使用gpu加速theano

测试的代码为

from theano import function, config, shared, tensor
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([], tensor.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, tensor.Elemwise) and
              ('Gpu' not in type(x.op).__name__)
              for x in f.maker.fgraph.toposort()]):
    print('Used the cpu')
else:
    print('Used the gpu')

运行cpu的代码为

THEANO_FLAGS=device=cpu python gpu_tutorial1.py

运行gpu的代码为

THEANO_FLAGS=device=cuda0 python gpu_tutorial1.py

THEANO_FLAGS='device=cuda1' python cifar10.py >train_cifar10.log

0表示使用编号为0的进行训练

[1] theano文档