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# taken from http://deeplearning.net/software/theano/tutorial/using_gpu.html | |
from theano import function, config, shared, sandbox | |
import theano.sandbox.cuda.basic_ops | |
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), 'float32')) | |
f = function([], sandbox.cuda.basic_ops.gpu_from_host(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,)) | |
print("Numpy result is %s" % (numpy.asarray(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') |
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