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July 17, 2017 07:18
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A wget-able copy of the test script from Theano. For the most recent version, please see http://deeplearning.net/software/theano/tutorial/using_gpu.html#testing-theano-with-gpu
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| 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') |
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