已经安装cuda但是tensorflow仍然使用cpu加速的问题

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

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