看有没有安装#tensorflow和tensorboard
pip uninstall tensorflow
pip uninstall keras
pip uninastall tensorflow-gpu
pip install tendorflow-gpu
pip install keras
把页面关了，重启
已经安装cuda但是tensorflow仍然使用cpu加速的问题
标签：nas theano range lse mes 小程序 int fun top
原文地址：https://www.cnblogs.com/kongle666/p/9456417.html
