使用gpu加速theano

时间:2022-06-02 05:14:43

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

0表示使用编号为0的进行训练




[1] theano文档