Not sure if this affects the result but note that the link you provided is for theano 0.8.X, not theano 0.9.0 as your title implies.
On Thursday, June 15, 2017 at 2:45:26 PM UTC-7, Meier Benjamin wrote: > > Hello, > > I use the follwing test program: > https://theano.readthedocs.io/en/0.8.x/tutorial/using_gpu.html > > 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') > > And I get this output: > > root@21cfc9b009d4:/code/tmp/test# THEANO_FLAGS='floatX=float32,device=cuda0' > python gpu_test.py > Using cuDNN version 5105 on context None > Mapped name None to device cuda0: TITAN X (Pascal) (0000:87:00.0) > [GpuElemwise{exp,no_inplace}(<GpuArrayType<None>(float32, (False,))>), > HostFromGpu(gpuarray)(GpuElemwise{exp,no_inplace}.0)] > Looping 1000 times took 0.221684 seconds > Result is [ 1.23178029 1.61879349 1.52278066 ..., 2.20771813 2.29967761 > 1.62323296] > Used the cpu > > > For some reason theano still uses the CPU? But it already prints the GPU > infos? Do I do something wrong? > > Thank you very much > > > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
