使用gpu加速theano

测试的代码为

from theano import function, config, shared, tensorimport numpyimport timevlen = 10 * 30 * 768  # 10 x #cores x # threads per coreiters = 1000rng = 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

0表示使用编号为0的进行训练

[1] theano文档