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  1.  
  2. from theano import function, config, shared, sandbox, tensor, Out
  3. import numpy
  4. import time
  6. vlen = 10 * 30 * 768 # 10 x # cores x # threads per core
  7. iters = 1000
  9. rng = numpy.random.RandomState(22)
  10. x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
  11. f1 = function([], sandbox.cuda.basic_ops.gpu_from_host(tensor.exp(x)))
  12. f2 = function([],
  13. Out(sandbox.cuda.basic_ops.gpu_from_host(tensor.exp(x)),
  14. borrow=True))
  15. t0 = time.time()
  16. for i in range(iters):
  17. r = f1()
  18. t1 = time.time()
  19. no_borrow = t1 - t0
  20. t0 = time.time()
  21. for i in range(iters):
  22. r = f2()
  23. t1 = time.time()
  24. print(
  25. "Looping %s times took %s seconds without borrow "
  26. "and %s seconds with borrow" % (iters, no_borrow, (t1 - t0))
  27. )
  28. if numpy.any([isinstance(x.op, tensor.Elemwise) and
  29. ('Gpu' not in type(x.op).__name__)
  30. for x in f1.maker.fgraph.toposort()]):
  31. print('Used the cpu')
  32. else:
  33. print('Used the gpu')
  34.  
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